CN110545282A - Data acquisition and analysis system based on wireless body area network and low-energy-consumption data fusion privacy protection algorithm - Google Patents
Data acquisition and analysis system based on wireless body area network and low-energy-consumption data fusion privacy protection algorithm Download PDFInfo
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- CN110545282A CN110545282A CN201910850683.2A CN201910850683A CN110545282A CN 110545282 A CN110545282 A CN 110545282A CN 201910850683 A CN201910850683 A CN 201910850683A CN 110545282 A CN110545282 A CN 110545282A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/04—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks
- H04L63/0428—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the data content is protected, e.g. by encrypting or encapsulating the payload
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
- H04L9/08—Key distribution or management, e.g. generation, sharing or updating, of cryptographic keys or passwords
- H04L9/0816—Key establishment, i.e. cryptographic processes or cryptographic protocols whereby a shared secret becomes available to two or more parties, for subsequent use
- H04L9/0819—Key transport or distribution, i.e. key establishment techniques where one party creates or otherwise obtains a secret value, and securely transfers it to the other(s)
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
- H04L9/08—Key distribution or management, e.g. generation, sharing or updating, of cryptographic keys or passwords
- H04L9/0861—Generation of secret information including derivation or calculation of cryptographic keys or passwords
- H04L9/0863—Generation of secret information including derivation or calculation of cryptographic keys or passwords involving passwords or one-time passwords
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
- H04W12/03—Protecting confidentiality, e.g. by encryption
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Abstract
the invention discloses a data acquisition and analysis system based on a wireless body area network and a low-energy-consumption data fusion privacy protection algorithm. The invention uses a data fusion model with a tree structure, provides a data fusion function based on unequal long-time intervals on the basis of a data fusion function structure expression, and adopts a random key distribution strategy for data encryption and decryption; the method has the characteristics of small data traffic, high privacy protection, high accuracy and low energy consumption.
Description
Technical Field
The invention belongs to the technical field of network security, and particularly relates to a data acquisition and analysis system based on a wireless body area network and a low-energy-consumption data fusion privacy protection algorithm.
background
with the continuous progress of wireless communication technology, internet of things and low-energy consumption sensing equipment development technology, Wireless Sensor Networks (WSNs) (wireless Sensor networks) are developed greatly and are widely applied to the fields of health and medical care, environmental monitoring, national defense construction and the like. A wireless Body area network wbsn (wireless Body Sensor network) is an important branch of the WSN in the field of health care, and has attracted attention in many fields including remote medical care, remote monitoring, and community aging. WBSN through settle different kinds of low energy consumption sensor node such as with implanted, wearable or nearly style in the human body or the body surface, collects the human health sign data of multiple modality, uploads data acquisition father node step by step through wireless communication network, judges to the human health status based on data mining and the supplementary medical personnel of intelligent analysis technique.
Monitoring data in the WBSN are uploaded and fused step by step, the data contain a large amount of privacy information related to personal health conditions, once some nodes in the sensing network are invaded maliciously, the sensitive privacy information is possibly monitored, the monitoring data fusion is abnormal, a monitoring data security disaster which is difficult to estimate is caused, and the trust of a user on remote medical care and health monitoring based on the wireless sensor network technology is influenced. In order to improve the safety of data fusion in a wireless sensor network, a low-energy-consumption data fusion privacy protection algorithm based on a wireless body area network is provided, and the privacy protection of personal monitoring data is improved on the premise of reducing the data redundancy of sensor nodes in a WBSN (wireless data network) and the communication traffic of a sensing network.
Disclosure of Invention
the invention aims to provide a data acquisition and analysis system based on a wireless body area network and a low-energy-consumption data fusion privacy protection algorithm, so as to solve the problems in the background technology.
in order to achieve the above object, the present invention provides a data acquisition and analysis system based on a wireless body area network, which includes a data acquisition node electrically connected to a data monitoring device and configured to receive data from the monitoring device, a data transmission node electrically connected to the data acquisition node and configured to perform noise filtering and first-level data fusion calculation, and a data analysis node in signal connection with the data transmission node and configured to perform final data fusion analysis calculation.
In the scheme, the monitoring data of the data monitoring equipment is received through the data acquisition node and is periodically transmitted to the upper-level data transmission node through the wireless communication network; the data transmission node collects multi-modal monitoring data, carries out noise data filtering, carries out data fusion calculation of a first level according to the data type, and uploads the calculation result to the data analysis node; and the data analysis node acquires the primarily processed monitoring data information and performs final data fusion calculation.
