CN109121134B - Privacy protection and integrity detection method suitable for multi-application data fusion of wireless sensor network - Google Patents
Privacy protection and integrity detection method suitable for multi-application data fusion of wireless sensor network Download PDFInfo
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Abstract
The invention discloses a privacy protection and integrity detection method suitable for multi-application data fusion of a wireless sensor network, and belongs to the technical field of information security and Internet of things application. According to the invention, the problems that the privacy data is stolen and tampered in the fusion and transmission processes are solved by carrying out privacy protection and integrity detection on the collected and fused multi-application data in the multi-application environment of the sensing network. The invention realizes the privacy protection of the fusion data by using a homomorphic Paillier encryption method, detects the integrity of the fusion data at a base station by using a homomorphic MAC method, and finally separates different application data from the fusion ciphertext by the base station through Chinese Remainder Theorem (CRT). Analysis shows that the method has higher safety and lower energy consumption while having error tolerance to node failure or data loss, and is simple to implement, low in cost and easy to popularize.
Description
Technical Field
The invention relates to a privacy protection and integrity detection method for resisting attack in the process of fusion and transmission of multiple application data of a sensor network, and belongs to the technical field of information security and Internet of things application.
Background
The wireless sensor network is an important component of a sensing layer of the Internet of things, and information sensing, acquisition and transmission can be carried out on a target by utilizing the sensor nodes, so that a data source is provided for application of the Internet of things. Data fusion is one of the important technologies for energy conservation of the wireless sensor network, but in the data acquisition and fusion process, the data privacy leakage and tampering are easy to occur, and many applications have high requirements on data security and privacy, such as smart power grids, smart homes, telemedicine and the like, so that privacy protection and integrity detection are performed on the acquired and fused data, the data is prevented from being stolen and tampered in the fusion and transmission process, a base station is ensured to acquire safe and reliable data, and finally an application layer of the internet of things makes a correct decision.
In actual application of the internet of things, application environments and sensing equipment types are diverse, and the existing data privacy protection and integrity detection technology is mainly designed in a data fusion scene of a single application environment and sensing nodes of the same type of a sensing network, so that data fusion of hybrid nodes based on multiple applications in the sensing network cannot be effectively supported. The recoverable data fusion scheme proposed by the existing latest document does not consider the data fusion of a multi-application environment and a hybrid node of a sensor network, the length of the transmitted fusion data is in direct proportion to the number of nodes, and the communication traffic and the calculation amount are large. Although the method such as CDAMA considers the fusion data privacy under the multi-application environment of the sensor network, the integrity protection of the fusion data is not considered, the communication overhead linearly increases along with the increase of application groups, and the communication traffic is large.
Aiming at the defects in the method, the invention provides a lightweight privacy protection and integrity detection method suitable for hybrid data fusion in a sensor network multi-application environment.
Disclosure of Invention
Technical problem to be solved by the invention
The invention provides a privacy protection and integrity detection method for lightweight multi-application data fusion and transmission, which ensures the privacy and integrity of hybrid data acquired by different types of sensor nodes in the fusion and transmission processes in a sensor network multi-application environment and can tolerate node errors and data loss.
Technical scheme
In order to solve the technical problems, the invention adopts the following technical scheme:
a privacy protection and integrity detection method suitable for multi-application data fusion of a wireless sensor network is characterized by comprising the following steps:
step S1, initializing the wireless sensor network system;
step S2, key distribution;
step S3, generating a node data homomorphic MAC;
step S4, node data encryption transmission;
step S5, fusing multi-application data;
step S6, the base station decrypts the data;
step S7, the base station splits the multi-application data;
in step S8, the base station analyzes the integrity of the data.
