CN113204741A - Method and system suitable for intelligent power consumption data aggregation - Google Patents

Method and system suitable for intelligent power consumption data aggregation Download PDF

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CN113204741A
CN113204741A CN202110389155.9A CN202110389155A CN113204741A CN 113204741 A CN113204741 A CN 113204741A CN 202110389155 A CN202110389155 A CN 202110389155A CN 113204741 A CN113204741 A CN 113204741A
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intelligent electric
terminal
trusted
control center
party
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Inventor
梁晓兵
赵兵
许海清
葛得辉
翟峰
孙炜
岑炜
陈昊
付义伦
曹永峰
李保丰
徐萌
王晖南
刘佳易
武文萍
杨兆忠
高强
王昱瑾
许进
陈力波
刘鹰
许斌
孔令达
冯云
冯占成
周琪
任博
张庚
韩文博
郑旖旎
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State Grid Corp of China SGCC
China Electric Power Research Institute Co Ltd CEPRI
Marketing Service Center of State Grid Shanxi Electric Power Co Ltd
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State Grid Corp of China SGCC
China Electric Power Research Institute Co Ltd CEPRI
Marketing Service Center of State Grid Shanxi Electric Power Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2455—Query execution
    • G06F16/24553—Query execution of query operations
    • G06F16/24554—Unary operations; Data partitioning operations
    • G06F16/24556—Aggregation; Duplicate elimination
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
    • G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
    • G06F21/6227—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database where protection concerns the structure of data, e.g. records, types, queries
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/64—Protecting data integrity, e.g. using checksums, certificates or signatures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas or water supply
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2221/00—Indexing scheme relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F2221/21—Indexing scheme relating to G06F21/00 and subgroups addressing additional information or applications relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F2221/2107—File encryption

Abstract

The invention discloses a method and a system suitable for intelligent power consumption data aggregation, and belongs to the technical field of information safety. The method comprises the following steps: generating initialization parameters of the intelligent electric energy meter and the convergence terminal by a trusted third party, and controlling the intelligent electric energy meter and the convergence terminal to use the initialization parameters to complete initialization; after the initialization of the intelligent electric energy meter and the convergence terminal is completed, registering the intelligent electric energy meter to the convergence terminal and a trusted third party, registering the convergence terminal to the control center and the trusted third party, and registering the control center to the trusted third party; after the registration is completed, the intelligent electric energy meter sends user data to the convergence terminal, the convergence terminal acquires a user ID according to the user data and sends the user ID to the control center and the trusted third party, the trusted third party generates a blinding factor according to the user ID and transmits the blinding factor to the convergence terminal through the control center, and the convergence terminal aggregates the user data according to the blinding factor. The invention has a fault-tolerant mechanism and can protect data privacy.

Description

Method and system suitable for intelligent power consumption data aggregation
Technical Field
The present invention relates to the field of information security technologies, and more particularly, to a method and system suitable for intelligent power consumption data aggregation.
Background
The intelligent power grid is an automatic and intelligent novel power grid formed by combining a computer network and an information infrastructure, on one hand, the intelligent power grid has the characteristics of containing, interacting and opening, power consumers can participate in the operation of the power grid more widely through intelligent electric meters, the bidirectional interaction between the power grid and the power consumers is more frequent, and the power consumption experience of the power consumers is greatly improved. On the other hand, the smart grid has the characteristics of large number of users, strong bidirectional interactivity, complex network boundary and the like, and the openness and the inclusion of the smart grid also provide challenges for safe and reliable operation of the smart grid and privacy protection of power users. In the smart grid, an electric power company periodically acquires the power utilization information of a user through smart devices such as a smart meter and a collection terminal, analyzes the current power utilization condition of the power grid in real time, and regulates and controls the power.
However, the detailed electricity utilization information reveals important privacy such as living habits of users, whether people are at home and the use condition of electrical equipment at home, and the safety and social stability of the users are seriously threatened. Therefore, the research on the advanced smart grid privacy protection technology has important practical significance for ensuring the safe and reliable operation of the smart grid, maintaining the safety of power consumers and maintaining the social stability. Most of the existing privacy protection and data security aggregation technologies are realized based on a homomorphic encryption algorithm, so that large calculation overhead is brought, relatively few consideration is given in the aspect of data aggregation fault tolerance, and the existing privacy protection and data security aggregation technologies are not suitable for privacy protection and aggregation analysis processing of massive power consumption data by an intelligent power consumption information system, so that research on an intelligent power consumption data security high-efficiency aggregation method supporting fault tolerance and privacy protection is urgently needed, and the overall security of the intelligent power consumption information system is improved.
Disclosure of Invention
In order to solve the above problems, the present invention provides a method suitable for intelligent power consumption data aggregation, including:
generating initialization parameters of the intelligent electric energy meter and the convergence terminal by a trusted third party, and controlling the intelligent electric energy meter and the convergence terminal to use the initialization parameters to complete initialization;
after the initialization of the intelligent electric energy meter and the convergence terminal is completed, registering the intelligent electric energy meter to the convergence terminal and a trusted third party, registering the convergence terminal to the control center and the trusted third party, and registering the control center to the trusted third party;
after the registration is completed, the intelligent electric energy meter sends user data to the convergence terminal, the convergence terminal acquires a user ID according to the user data and sends the user ID to the control center and the trusted third party, the trusted third party generates a blinding factor according to the user ID and transmits the blinding factor to the convergence terminal through the control center, and the convergence terminal aggregates the user data according to the blinding factor.
Optionally, the generating, by the trusted third party, the initialization parameter of the intelligent electric energy meter and the aggregation terminal includes:
the TTP gives a security parameter k, two large prime numbers p and q are selected, the p and the q meet | p | ═ k and q | (p-1), G is a cyclic group with the order of p, G is a generator of G, and the order of the generator is P
Figure BDA0003015791680000021
For secure one-way hash functions, initialization parameters are determined as { p, q, g, H0,H1,H2G }, wherein,
Figure BDA0003015791680000022
is a cryptographic operation cycle group.
Optionally, the initialization parameters are { p, q, g, H0,H1,H2G } is disclosed.
Optionally, registering the intelligent electric energy meter to a trusted third party and a convergence terminal, registering the convergence terminal to a control center and the trusted third party, and registering the control center to the trusted third party specifically include:
registering the intelligent electric energy meter to a trusted third party and a convergence terminal comprises the following steps:
intelligent electric energy meter SMijSending a registration request and an intelligent electric energy meter user ID _ SM to a trusted third party TTPij；
TTP random selection r of trusted third partyij,
Figure BDA0003015791680000023
According to xijDetermining
Figure BDA0003015791680000024
Wherein r isijIs a random number xijAnd YijFor intelligent electric energy meter SMijA public and private key pair;
calculating a blinding factor pi from the ID of the intelligent userijWhere i denotes the ith smart meter, j 1,2i1,πi2,.......πin，
Figure BDA0003015791680000031
Wherein n is the number of intelligent electric energy meters actually participating in aggregation;
trusted third party TTP sends parameter ID _ TTP, xij,Yij,rij,πijTo intelligent electric energy meter SMijIntelligent electric energy meter SMijTo rij,πiSecret storage;
to intelligent electric energy meter SMijTo a convergence terminal AggiAnd registering, including:
intelligent electric energy meter SMijSending registration request and ID _ SMijFor gathering terminal AggiRegistering;
the sink terminal will sink the terminal ID _ AggiSend to intelligent electric energy meter SMij。
The pair of convergence terminals AggiRegistering with a control center CC and a trusted third party TTP, comprising:
aggregation terminal AggiSending registration request and ID _ Agg to trusted third party TTPi；
TTP random selection r of trusted third partyi,
Figure BDA0003015791680000032
Computing
Figure BDA0003015791680000033
xi,YiFor a convergence terminal AggiPublic and private key pair of send (ID _ TTP, r)i,xi,Yi,Yij) For gathering terminal Aggi；
Aggregation terminal AggiSending registration request and ID _ AggiFeeding the control center CC;
the control center CC sends the ID _ CC to the aggregation terminal Aggi；
Registering the control center with a trusted third party, comprising:
the control center CC sends the ID _ CC to the TTP;
trusted third party TTP Transmission (ID _ TTP, Y)i) The registration is completed for the control center CC.