The invention also provides a low-energy-consumption data fusion privacy protection algorithm based on the wireless body area network, which is realized by adopting a data acquisition and analysis system based on the wireless body area network, and the algorithm specifically comprises the following steps:
S1, abstracting the wireless body area network into a tree network with a three-layer structure;
S2, reducing data flux and energy consumption by using a data fusion algorithm of repeated reduction factors;
And S3, improving data privacy protection by using fragment transmission and a random key distribution mechanism.
in S1, the data fusion model of the tree structure is a typical wireless body area network WBSN generally including 3 types of nodes: the leaf nodes are composed of data received by the data acquisition nodes; the data transmission node is used for collecting data of the multi-mode multi-nodes and performing a data fusion calculation function; QS (query Server) node, and data analysis node is responsible for final fusion analysis of data. The nodes of 3 types form a tree structure, wherein the QS node is used as a root node to obtain a data fusion result and provide a basis for further data analysis, the fusion node is responsible for receiving data from leaf nodes, performing fusion calculation and then transmitting the data to the root node, the leaf nodes collect data of multiple modes and multiple nodes and upload the data to corresponding nodes, and the data fusion process based on the tree structure is one-way transmission. .
As a preferred embodiment, the data fusion algorithm of the repetitive reduction factor in S2 includes the following steps:
S201, judging whether the periodic repeatability exists or not according to the acquired monitoring data;
S202, reduction compression processing is carried out on a large amount of existing normal data with periodic repeatability, data communication quantity and energy consumption of a wireless sensor network are reduced, and data fusion efficiency is improved.
In the scheme, the algorithm of adding the repeated reduction factor can greatly reduce communication load caused by periodic repeated monitoring data transmission according to whether the acquired data has periodic repeatability, and each calculation is not needed. The monitoring data are considered to be basically normal in most of time when data fragmentation and transmission of the WBSN are carried out, abnormal signals are more valuable to health analysis, compression processing is carried out on a large number of existing normal data with periodic repeatability, occasional abnormal data are collected in a key mode, data communication quantity of a wireless sensor network is reduced, and data fusion efficiency is improved.
as a preferred embodiment, the fragment transmission and random key distribution mechanism described in S3 includes the following steps:
S301, dividing data collected by each node into j pieces;
S302, transmitting j-1 pieces of data to adjacent nodes, so that an eavesdropper can decrypt complete information transmitted by the node only when acquiring all j-1 outgoing links and all incoming links;
wherein, the probability that the data acquired by each borrowing point is intercepted and decrypted is as follows:
in the above scheme, the data encryption and decryption adopts a random key distribution strategy: generating a key pool containing K keys, and randomly selecting K keys (K < K) from the key pool; nodes in the WBSN send messages to each other to determine which nodes are distributed to obtain the same key, and a data transmission link can be established between the nodes which obtain the same key; if the parent-child nodes in the tree structure are not distributed to obtain the same key, a transmission link can be established in a hop-by-hop mode. If the same key distribution scheme is adopted by the listener, the probability that the data in the WBSN is intercepted is p ═ K/K. The number of keys in the key pool is set to be relatively large, so that the probability of data interception in the wireless sensor network is reduced.
Compared with the prior art, the invention has the beneficial effects that:
the invention uses a data fusion model with a tree structure, provides a data fusion function based on unequal long-time intervals on the basis of a data fusion function structure expression, and adopts a random key distribution strategy for data encryption and decryption; the algorithm is a low-energy-consumption data fusion privacy protection algorithm with small data traffic, high privacy protection and high accuracy.
Drawings
FIG. 1 is a diagram of a wireless body area network based data acquisition and analysis system of the present invention;
FIG. 2 is a flow chart of a low-energy data fusion privacy protection algorithm based on a wireless body area network of the present invention;
FIG. 3 is a diagram of a tree-based data fusion model according to the present invention;
FIG. 4 is a flow chart of a data fusion algorithm for a iterative reduction factor of the present invention.
Detailed Description
The present invention will be further described with reference to the following examples.
The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention. The conditions in the embodiments can be further adjusted according to specific conditions, and simple modifications of the method of the present invention based on the concept of the present invention are within the scope of the claimed invention.
The invention provides a data acquisition and analysis system based on a wireless body area network, and please refer to fig. 1, the system comprises a monitoring data acquisition node which is electrically connected with a data monitoring device and used for receiving the data monitoring device, a data transmission node which is electrically connected with the data acquisition node and used for carrying out noise filtering and first-level data fusion calculation, and a data analysis node which is in signal connection with the data transmission node and used for final data fusion analysis calculation.