Step S1 includes the following steps:
step S11, the base station initializes the security parameters of the system by adopting a homomorphic Paillier encryption method, which comprises the following steps:
given a safety parameter k0K ', l, the base station randomly selects two security large prime numbers p and q, and calculates n ═ pq assuming that p ' and q ' are arbitrary prime numbers that make p ═ 2p ' +1 and q ═ 2q ' +1,
calculating the least common multiple λ of p-1 and q-1, expressed as λ lcm (p-1, q-1) ═ 2p 'q', and defining l (x) 1/n;
step S12, each sensing node sends the sensing data to the adjacent fusion node, and N sensing nodes are shared in the sensing networkr fusion nodes containing k application groupsEach application group(j is more than or equal to 1 and less than or equal to k) the transmitted data range is |0, Mj|,MjDefining maximum M ═ max { M ] of all data of the wireless sensor network for maximum data in jth application group1,M2,…MkWhere the binary bit length of M is denoted as | M | ═ lM;
Step S13, detecting the integrity of the fusion data by using a homomorphic information verification code method, and detecting the sensing data m of each node iiSplitting into d components (m)i1,mi2,…mid) And makeThe maximum value of each component is set as b, b<M, perception data MiAvailable finite fieldTo represent;
step S14, the base station uses Chinese remainder theorem to extract the fusion result of each application from the multi-application fusion data, the base station selects beta0,q1,q2,…qkA total of k +1 prime numbers, each prime number qiThe binary bit lengths of (i is more than or equal to 1 and less than or equal to k) are all k',
In the step of S15,
is provided with h1And h2For two hash functions, the base station selects a random number kiAs shared key of node i and fusion node, combined with key kiAnd a time parameter txCalculating kix=h1(ki||tx),
The base station distributes a random key { sk ] to each node1,sk2And (4) calculating homomorphic MAC by using two pseudo-random function generators G and F, and finally setting a system public key pms:
pms={n,qi:i=1,2…k,βj:j=0,1,2…k,h1,h2,L(x)}
step S2 includes the following steps:
step S21, the base station assigns the MAC key { sk ] through the secure channel1,sk2}, random key kiAnd public keypms to each node SiEach node SiRespectively generate random numbers riCarrying out random encryption;
step S22, the base station is distributed to the jth fusion node DAjIt and node SiShared random key kiAnd a secret key shared by the base station and the fusion nodeAnd a public key pms;
step S23, the MAC key { sk shared by the deployment nodes at the base station end1,sk2Key shared by base station and fusion nodePublic key pms and private key λ generated in step S11;
step S3 includes the following steps:
step S31, the node i collects the data miSplitting into d pieces with maximum length of lMComponent (m) ofi1,mi2,…mid) At time txInternal use random function generator G and key sk1Generating a random number vector u-G (sk)1);
Step S32, using the random function generator F and the key sk2Node ID IDiGenerating random number v with packet ID ridi=F(sk2,idi,rid);
Step S33, using the generated random number vector u and random number viAnd a plaintext miGenerating node data miIs expressed as TiThe generation method comprises the following steps:(symbol)representing vectors u and miIn a limited domainInner product of;
Step S34, the generated homomorphic MAC is connected with the original plaintext, and the connected plaintextComprises the following steps:
step S4 includes the following steps:
step S41, for belonging to application setSensing node SiN in step S11 and β in step S14 are used0And betaiThe hash function h in step S152Random number r in step S21iT in step S33iIn step S34And a time parameter txComputing the ciphertext cixThe method comprises the following steps:
step S42, using the key k in step S15ixAnd a hash function h1Computing the ciphertext cixMAC value of (d): macix=h1(cix||kix);
Step S43, node SiTransmission (c)ix,macix) To the fusion node.
Step S5 includes the following steps:
step S51, the fusion node calculates kix=h1(ki||tx) And then calculating MAC value MAC 'of received ciphertext'ix=h1(cix||kix) Comparing the received MAC value with the received MAC value, if the two MAC values are equal, receiving the ciphertext, otherwise refusing to receive;
step S52, fusing the nodes DAjReceivingAfter all the ciphertext data of the child nodes are obtained, accumulating and multiplying all the received ciphertext data, and accumulating and multiplying the result with n2Performing modular search to obtain the final fusion ciphertext CjxThen combined with that in step S22And a time parameter txComputing the fused ciphertext CjxMAC value MAC ofjxThe method comprises the following steps:
and step S53, after all the fusion nodes complete the data fusion operation, uploading the fusion result and the MAC value thereof to the base station.
Step S6 includes the following steps:
step S61, the base station at time txReceiving a fusion value (C) sent by a fusion node jjx,macjx) Then throughCalculating MAC value MAC of data'jxJudging whether the calculated MAC value is the same as the received MAC value, if so, receiving the fusion value, otherwise, discarding;
and step S62, decrypting the data by using the property of homomorphic Paillier encryption.
Step S62 includes the following steps:
step S621, the base station at time txCalculating fused ciphertexts C 'of k application environments by using private key lambda after receiving fused values uploaded by all r fused nodes'xThe method comprises the following steps:
in step S622, define the function L asThe base station is according to a fusion value C'xCalculating fusion results Y of k application environments:where n is calculated in step S11 and Q is calculated in step S14.
Step S7 includes the following steps:
step S71, the base station calculates each application group using the nature of Chinese Remainder Theorem (CRT)Fusion result of (2)jThe method comprises the following steps:
step S72, the base station extracts the fusion plaintext from the fusion resultAnd its fused homomorphic MAC valuesThe method comprises the following steps:
step S8 includes the following steps:
step S81, the base station uses (sk)1,sk2,rid,idi) Calculating homomorphic MAC parameters u 'and v':
in step S83, the base station compares the calculated homomorphic MAC value with the received MAC value, i.e., determines
If the two values are equal, the base station receives the fusion result, otherwise, the fusion result is discarded.