Optionally, the aggregating terminal aggregates the user data according to the blinding factor, which specifically includes:
intelligent electric energy meter SMijAcquiring power consumption data m of power consumerijSelecting a random number
Figure BDA0003015791680000034
Using secret stored random numbers rijCalculating the electricity consumption data ciphertext and the signature information, wherein the calculation process is as follows:
Figure BDA0003015791680000035
Figure BDA0003015791680000036
Figure BDA0003015791680000037
Figure BDA0003015791680000038
Figure BDA0003015791680000039
Figure BDA00030157916800000310
Figure BDA00030157916800000311
si＝ki-φi·xij modp
after the calculation is finished, the intelligent electric energy meter SMijDelivery ID _ SMij,ci,
Figure BDA00030157916800000312
di,siT to the aggregation terminal Aggi；
Wherein d isiFor the user in the clear of electricity data, ciA data cipher text for the user, t is the current time stamp, p1 ijIs the average value data component p of the intelligent ammeter after the blinding processing2 ijCalculating variance data component p for the intelligent electric meter after the blind processing3 ijAnd p4 ijThe blind processing is carried out on the single-factor variance data component of the intelligent electric meter;
aggregation terminal AggiCalculating received ID _ SMij,ci,
Figure BDA0003015791680000041
di,siThe hash value of t, and calculating
Figure BDA0003015791680000042
Verifying smart meter signature siThe verification process is as follows:
Figure BDA0003015791680000043
Figure BDA0003015791680000044
where j ∈ {1, 2.. n }.
If the verification is passed, calculating the aggregated data as follows:
Figure BDA0003015791680000045
Figure BDA0003015791680000046
the above-mentioned
Figure BDA0003015791680000047
Gathering the terminal Agg after the blind processingiThe aggregated data component of the mean value of the smart meters,
Figure BDA0003015791680000048
gathering the terminal Agg after the blind processingiThe converged smart meter counts variance data components,
Figure BDA0003015791680000049
and
Figure BDA00030157916800000410
gathering the terminal Agg after the blind processingiThe converged single-factor variance data components of the intelligent electric meter;
aggregation terminal AggiRandom selection
Figure BDA00030157916800000411
Computing
Figure BDA00030157916800000412
qi＝θi-ψiximodp，
Figure BDA00030157916800000413
qiIs AggiSignature value of wiAnd psiiIs AggiIs the current timestamp, and sends
Figure BDA00030157916800000414
Feeding the control center CC;
aggregation terminal AggiTransmission (ID _ SM)ij,ci,di) For a trusted third party TTP, the TTP calculates a blinding factor and a blinding-removing factor according to the ID of the intelligent electric energy meter actually participating in the convergence, and if the TTP actually participates in the intelligent electric energy meter SM with data aggregationijThe corresponding blinding factor is pii1,πi2,.......πin，
Figure BDA00030157916800000415
Then TTP calculates
Figure BDA00030157916800000416
Where j is 1,2,.. n, let pii0＝-πimodp, trusted third party TTP sending pii0To a control center CC wherei0Is a blindness-removing factor;
control center CC calculation
Figure BDA00030157916800000417
Authentication
Figure BDA00030157916800000418
Randomly selecting a set of fractions delta1,δ2,......δn,δn∈[1,2S]Detecting
Figure BDA00030157916800000419
Where s is a small integer with less computational cost, where w is verifiediThe process is as follows:
Figure BDA00030157916800000420
Figure BDA0003015791680000051
control center CC calculates C1,C2,C3,C4Obtaining the consumption data of the whole power consumer by solving the discrete logarithm of c and n by adopting Pollard's lambda algorithm, and outputting the result as
Figure BDA0003015791680000052
Wherein, C1The average value data component C of the intelligent electric meter gathered by the control center CC after the blinding processing2Calculating variance data component C for intelligent electric meter converged by control center CC after blind processing3And C4For the intelligent electric meter single-factor variance data component gathered by the control center CC after the blinding processing, the calculation process is as follows:
Figure BDA0003015791680000053
Figure BDA0003015791680000054
Figure BDA0003015791680000055
Figure BDA0003015791680000056
if the arbitration is needed, the trusted third party TTP may decrypt the ciphertext data aggregated by the control center CC, which is specifically as follows:
Figure BDA0003015791680000061
optionally, the control center CC analyzes the power consumer data, where the data analysis includes data analysis of different power rate policies and data analysis under the same power rate policy, and specifically includes:
make SBExpressing the sum of squares of different electricity price strategies, using SwThe square sum under the same electricity price strategy is represented, and the specific calculation is as follows:
Figure BDA0003015791680000062
Figure BDA0003015791680000063
the control center can then calculate the F-value of the F-test:
Figure BDA0003015791680000064
the F value of the F-test is mainly used for judging whether the electricity price strategy has a remarkable influence on the electricity consumption of the user.
The invention also provides a system suitable for intelligent power utilization data aggregation, which comprises the following components:
the initialization module controls a trusted third party to generate initialization parameters of the intelligent electric energy meter and the convergence terminal and controls the intelligent electric energy meter and the convergence terminal to use the initialization parameters to complete initialization;
the registration module registers the intelligent electric energy meter to the convergence terminal and a trusted third party, registers the convergence terminal to the control center and the trusted third party and registers the control center to the trusted third party after the intelligent electric energy meter and the convergence terminal are initialized;
and the aggregation module is used for sending user data to the aggregation terminal by the intelligent electric energy meter after the registration is finished, the aggregation terminal acquires a user ID according to the user data and sends the user ID to the control center and the credible third party, the credible third party generates a blinding factor according to the user ID and transmits the blinding factor to the aggregation terminal through the control center, and the aggregation terminal aggregates the user data according to the blinding factor.
Optionally, the generating, by the trusted third party, the initialization parameter of the intelligent electric energy meter and the aggregation terminal includes:
the TTP gives a security parameter k, two large prime numbers p and q are selected, the p and the q meet | p | ═ k and q | (p-1), G is a cyclic group with the order of p, G is a generator of G, and the order of the generator is P
Figure BDA0003015791680000071
For secure one-way hash functions, initialization parameters are determined as { p, q, g, H0,H1,H2G }, wherein,
Figure BDA0003015791680000072
is a cryptographic operation cycle group.