The invention also provides a low-energy-consumption data fusion privacy protection algorithm based on the wireless body area network, which is realized by adopting a data acquisition and analysis system based on the wireless body area network, please refer to fig. 2-4, and the algorithm specifically comprises the following steps:
s1, abstracting the wireless body area network into a tree network with a three-layer structure;
Referring to fig. 3, after receiving multi-modal monitoring data, a fusion node in the data fusion model based on a tree structure performs filtering on garbage data such as noise and periodically repeating data compression, and performs data fusion calculation of a first level through a data fusion function based on unequal long time intervals, where a function expression is:
in the formula, di (Δ ti) (i ═ 1,2, …, n) represents data collected by node i in the Δ ti time interval, and represents the least common time period of all node data collection time intervals.
For the monitoring data with obvious periodicity, the time interval can be set to be relatively longer, and some repeated sign data can be removed, so that the data communication volume can be reduced, and the data fusion efficiency can be improved.
each node divides the acquired data into j pieces, wherein j-1 pieces are sent to j-1 nodes randomly selected from adjacent node sets; the node decrypts the fragment data by using the shared key after receiving the fragment data; and then performing data fusion by using an algorithm. The data acquisition and transmission time interval is divided into time slices with different lengths according to different modal data, and the periodic repetitive data in the time slices are reduced, so that the data communication traffic is limited to reduce the energy consumption of the wireless sensor network. According to the fact that whether the acquired data have periodic repeatability or not, the nodes can be divided into a periodic node set Vr and an aperiodic node set Vu.
S2, reducing data flux and energy consumption by using a data fusion algorithm of repeated reduction factors;
Referring to fig. 2 and 4, data from the collection node is input first, and theoretically, the data comes from the data monitoring device, but for safety, it is necessary to determine whether the data comes from the data monitoring device; if the data come from the data monitoring equipment, a node set is randomly allocated, and then whether the data belong to the periodic node set Vr or not is judged by calculating a node data transmission time interval parameter delta ti; then judging whether the frequency domain characteristics of the data in 10 periods are equal, if so, directly removing repeated data, and if not, setting the time interval as the average time interval; if the data belongs to the aperiodic node set Vu, j-1 pieces of compressed data are sent to the nodes, the nodes decrypt the data by using the shared secret key; and finally obtaining a fusion result.
And S3, improving data privacy protection by using fragment transmission and a random key distribution mechanism.
Referring to fig. 2 and 4, the fragmentation transmission and random key distribution mechanism adopts a data fragmentation transmission and encryption decryption mechanism, data collected by each node is divided into j pieces and j-1 pieces of data are sent to adjacent nodes, and complete information sent by the node at this time can be decrypted only when an eavesdropper acquires all j-1 outgoing links and all incoming links;
wherein, the probability that the data acquired by the node is intercepted and decrypted is as follows:
In the formula, the probability of data interception due to the key assignment policy is expressed, D represents the maximum value of the degree of entry of all nodes in the network, and Pd ═ λ represents the probability that the degree of entry of a node is λ.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (4)
1. a data acquisition and analysis system based on a wireless body area network is characterized by comprising a monitoring data acquisition node, a data transmission node and a data analysis node, wherein the monitoring data acquisition node is electrically connected with a data monitoring device and used for receiving the data monitoring device, the data transmission node is electrically connected with the data acquisition node and used for carrying out noise filtering and first-level data fusion calculation, and the data analysis node is in signal connection with the data transmission node and used for carrying out final data fusion analysis calculation.
2. a low-energy consumption data fusion privacy protection algorithm based on a wireless body area network is realized by adopting the data acquisition and analysis system based on the wireless body area network as claimed in claim 1, and is characterized by specifically comprising the following steps:
S1, abstracting the wireless body area network into a tree network with a three-layer structure;
s2, reducing data flux and energy consumption by using a data fusion algorithm of repeated reduction factors;
and S3, improving data privacy protection by using fragment transmission and a random key distribution mechanism.
3. the wireless body area network-based low-energy-consumption data fusion privacy protection algorithm according to claim 2, wherein the data fusion algorithm with repeated reduction factors in S2 comprises the following steps:
S201, judging whether the periodic repeatability exists according to the acquired monitoring data;
S202, reduction compression processing is carried out on a large amount of existing normal data with periodic repeatability, data communication quantity and energy consumption of a wireless sensor network are reduced, and data fusion efficiency is improved.
4. the wireless body area network-based low-energy-consumption data fusion privacy protection algorithm according to claim 2, wherein the fragmentation transmission and random key distribution mechanism in S3 comprises the following steps:
s301, dividing data collected by each node into j pieces;
s302, transmitting j-1 pieces of data to adjacent nodes, so that an eavesdropper can decrypt complete information transmitted by the node only when acquiring all j-1 outgoing links and all incoming links;
Wherein, the probability that the data acquired by each borrowing point is intercepted and decrypted is as follows:
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