Advantageous effects
The invention has the significance that a privacy protection and integrity detection method is provided for a multi-application data fusion environment of a wireless sensor network, and the problems that privacy data is stolen and tampered in the fusion and transmission process are solved by carrying out privacy protection and integrity detection on collected and fused multi-application data in the multi-application environment of the sensor network.
The invention integrates the homomorphic Paillier encryption, homomorphic MAC, the unidirectionality of HASH functions, Chinese remainder theorem and other technologies and methods, simultaneously realizes the privacy protection and integrity detection of the fused data aiming at the multi-application data fusion environment of the sensor network for the first time, and has the advantages of high system safety and low energy consumption.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
FIG. 2 is a diagram illustrating a multi-application data fusion method according to the present invention.
Detailed Description
For a further understanding of the invention, reference should be made to the following detailed description taken in conjunction with the accompanying drawings.
As shown in fig. 1, the method adopted by the present invention is divided into 8 steps of system initialization, key distribution, node data homomorphic MAC generation, node data encryption transmission, multi-application data fusion, base station data decryption, base station multi-application data splitting, and data integrity analysis.
1. System initialization
System setting safety parameter k0K ', l, the base station randomly selects a security large prime number p, q so that p ═ 2p ' +1, q ═ 2q ' +1, | p | ═ q | ═ k0Then, n ═ pq, λ ═ lcm (p-1, q-1) ═ 2p 'q' is calculated, and l (x) ═ x-1)/n is defined.
According to the technical scheme, the specific parameters are set as follows:
parameter(s) | Value taking |
k0,p,q | |p|=|q|=k0 |
n,n2 | n=pq,|n|=2k0=1024,|n2|=4k0=2048 |
k',qi | |qi|=k'=60 |
β0 | β0=30 |
N,Nj,k,r | N=1000,Nj=100,k=10,r=4 |
lM,l,d | lM=|M|=16,|l|=160,|d|=3 |
Assuming that a sensor network needs to collect 3 environmental data of temperature, luminosity and smoke, the sensor network has 1000 nodesComprising 10 application groupsEach sensor node will send sensed data to its neighboring fusion node, each application groupThe data range of transmission is |0, Mj| define M ═ max { M1,M2,…M10}. To detect data integrity, sense data miSplitting into 8 components (m)i1,mi2,…mi8) So thatThe base station selects 11 prime numbers: beta is a0,q1,q2,…q10Each prime number qiAre 60 bits in length, i.e. | qiI is equal to or more than 1 and is equal to or less than 10, and the following calculation is carried out:
in order to ensure that the sensing data can be fused into a ciphertext, the parameters all satisfy the following conditions:
the method sets the data space to [0, M ═ 216]The number of sensors is N-210,|β030 to satisfy the condition N.M.ltoreq.beta0(ii) a Setting | qiK' 60 and d 3 to satisfy the condition N · ((d +1) · M · β)0+M)<qi(ii) a Passing condition log2k+k'(k+1)<| n | the number k of application groups to be set is 15 at maximum, where k is set to 10.
The method uses two hash functions h1And h2Generating a secret key and a random number, h1:{0,1}*→{0,1}lAndbase station selects random number kiK is calculated as a shared key of the node i and the fusion node thereofix=h1(ki||tx),kix∈{0,1}lAnd the MAC value is used for generating the MAC value of the perception data so as to avoid the illegal nodes from implementing error data injection attacks.
The base station distributes a secret key { sk ] to each node1,sk2Two pseudo-random function generatorsAnd the method is used for calculating homomorphic MAC (media access control) so as to carry out integrity detection on fused data, and finally, a system public key pms is set to { n, q ═ n, q }i:i=1,2…k,βj:j=0,1,2…k,h1,h2,L(x)}。
2. Key distribution
A sensing node end: base station distributes MAC key { sk through secure channel1,sk2}, random key kiAnd a public key pms to each node SiEach node SiRespectively generate random numbers riRandom encryption is performed.
A fusion node end: distribution of the fusion node DA by the base stationjAnd node SiShared random key kiBase station and fusion node DAjShared secret keyAnd a public key pms.
A base station end: deploying a MAC Key { sk shared with a node1,sk2}, secret key shared with the fusion nodePublic key pms and private key λ.