Optionally, the initialization parameters are { p, q, g, H0,H1,H2G } is disclosed.
Optionally, registering the intelligent electric energy meter to a trusted third party and a convergence terminal, registering the convergence terminal to a control center and the trusted third party, and registering the control center to the trusted third party specifically include:
registering the intelligent electric energy meter to a trusted third party and a convergence terminal comprises the following steps:
intelligent electric energy meter SMijSending a registration request and an IDID _ SM of the intelligent electric energy meter user to a trusted third party TTPij；
TTP random selection r of trusted third partyij,
Figure BDA0003015791680000073
According to xijDetermining
Figure BDA0003015791680000074
Wherein r isijIs a random number xijAnd YijFor intelligent electric energy meter SMijA public and private key pair;
calculating a blinding factor pi from the ID of the intelligent userijWhere i denotes the ith smart meter, j 1,2i1,πi2,.......πin，
Figure BDA0003015791680000075
Wherein n is the number of intelligent electric energy meters actually participating in aggregation;
trusted third party TTP sends parameter ID _ TTP, xij,Yij,rij,πijTo intelligent electric energy meter SMijIntelligent electric energy meter SMijTo rij,πiSecret storage;
to intelligent electric energy meter SMijTo a convergence terminal AggiAnd registering, including:
intelligent electric energy meter SMijSending registration request and ID _ SMijFor gathering terminal AggiRegistering;
the sink terminal will sink the terminal ID _ AggiSend to intelligent electric energy meter SMij。
The pair of convergence terminals AggiRegistering with a control center CC and a trusted third party TTP, comprising:
aggregation terminal AggiSending registration request and ID _ Agg to trusted third party TTPi；
TTP random selection r of trusted third partyi,
Figure BDA0003015791680000076
Computing
Figure BDA0003015791680000077
xi,YiFor a convergence terminal AggiPublic and private key pair of send (ID _ TTP, r)i,xi,Yi,Yij) For gathering terminal Aggi；
Aggregation terminal AggiSending registration request and ID _ AggiFeeding the control center CC;
the control center CC sends the ID _ CC to the aggregation terminal Aggi；
Registering the control center with a trusted third party, comprising:
the control center CC sends the ID _ CC to the TTP;
trusted third party TTP Transmission (ID _ TTP, Y)i) The registration is completed for the control center CC.
Optionally, the aggregating terminal aggregates the user data according to the blinding factor, which specifically includes:
intelligent electric energy meter SMijAcquiring power consumption data m of power consumerijSelecting a random number
Figure BDA0003015791680000081
Using secret stored random numbers rijCalculating the electricity consumption data ciphertext and the signature information, wherein the calculation process is as follows:
Figure BDA0003015791680000082
Figure BDA0003015791680000083
Figure BDA0003015791680000084
Figure BDA0003015791680000085
Figure BDA0003015791680000086
Figure BDA0003015791680000087
Figure BDA0003015791680000088
si＝ki-φi·xij modp
after the calculation is finished, the intelligent electric energy meter SMijDelivery ID _ SMij,ci,
Figure BDA0003015791680000089
di,siT to the aggregation terminal Aggi；
Wherein d isiFor the user in the clear of electricity data, ciA data cipher text for the user, t is the current time stamp, p1 ijIs the average value data component p of the intelligent ammeter after the blinding processing2 ijCalculating variance data component p for the intelligent electric meter after the blind processing3 ijAnd p4 ijThe blind processing is carried out on the single-factor variance data component of the intelligent electric meter;
aggregation terminal AggiCalculating received ID _ SMij,ci,
Figure BDA00030157916800000810
di,siThe hash value of t, and calculating
Figure BDA00030157916800000811
Verifying smart meter signature siThe verification process is as follows:
Figure BDA00030157916800000812
Figure BDA00030157916800000813
where j ∈ {1, 2.. n }.
If the verification is passed, calculating the aggregated data as follows:
Figure BDA00030157916800000814
Figure BDA00030157916800000815
the above-mentioned
Figure BDA00030157916800000816
Gathering the terminal Agg after the blind processingiThe aggregated data component of the mean value of the smart meters,
Figure BDA00030157916800000817
gathering the terminal Agg after the blind processingiThe converged smart meter counts variance data components,
Figure BDA00030157916800000818
and
Figure BDA00030157916800000819
gathering the terminal Agg after the blind processingiThe converged single-factor variance data components of the intelligent electric meter;
aggregation terminal AggiRandom selection
Figure BDA00030157916800000820
Computing
Figure BDA00030157916800000821
qi＝θi-ψiximodp，
Figure BDA00030157916800000822
qiIs AggiSignature value of wiAnd psiiIs AggiIs the current timestamp, and sends
Figure BDA0003015791680000091
Feeding the control center CC;
aggregation terminal AggiTransmission (ID _ SM)ij,ci,di) For a trusted third party TTP, the TTP calculates a blinding factor and a blinding-removing factor according to the ID of the intelligent electric energy meter actually participating in the convergence, and if the TTP actually participates in the intelligent electric energy meter SM with data aggregationijThe corresponding blinding factor is pii1,πi2,.......πin，
Figure BDA0003015791680000092
Then TTP calculates
Figure BDA0003015791680000093
Where j is 1,2,.. n, let pii0＝-πimodp, trusted third party TTP sending pii0To a control center CC wherei0Is a blindness-removing factor;
control center CC calculation
Figure BDA0003015791680000094
Authentication
Figure BDA0003015791680000095
Randomly selecting a set of fractions delta1,δ2,......δn,δn∈[1,2S]Detecting
Figure BDA0003015791680000096
Where s is a small integer with less computational cost, where w is verifiediThe process is as follows:
Figure BDA0003015791680000097
control center CC calculates C1,C2,C3,C4Obtaining the consumption data of the whole power consumer by solving the discrete logarithm of c and n by adopting Pollard's lambda algorithm, and outputting the result as
Figure BDA0003015791680000098
Wherein, C1The average value data component C of the intelligent electric meter gathered by the control center CC after the blinding processing2Calculating variance data component C for intelligent electric meter converged by control center CC after blind processing3And C4For the intelligent electric meter single-factor variance data component gathered by the control center CC after the blinding processing, the calculation process is as follows:
Figure BDA0003015791680000099
Figure BDA0003015791680000101
Figure BDA0003015791680000102
Figure BDA0003015791680000103
if the arbitration is needed, the trusted third party TTP may decrypt the ciphertext data aggregated by the control center CC, which is specifically as follows:
Figure BDA0003015791680000104
optionally, the system further includes a data analysis module, where the data analysis module analyzes the power consumer data by using the control center CC, and the data analysis includes data analysis of different power rate policies and data analysis under the same power rate policy, and specifically includes:
make SBExpressing the sum of squares of different electricity price strategies, using SwThe square sum under the same electricity price strategy is represented, and the specific calculation is as follows:
Figure BDA0003015791680000105
Figure BDA0003015791680000106
the control center can then calculate the F-value of the F-test:
Figure BDA0003015791680000107
the F value of the F-test is mainly used for judging whether the electricity price strategy has a remarkable influence on the electricity consumption of the user.
On the premise of realizing privacy protection of the power consumers, the control center can realize analysis of the average value, the variance and the single-factor variance of the power consumption data of the power consumers, and effective arbitration is carried out when data disputes occur between the power consumers and a power company.
The intelligent electric energy meter control system has a fault-tolerant mechanism, and when individual intelligent electric energy meters have faults and data cannot be transmitted to the control center, data aggregation and processing can still be normally executed.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a block diagram of the system of the present invention.
Detailed Description
The exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, however, the present invention may be embodied in many different forms and is not limited to the embodiments described herein, which are provided for complete and complete disclosure of the present invention and to fully convey the scope of the present invention to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the accompanying drawings is not intended to be limiting of the invention. In the drawings, the same units/elements are denoted by the same reference numerals.
Unless otherwise defined, terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Further, it will be understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense.
The invention provides a method suitable for intelligent electricity consumption data aggregation, which comprises the following steps of:
generating initialization parameters of the intelligent electric energy meter and the convergence terminal by a trusted third party, and controlling the intelligent electric energy meter and the convergence terminal to use the initialization parameters to complete initialization;
after the initialization of the intelligent electric energy meter and the convergence terminal is completed, registering the intelligent electric energy meter to the convergence terminal and a trusted third party, registering the convergence terminal to the control center and the trusted third party, and registering the control center to the trusted third party;
after the registration is finished, sending user data to a convergence terminal by the intelligent electric energy meter, acquiring a user ID by the convergence terminal according to the user data, sending the user ID to a control center and a trusted third party, generating a blinding factor by the trusted third party according to the user ID, transmitting the blinding factor to the convergence terminal through the control center, and aggregating the user data by the convergence terminal according to the blinding factor;
and analyzing the power user data by using the control center CC, wherein the data analysis comprises data analysis of different power price strategies and data analysis under the same power price strategy.
The method for generating the intelligent electric energy meter and the initialization parameters of the convergence terminal by the trusted third party comprises the following steps:
the TTP gives a security parameter k, two large prime numbers p and q are selected, the p and the q meet | p | ═ k and q | (p-1), G is a cyclic group with the order of p, G is a generator of G, and the order of the generator is P
Figure BDA0003015791680000121
For secure one-way hash functions, initialization parameters are determined as { p, q, g, H0,H1,H2G }, wherein,
Figure BDA0003015791680000122
is a cryptographic operation cycle group.
Wherein the initialization parameters are { p, q, g, H0,H1,H2G } is disclosed.
The intelligent electric energy meter is registered to a trusted third party and a convergence terminal, the convergence terminal is registered to a control center and the trusted third party, and the control center is registered to the trusted third party, and the method specifically comprises the following steps:
registering the intelligent electric energy meter to a trusted third party and a convergence terminal comprises the following steps:
intelligent electric energy meter SMijSending a registration request and an intelligent electric energy meter user ID _ SM to a trusted third party TTPij；
TTP random selection r of trusted third partyij,
Figure BDA0003015791680000123
According to xijDetermining
Figure BDA0003015791680000124
Wherein r isijIs a random number xijAnd YijFor intelligent electric energy meter SMijA public and private key pair;
calculating a blinding factor pi from the ID of the intelligent userijWhere i denotes the ith smart meter, j 1,2i1,πi2,.......πin，
Figure BDA0003015791680000125
Wherein n is the number of intelligent electric energy meters actually participating in aggregation;
trusted third party TTP sends parameter ID _ TTP, xij,Yij,rij,πijTo intelligent electric energy meter SMijIntelligent electric energy meter SMijTo rij,πiSecret storage;
to intelligent electric energy meter SMijTo a convergence terminal AggiAnd registering, including:
intelligent electric energy meter SMijSending registration request and ID _ SMijFor gathering terminal AggiRegistering;
final collectionEnd-to-end aggregation terminal ID _ AggiSend to intelligent electric energy meter SMij。
The pair of convergence terminals AggiRegistering with a control center CC and a trusted third party TTP, comprising:
aggregation terminal AggiSending registration request and ID _ Agg to trusted third party TTPi；
TTP random selection r of trusted third partyi,
Figure BDA0003015791680000131
Computing
Figure BDA0003015791680000132
xi,YiFor a convergence terminal AggiPublic and private key pair of send (ID _ TTP, r)i,xi,Yi,Yij) For gathering terminal Aggi；
Aggregation terminal AggiSending registration request and ID _ AggiFeeding the control center CC;
the control center CC sends the ID _ CC to the aggregation terminal Aggi；
Registering the control center with a trusted third party, comprising:
the control center CC sends the ID _ CC to the TTP;
trusted third party TTP Transmission (ID _ TTP, Y)i) The registration is completed for the control center CC.
The aggregation terminal aggregates the user data according to the blinding factor, and specifically includes:
intelligent electric energy meter SMijAcquiring power consumption data m of power consumerijSelecting a random number
Figure BDA0003015791680000133
Using secret stored random numbers rijCalculating the electricity consumption data ciphertext and the signature information, wherein the calculation process is as follows:
Figure BDA0003015791680000134
Figure BDA0003015791680000135
Figure BDA0003015791680000136
Figure BDA0003015791680000137
Figure BDA0003015791680000138
Figure BDA0003015791680000139
Figure BDA00030157916800001310
si＝ki-φi·xij modp
after the calculation is finished, the intelligent electric energy meter SMijDelivery ID _ SMij,ci,
Figure BDA00030157916800001311
diSi, t to the aggregation terminal Aggi；
Wherein d isiFor the user in the clear of electricity data, ciA data cipher text for the user, t is the current time stamp, p1 ijIs the average value data component p of the intelligent ammeter after the blinding processing2 ijCalculating variance data component p for the intelligent electric meter after the blind processing3 ijAnd p4 ijThe blind processing is carried out on the single-factor variance data component of the intelligent electric meter;
aggregation terminal AggiCalculating received ID _ SMij,ci,
Figure BDA00030157916800001312
di,siThe hash value of t, and calculating
Figure BDA00030157916800001313
Verifying smart meter signature siThe verification process is as follows:
Figure BDA00030157916800001314
Figure BDA00030157916800001315
where j ∈ {1, 2.. n }.
If the verification is passed, calculating the aggregated data as follows:
Figure BDA0003015791680000141
Figure BDA0003015791680000142
the above-mentioned
Figure BDA0003015791680000143
Gathering the terminal Agg after the blind processingiThe aggregated data component of the mean value of the smart meters,
Figure BDA0003015791680000144
gathering the terminal Agg after the blind processingiThe converged smart meter counts variance data components,
Figure BDA0003015791680000145
and
Figure BDA0003015791680000146
gathering the terminal Agg after the blind processingiThe converged single-factor variance data components of the intelligent electric meter;
aggregation terminal AggiRandom selection
Figure BDA0003015791680000147
Computing
Figure BDA0003015791680000148
qi＝θi-ψiximodp，
Figure BDA0003015791680000149
qiIs AggiSignature value of wiAnd psiiIs AggiIs the current timestamp, and sends
Figure BDA00030157916800001410
Feeding the control center CC;
aggregation terminal AggiTransmission (ID _ SM)ij,ci,di) For a trusted third party TTP, the TTP calculates a blinding factor and a blinding-removing factor according to the ID of the intelligent electric energy meter actually participating in the convergence, and if the TTP actually participates in the intelligent electric energy meter SM with data aggregationijThe corresponding blinding factor is pii1,πi2,.......πin，
Figure BDA00030157916800001411
Then TTP calculates
Figure BDA00030157916800001412
Where j is 1,2,.. n, let pii0＝-πimodp, trusted third party TTP sending pii0To a control center CC wherei0Is a blindness-removing factor;
control center CC calculation
Figure BDA00030157916800001413
Authentication
Figure BDA00030157916800001414
Randomly selecting a set of fractions delta1,δ2,......δn,δn∈[1,2S]Detecting
Figure BDA00030157916800001415
Where s is a small integer with less computational cost, where w is verifiediThe process is as follows:
Figure BDA00030157916800001416
Figure BDA00030157916800001417
control center CC calculates C1,C2,C3,C4Obtaining the consumption data of the whole power consumer by solving the discrete logarithm of c and n by adopting Pollard's lambda algorithm, and outputting the result as
Figure BDA00030157916800001418
Wherein, C1The average value data component C of the intelligent electric meter gathered by the control center CC after the blinding processing2Calculating variance data component C for intelligent electric meter converged by control center CC after blind processing3And C4For the intelligent electric meter single-factor variance data component gathered by the control center CC after the blinding processing, the calculation process is as follows:
Figure BDA0003015791680000151
Figure BDA0003015791680000152
Figure BDA0003015791680000153
Figure BDA0003015791680000154
if the arbitration is needed, the trusted third party TTP may decrypt the ciphertext data aggregated by the control center CC, which is specifically as follows:
Figure BDA0003015791680000155
the control center CC analyzes the power consumer data, and the data analysis includes data analysis of different power rate strategies and data analysis under the same power rate strategy, and specifically includes:
make SBExpressing the sum of squares of different electricity price strategies, using SwThe square sum under the same electricity price strategy is represented, and the specific calculation is as follows:
Figure BDA0003015791680000156
Figure BDA0003015791680000161
the control center can then calculate the F-value of the F-test:
Figure BDA0003015791680000162
the F value of the F-test is mainly used for judging whether the electricity price strategy has a remarkable influence on the electricity consumption of the user.
The present invention further provides a system 200 for intelligent power consumption data aggregation, as shown in fig. 2, including:
the initialization module 201 is used for controlling a trusted third party to generate initialization parameters of the intelligent electric energy meter and the convergence terminal, and controlling the intelligent electric energy meter and the convergence terminal to use the initialization parameters to complete initialization;
the registration module 202 is used for registering the intelligent electric energy meter to the convergence terminal and a trusted third party, registering the convergence terminal to the control center and the trusted third party and registering the control center to the trusted third party after the intelligent electric energy meter and the convergence terminal are initialized;
the aggregation module 203 is used for sending user data to the aggregation terminal by the intelligent electric energy meter after the registration is finished, the aggregation terminal acquires a user ID according to the user data and sends the user ID to the control center and the trusted third party, the trusted third party generates a blinding factor according to the user ID and transmits the blinding factor to the aggregation terminal through the control center, and the aggregation terminal aggregates the user data according to the blinding factor;
a data analysis module 204, which analyzes the power consumer data using the control center CC, and the data analysis includes data analysis of different power rate policies and data analysis under the same power rate policy.
The method for generating the intelligent electric energy meter and the initialization parameters of the convergence terminal by the trusted third party comprises the following steps:
the TTP gives a security parameter k, two large prime numbers p and q are selected, the p and the q meet | p | ═ k and q | (p-1), G is a cyclic group with the order of p, G is a generator of G, and the order of the generator is P
Figure BDA0003015791680000163
For secure one-way hash functions, initialization parameters are determined as { p, q, g, H0,H1,H2G }, wherein,
Figure BDA0003015791680000164
is a cryptographic operation cycle group.
Wherein the initialization parameters are { p, q, g, H0,H1,H2G } is disclosed.
The intelligent electric energy meter is registered to a trusted third party and a convergence terminal, the convergence terminal is registered to a control center and the trusted third party, and the control center is registered to the trusted third party, and the method specifically comprises the following steps:
registering the intelligent electric energy meter to a trusted third party and a convergence terminal comprises the following steps:
intelligent electric energy meter SMijSending a registration request and an intelligent electric energy meter user ID _ SM to a trusted third party TTPij；
TTP random selection r of trusted third partyij,
Figure BDA0003015791680000171
According to xijDetermining
Figure BDA0003015791680000172
Wherein r isijIs a random number xijAnd YijFor intelligent electric energy meter SMijA public and private key pair;
calculating a blinding factor pi from the ID of the intelligent userijWhere i denotes the ith smart meter, j 1,2i1,πi2,.......πin，
Figure BDA0003015791680000173
Wherein n is the number of intelligent electric energy meters actually participating in aggregation;
trusted third party TTP sends parameter ID _ TTP, xij,Yij,rij,πijTo intelligent electric energy meter SMijIntelligent electric energy meter SMijTo rij,πiSecret storage;
to intelligent electric energy meter SMijTo a convergence terminal AggiAnd registering, including:
intelligent electric energy meter SMijSending registration request and ID _ SMijFor gathering terminal AggiRegistering;
the sink terminal will sink the terminal ID _ AggiSend to intelligent electric energy meter SMij。
The pair of convergence terminals AggiRegistering with a control center CC and a trusted third party TTP, comprising:
aggregation terminal AggiSending registration request and ID _ Ag to trusted third party TTPgi；
TTP random selection r of trusted third partyi,
Figure BDA0003015791680000174
Computing
Figure BDA0003015791680000175
xi,YiFor a convergence terminal AggiPublic and private key pair of send (ID _ TTP, r)i,xi,Yi,Yij) For gathering terminal Aggi；
Aggregation terminal AggiSending registration request and ID _ AggiFeeding the control center CC;
the control center CC sends the ID _ CC to the aggregation terminal Aggi；
Registering the control center with a trusted third party, comprising:
the control center CC sends the ID _ CC to the TTP;
trusted third party TTP Transmission (ID _ TTP, Y)i) The registration is completed for the control center CC.
The aggregation terminal aggregates the user data according to the blinding factor, and specifically includes:
intelligent electric energy meter SMijAcquiring power consumption data m of power consumerijSelecting a random number
Figure BDA0003015791680000176
Using secret stored random numbers rijCalculating the electricity consumption data ciphertext and the signature information, wherein the calculation process is as follows:
Figure BDA0003015791680000177
Figure BDA0003015791680000178
Figure BDA0003015791680000179
Figure BDA00030157916800001710
Figure BDA0003015791680000181
Figure BDA0003015791680000182
Figure BDA0003015791680000183
si＝ki-φi·xij modp
after the calculation is finished, the intelligent electric energy meter SMijDelivery ID _ SMij,ci,
Figure BDA0003015791680000184
di,siT to the aggregation terminal Aggi；
Wherein d isiFor the user in the clear of electricity data, ciA data cipher text for the user, t is the current time stamp, p1 ijIs the average value data component p of the intelligent ammeter after the blinding processing2 ijCalculating variance data component p for the intelligent electric meter after the blind processing3 ijAnd p4 ijThe blind processing is carried out on the single-factor variance data component of the intelligent electric meter;
aggregation terminal AggiCalculating received ID _ SMij,ci,
Figure BDA0003015791680000185
di,siThe hash value of t, and calculating
Figure BDA0003015791680000186
Verifying smart meter signature siThe verification process is as follows:
Figure BDA0003015791680000187
Figure BDA0003015791680000188
where j ∈ {1, 2.. n }.
If the verification is passed, calculating the aggregated data as follows:
Figure BDA0003015791680000189
Figure BDA00030157916800001810
the above-mentioned
Figure BDA00030157916800001811
Gathering the terminal Agg after the blind processingiThe aggregated data component of the mean value of the smart meters,
Figure BDA00030157916800001812
gathering the terminal Agg after the blind processingiThe converged smart meter counts variance data components,
Figure BDA00030157916800001813
and
Figure BDA00030157916800001814
gathering the terminal Agg after the blind processingiThe converged single-factor variance data components of the intelligent electric meter;
aggregation terminal AggiRandom selection
Figure BDA00030157916800001815
Computing
Figure BDA00030157916800001816
qi＝θi-ψiximodp，
Figure BDA00030157916800001817
qiIs AggiSignature value of wiAnd psiiIs AggiIs the current timestamp, and sends
Figure BDA00030157916800001818
Feeding the control center CC;
aggregation terminal AggiTransmission (ID _ SM)ij,ci,di) For a trusted third party TTP, the TTP calculates a blinding factor and a blinding-removing factor according to the ID of the intelligent electric energy meter actually participating in the convergence, and if the TTP actually participates in the intelligent electric energy meter SM with data aggregationijThe corresponding blinding factor is pii1,πi2,.......πin，
Figure BDA00030157916800001819
Then TTP calculates
Figure BDA00030157916800001820
Where j is 1,2,.. n, let pii0＝-πimodp, trusted third party TTP sending pii0To a control center CC wherei0Is a blindness-removing factor;
control center CC calculation
Figure BDA0003015791680000191
Authentication
Figure BDA0003015791680000192
Randomly selecting a set of fractions delta1,δ2,......δn,δn∈[1,2S]Detecting
Figure BDA0003015791680000193
Where s is a small integer with less computational cost, where w is verifiediThe process is as follows:
Figure BDA0003015791680000194
control center CC calculates C1,C2,C3,C4Obtaining the consumption data of the whole power consumer by solving the discrete logarithm of c and n by adopting Pollard's lambda algorithm, and outputting the result as
Figure BDA0003015791680000195
Wherein, C1The average value data component C of the intelligent electric meter gathered by the control center CC after the blinding processing2Calculating variance data component C for intelligent electric meter converged by control center CC after blind processing3And C4For the intelligent electric meter single-factor variance data component gathered by the control center CC after the blinding processing, the calculation process is as follows:
Figure BDA0003015791680000196
Figure BDA0003015791680000197
Figure BDA0003015791680000198
Figure BDA0003015791680000201
if the arbitration is needed, the trusted third party TTP may decrypt the ciphertext data aggregated by the control center CC, which is specifically as follows:
Figure BDA0003015791680000202
the data analysis module analyzes the power user data by using the control center CC, the data analysis comprises data analysis of different power price strategies and data analysis under the same power price strategy, and the data analysis specifically comprises the following steps:
make SBExpressing the sum of squares of different electricity price strategies, using SwThe square sum under the same electricity price strategy is represented, and the specific calculation is as follows:
Figure BDA0003015791680000203
Figure BDA0003015791680000204
the control center can then calculate the F-value of the F-test:
Figure BDA0003015791680000205
the F value of the F-test is mainly used for judging whether the electricity price strategy has a remarkable influence on the electricity consumption of the user.
On the premise of realizing privacy protection of the power consumers, the control center can realize analysis of the average value, the variance and the single-factor variance of the power consumption data of the power consumers, and effective arbitration is carried out when data disputes occur between the power consumers and a power company.
The intelligent electric energy meter control system has a fault-tolerant mechanism, and when individual intelligent electric energy meters have faults and data cannot be transmitted to the control center, data aggregation and processing can still be normally executed.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein. The scheme in the embodiment of the invention can be realized by adopting various computer languages, such as object-oriented programming language Java and transliterated scripting language JavaScript.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.

Claims (12)

1. A method adapted for intelligent electricity consumption data aggregation, the method comprising:
generating initialization parameters of the intelligent electric energy meter and the convergence terminal by a trusted third party, and controlling the intelligent electric energy meter and the convergence terminal to use the initialization parameters to complete initialization;
after the initialization of the intelligent electric energy meter and the convergence terminal is completed, registering the intelligent electric energy meter to the convergence terminal and a trusted third party, registering the convergence terminal to the control center and the trusted third party, and registering the control center to the trusted third party;
after the registration is completed, the intelligent electric energy meter sends user data to the convergence terminal, the convergence terminal acquires a user ID according to the user data and sends the user ID to the control center and the trusted third party, the trusted third party generates a blinding factor according to the user ID and transmits the blinding factor to the convergence terminal through the control center, and the convergence terminal aggregates the user data according to the blinding factor.
2. The method of claim 1, wherein the generating, by the trusted third party, the initialization parameters of the intelligent electric energy meter and the aggregation terminal comprises:
the TTP gives a security parameter k, two large prime numbers p and q are selected, the p and the q meet | p | ═ k and q | (p-1), G is a cyclic group with the order of p, G is a generator of G, and the order of the generator is P
Figure FDA0003015791670000011
For secure one-way hash functions, initialization parameters are determined as { p, q, g, H0,H1,H2G }, wherein,
Figure FDA0003015791670000012
is a cryptographic operation cycle group.
3. The method of claim 2, the initialization parameter being { p, q, g, H0,H1,H2G } is disclosed.
4. The method according to claim 1, wherein the registering the intelligent electric energy meter with the trusted third party and the aggregation terminal, the registering the aggregation terminal with the control center and the trusted third party, and the registering the control center with the trusted third party specifically include:
registering the intelligent electric energy meter to a trusted third party and a convergence terminal comprises the following steps:
intelligent electric energy meter SMijSending a registration request and an intelligent electric energy meter user ID _ SM to a trusted third party TTPij；
Trusted third party TTP random selection
Figure FDA0003015791670000013
According to xijDetermining
Figure FDA0003015791670000014
Wherein r isijIs a random number xijAnd YijFor intelligent electric energy meter SMijA public and private key pair;
calculating a blinding factor pi from the ID of the intelligent userijWhere i denotes the ith smart meter, j 1,2i1,πi2,.......πin，
Figure FDA0003015791670000021
Wherein n is the number of intelligent electric energy meters actually participating in aggregation;
trusted third party TTP transmissionParameter ID _ TTP, xij,Yij,rij,πijTo intelligent electric energy meter SMijIntelligent electric energy meter SMijTo rij,πiSecret storage;
to intelligent electric energy meter SMijTo a convergence terminal AggiAnd registering, including:
intelligent electric energy meter SMijSending registration request and ID _ SMijFor gathering terminal AggiRegistering;
the sink terminal will sink the terminal ID _ AggiSend to intelligent electric energy meter SMij。
The pair of convergence terminals AggiRegistering with a control center CC and a trusted third party TTP, comprising:
aggregation terminal AggiSending registration request and ID _ Agg to trusted third party TTPi；
Trusted third party TTP random selection
Figure FDA0003015791670000022
Computing
Figure FDA0003015791670000023
xi,YiFor a convergence terminal AggiPublic and private key pair of send (ID _ TTP, r)i,xi,Yi,Yij) For gathering terminal Aggi；
Aggregation terminal AggiSending registration request and ID _ AggiFeeding the control center CC;
the control center CC sends the ID _ CC to the aggregation terminal Aggi；
Registering the control center with a trusted third party, comprising:
the control center CC sends the ID _ CC to the TTP;
trusted third party TTP Transmission (ID _ TTP, Y)i) The registration is completed for the control center CC.
5. The method according to claim 1, wherein the aggregation terminal aggregates the user data according to the blinding factor, and specifically comprises:
intelligent electric energy meter SMijAcquiring power consumption data m of power consumerijSelecting a random number
Figure FDA0003015791670000024
Using secret stored random numbers rijCalculating the electricity consumption data ciphertext and the signature information, wherein the calculation process is as follows:
Figure FDA0003015791670000025
Figure FDA0003015791670000026
Figure FDA0003015791670000027
Figure FDA0003015791670000028
Figure FDA0003015791670000029
Figure FDA00030157916700000210
Figure FDA00030157916700000211
si＝ki-φi·xijmod p
after the calculation is finished, the intelligent electric energy meter SMijDelivery ID _ SMij,ci,
Figure FDA00030157916700000212
di,siT to the aggregation terminal Aggi；
Wherein d isiFor the user in the clear of electricity data, ciA data cipher text for the user, t is the current time stamp, p1 ijIs the average value data component p of the intelligent ammeter after the blinding processing2 ijCalculating variance data component p for the intelligent electric meter after the blind processing3 ijAnd p4 ijThe blind processing is carried out on the single-factor variance data component of the intelligent electric meter;
aggregation terminal AggiCalculating received ID _ SMij,ci,
Figure FDA0003015791670000031
di,siThe hash value of t, and calculating
Figure FDA0003015791670000032
Verifying smart meter signature siThe verification process is as follows:
Figure FDA0003015791670000033
Figure FDA0003015791670000034
where j ∈ {1, 2.. n }.
If the verification is passed, calculating the aggregated data as follows:
Figure FDA0003015791670000035
Figure FDA0003015791670000036
the above-mentioned
Figure FDA0003015791670000037
Gathering the terminal Agg after the blind processingiThe converged mean value data component of the intelligent electric meter;
Figure FDA0003015791670000038
gathering the terminal Agg after the blind processingiThe converged intelligent electric meter counts variance data components;
Figure FDA0003015791670000039
and
Figure FDA00030157916700000310
gathering the terminal Agg after the blind processingiThe converged single-factor variance data components of the intelligent electric meter;
aggregation terminal AggiRandom selection
Figure FDA00030157916700000311
Computing
Figure FDA00030157916700000312
qi＝θi-ψiximod p，
Figure FDA00030157916700000313
qiIs AggiSignature value of wiAnd psiiIs AggiIs the current timestamp, and sends
Figure FDA00030157916700000314
Feeding the control center CC;
aggregation terminal AggiTransmission (ID _ SM)ij,ci,di) To trusted third parties TTPThe TTP calculates a blinding factor and a blinding-free factor according to the ID of the intelligent electric energy meter actually participating in the convergence, and if the TTP actually participates in the intelligent electric energy meter SM with data aggregationijThe corresponding blinding factor is pii1,πi2,.......πin，
Figure FDA00030157916700000315
Then TTP calculates
Figure FDA00030157916700000316
Where j is 1,2,.. n, let pii0＝-πimod p, trusted third party TTP sending pii0To a control center CC wherei0Is a blindness-removing factor;
control center CC calculation
Figure FDA00030157916700000317
Authentication
Figure FDA00030157916700000318
Randomly selecting a set of fractions delta1,δ2,......δn,δn∈[1,2S]Detecting
Figure FDA00030157916700000319
Where s is a small integer with less computational cost, where w is verifiediThe process is as follows:
Figure FDA00030157916700000320
Figure FDA0003015791670000041
control center CC calculates C1,C2,C3,C4Obtaining the consumption data of the whole power consumer by solving the discrete logarithm of c and n by adopting Pollard's lambda algorithm, and outputting the resultThe fruit is
Figure FDA0003015791670000042
Wherein, C1The average value data component C of the intelligent electric meter gathered by the control center CC after the blinding processing2Calculating variance data component C for intelligent electric meter converged by control center CC after blind processing3And C4For the intelligent electric meter single-factor variance data component gathered by the control center CC after the blinding processing, the calculation process is as follows:
Figure FDA0003015791670000043
Figure FDA0003015791670000044
Figure FDA0003015791670000045
Figure FDA0003015791670000046
if the arbitration is needed, the trusted third party TTP may decrypt the ciphertext data aggregated by the control center CC, which is specifically as follows:
Figure FDA0003015791670000051
6. the method according to claim 1, wherein the control center CC analyzes the power consumer data, and the data analysis includes data analysis of different power rate policies and data analysis under the same power rate policy, and specifically includes:
make SBExpressing the sum of squares of different electricity price strategies, using SwThe square sum under the same electricity price strategy is represented, and the specific calculation is as follows:
Figure FDA0003015791670000052
Figure FDA0003015791670000053
the control center can then calculate the F-value of the F-test:
Figure FDA0003015791670000054
the F value of the F-test is mainly used for judging whether the electricity price strategy has a remarkable influence on the electricity consumption of the user.
7. A system adapted for intelligent electricity consumption data aggregation, the system comprising:
the initialization module controls a trusted third party to generate initialization parameters of the intelligent electric energy meter and the convergence terminal and controls the intelligent electric energy meter and the convergence terminal to use the initialization parameters to complete initialization;
the registration module registers the intelligent electric energy meter to the convergence terminal and a trusted third party, registers the convergence terminal to the control center and the trusted third party and registers the control center to the trusted third party after the intelligent electric energy meter and the convergence terminal are initialized;
and the aggregation module is used for sending user data to the aggregation terminal by the intelligent electric energy meter after the registration is finished, the aggregation terminal acquires a user ID according to the user data and sends the user ID to the control center and the credible third party, the credible third party generates a blinding factor according to the user ID and transmits the blinding factor to the aggregation terminal through the control center, and the aggregation terminal aggregates the user data according to the blinding factor.
8. The system of claim 7, wherein the generating of the initialization parameters of the intelligent electric energy meter and the aggregation terminal by the trusted third party comprises:
the TTP gives a security parameter k, two large prime numbers p and q are selected, the p and the q meet | p | ═ k and q | (p-1), G is a cyclic group with the order of p, G is a generator of G, and the order of the generator is P
Figure FDA0003015791670000061
For secure one-way hash functions, initialization parameters are determined as { p, q, g, H0,H1,H2G }, wherein,
Figure FDA0003015791670000062
is a cryptographic operation cycle group.
9. The system of claim 8, the initialization parameters being { p, q, g, H0,H1,H2G } is disclosed.
10. The system of claim 7, wherein the registering the smart electric energy meter with the trusted third party and the aggregation terminal, the registering the aggregation terminal with the control center and the trusted third party, and the registering the control center with the trusted third party specifically include:
registering the intelligent electric energy meter to a trusted third party and a convergence terminal comprises the following steps:
intelligent electric energy meter SMijSending a registration request and an intelligent electric energy meter user ID _ SM to a trusted third party TTPij；
Trusted third party TTP random selection
Figure FDA0003015791670000063
According to xijDetermining
Figure FDA0003015791670000064
Wherein r isijIs a random number xijAnd YijFor intelligent electric energy meter SMijA public and private key pair;
calculating a blinding factor pi from the ID of the intelligent userijWhere i denotes the ith smart meter, j 1,2i1,πi2,.......πin，
Figure FDA0003015791670000065
Wherein n is the number of intelligent electric energy meters actually participating in aggregation;
trusted third party TTP sends parameter ID _ TTP, xij,Yij,rij,πijTo intelligent electric energy meter SMijIntelligent electric energy meter SMijTo rij,πiSecret storage;
to intelligent electric energy meter SMijTo a convergence terminal AggiAnd registering, including:
intelligent electric energy meter SMijSending registration request and ID _ SMijFor gathering terminal AggiRegistering;
the sink terminal will sink the terminal ID _ AggiSend to intelligent electric energy meter SMij。
The pair of convergence terminals AggiRegistering with a control center CC and a trusted third party TTP, comprising:
aggregation terminal AggiSending registration request and ID _ Agg to trusted third party TTPi；
Trusted third party TTP random selection
Figure FDA0003015791670000066
Computing
Figure FDA0003015791670000067
xi,YiFor a convergence terminal AggiPublic and private key pair of send (ID _ TTP, r)i,xi,Yi,Yij) For gathering terminal Aggi；
Aggregation terminal AggiSending registration request and ID _ AggiFeeding the control center CC;
the control center CC sends the ID _ CC to the aggregation terminal Aggi；
Registering the control center with a trusted third party, comprising:
the control center CC sends the ID _ CC to the TTP;
trusted third party TTP Transmission (ID _ TTP, Y)i) The registration is completed for the control center CC.
11. The system according to claim 7, wherein the aggregation terminal aggregates the user data according to the blinding factor, and specifically includes:
intelligent electric energy meter SMijAcquiring power consumption data m of power consumerijSelecting a random number
Figure FDA0003015791670000071
Using secret stored random numbers rijCalculating the electricity consumption data ciphertext and the signature information, wherein the calculation process is as follows:
Figure FDA0003015791670000072
Figure FDA0003015791670000073
Figure FDA0003015791670000074
Figure FDA0003015791670000075
Figure FDA0003015791670000076
Figure FDA0003015791670000077
Figure FDA0003015791670000078
si＝ki-φi·xijmod p
after the calculation is finished, the intelligent electric energy meter SMijDelivery ID _ SMij,ci,
Figure FDA0003015791670000079
di,siT to the aggregation terminal Aggi；
Wherein d isiFor the user in the clear of electricity data, ciA data cipher text for the user, t is the current time stamp, p1 ijIs the average value data component p of the intelligent ammeter after the blinding processing2 ijCalculating variance data component p for the intelligent electric meter after the blind processing3 ijAnd p4 ijThe blind processing is carried out on the single-factor variance data component of the intelligent electric meter;
aggregation terminal AggiCalculating received ID _ SMij,ci,
Figure FDA00030157916700000710
di,siThe hash value of t, and calculating
Figure FDA00030157916700000711
Verifying smart meter signature siThe verification process is as follows:
Figure FDA00030157916700000712
Figure FDA00030157916700000713
where j ∈ {1, 2.. n }.
If the verification is passed, calculating the aggregated data as follows:
Figure FDA00030157916700000714
Figure FDA00030157916700000715
the above-mentioned
Figure FDA00030157916700000716
Gathering the terminal Agg after the blind processingiThe aggregated data component of the mean value of the smart meters,
Figure FDA00030157916700000717
gathering the terminal Agg after the blind processingiThe converged smart meter counts variance data components,
Figure FDA0003015791670000081
and
Figure FDA0003015791670000082
gathering the terminal Agg after the blind processingiThe converged single-factor variance data components of the intelligent electric meter;
aggregation terminal AggiRandom selection
Figure FDA0003015791670000083
Computing
Figure FDA0003015791670000084
qi＝θi-ψiximod p，
Figure FDA0003015791670000085
qiIs AggiSignature value of wiAnd psiiIs AggiIs the current timestamp, and sends
Figure FDA0003015791670000086
Feeding the control center CC;
aggregation terminal AggiTransmission (ID _ SM)ij,ci,di) For a trusted third party TTP, the TTP calculates a blinding factor and a blinding-removing factor according to the ID of the intelligent electric energy meter actually participating in the convergence, and if the TTP actually participates in the intelligent electric energy meter SM with data aggregationijThe corresponding blinding factor is pii1,πi2,.......πin，
Figure FDA0003015791670000087
Then TTP calculates
Figure FDA0003015791670000088
Where j is 1,2,.. n, let pii0＝-πimodp, trusted third party TTP sending pii0To a control center CC wherei0Is a blindness-removing factor;
control center CC calculation
Figure FDA0003015791670000089
Authentication
Figure FDA00030157916700000810
Randomly selecting a set of fractions delta1,δ2,......δn,δn∈[1,2S]Detecting
Figure FDA00030157916700000811
Where s is a small integer with less computational cost, where w is verifiediThe process is as follows:
Figure FDA00030157916700000812
Figure FDA00030157916700000813
control center CC calculates C1,C2,C3,C4Obtaining the consumption data of the whole power consumer by solving the discrete logarithm of c and n by adopting Pollard's lambda algorithm, and outputting the result as
Figure FDA00030157916700000814
Wherein, C1The average value data component C of the intelligent electric meter gathered by the control center CC after the blinding processing2Calculating variance data component C for intelligent electric meter converged by control center CC after blind processing3And C4For the intelligent electric meter single-factor variance data component gathered by the control center CC after the blinding processing, the calculation process is as follows:
Figure FDA00030157916700000815
Figure FDA0003015791670000091
Figure FDA0003015791670000092
Figure FDA0003015791670000093
if the arbitration is needed, the trusted third party TTP may decrypt the ciphertext data aggregated by the control center CC, which is specifically as follows:
Figure FDA0003015791670000094
12. the system according to claim 7, further comprising a data analysis module, wherein the data analysis module analyzes the power consumer data by using the control center CC, and the data analysis comprises data analysis of different power rate policies and data analysis under the same power rate policy, and specifically comprises:
make SBExpressing the sum of squares of different electricity price strategies, using SwThe square sum under the same electricity price strategy is represented, and the specific calculation is as follows:
Figure FDA0003015791670000095
Figure FDA0003015791670000096
the control center can then calculate the F-value of the F-test:
Figure FDA0003015791670000097
the F value of the F-test is mainly used for judging whether the electricity price strategy has a remarkable influence on the electricity consumption of the user.
CN202110389155.9A 2021-04-12 2021-04-12 Method and system suitable for intelligent power consumption data aggregation Pending CN113204741A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115033908A (en) * 2022-08-11 2022-09-09 西南石油大学 Cloud storage-based oil and gas exploration fine-grained dense-state data retrieval method

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115033908A (en) * 2022-08-11 2022-09-09 西南石油大学 Cloud storage-based oil and gas exploration fine-grained dense-state data retrieval method

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