3. Generating node data homomorphic MAC
At each time period txEach node generates a node data homomorphic MAC by:
using a random function generator F, a secret key sk2Node ID IDiGenerating random number v with packet ID ridi=F(sk2,idi,rid)
Using the previously generated random number vector u, random number viAnd a plaintext miGenerating node data miIs expressed as TiThe generation method comprises the following steps:(symbol)representing vectors u and miIn a limited domainInner product of (d).
Connecting the generated homomorphic MAC with the original plaintext, and obtaining the connected plaintextComprises the following steps:
4. node data encrypted transmission
(1) If sensing nodeThen SiUsing a random number riAnd (beta)0,βj) The ciphertext is calculated as follows:
(2)Siusing a secret key kixCalculating macix=h1(cix||kix)。
(3)SiTransmission (c)ix,macix) To the fusion node.
5. Multi-application data fusion, as shown in figure 2,
(1) fusion node calculation kix=h1(ki||tx) And then calculating MAC value MAC 'of received ciphertext'ix=h1(cix||kix) Detects whether it is equal to the received MAC valueIf they are equal, the cipher text is received, otherwise the reception is refused.
(2) Fusion node DAjAfter receiving the sensing data of all the child nodes, performing the following fusion operation:
and after all the fusion nodes (r nodes in total) finish the data fusion operation, uploading the fusion result and the MAC value thereof to the base station.
6. Base station deciphered data
Base station in time window txReceiving a fusion node j (1)<j is less than or equal to r) transmitted fusion value (C)jx,macjx) Then, calculateDetermine if the calculated MAC value is the same as the received MAC value, i.e.If the two are the same, the fused value is received, otherwise, the fused value is discarded.
And (3) decrypting the data after detection is finished:
(1) base station in time window txCalculating C 'after receiving all fused values'x:
(2) And the base station calculates:
further, it is possible to obtain:
7. base station splitting multi-application data
8. data integrity analysis
Base station usage (sk)1,sk2,rid,idi) Calculating u 'and v'
The base station calculates a homomorphic MAC using u 'and v', compares it with the received MAC, i.e., determinesIf the equation is true, the base station receives the result, otherwise discards the fusion result.
The present invention and its embodiments have been described above schematically, without limitation, and what is shown in the drawings is only one of the embodiments of the present invention, and the actual structure is not limited thereto. Therefore, if the person skilled in the art receives the teaching, without departing from the spirit of the invention, the person skilled in the art shall not inventively design the similar structural modes and embodiments to the technical solution, but shall fall within the scope of the invention.
Claims (1)
1. A privacy protection and integrity detection method suitable for multi-application data fusion of a wireless sensor network is characterized by comprising the following steps:
step S1, initializing the wireless sensor network system, the method includes:
firstly, a base station initializes the security parameters of a system by adopting a homomorphic Paillier encryption method, and the method comprises the following steps:
given a safety parameter k0K ', l, the base station randomly selects two security large prime numbers p and q, and let p ' and q ' be arbitrary prime numbers that make p 2p ' +1 and q 2q ' +1 hold, calculates n pq, calculates the least common multiple λ of p-1 and q-1, expressed as λ lcm (p-1, q-1) ═ 2p ' q ', and defines l (x) -1)/n;
secondly, each sensing node sends sensing data to adjacent fusion nodes, and N sensing nodes are shared in the sensing networkr fusion nodes containing k application groupsEach application groupThe data range of transmission is |0, Mj|,MjDefining maximum M ═ max { M ] of all data of the wireless sensor network for maximum data in jth application group1,M2,…MkWhere the binary bit length of M is denoted as | M | ═ lM;
Thirdly, detecting the integrity of the fusion data by using a homomorphic information verification code method, and enabling the sensing data m of each node iiSplitting into d components (m)i1,mi2,…mid) And makeThe maximum value of each component is set as b, b<M, perception data MiAvailable finite fieldTo represent;
fourthly, the base station applies Chinese remainder theorem to respectively extract the fusion result of each application from the multi-application fusion data, and selects beta0,q1,q2,…qkA total of k +1 prime numbers, each prime number qi(1. ltoreq. i. ltoreq.k)The bit lengths are all k',
The fifth step is to set h1And h2For two hash functions, the base station selects a random number kiAs shared key of node i and fusion node, combined with key kiAnd a time parameter txCalculating kix=h1(ki||tx) The base station distributes a random key { sk ] to each node1,sk2And (4) calculating homomorphic MAC by using two pseudo-random function generators G and F, and finally setting a system public key pms: pms ═ n, qi:i=1,2…k,βj:j=0,1,2…k,h1,h2,L(x)};
Step S2, key distribution, the method is:
first, the base station assigns the MAC key { sk in step S1 through a secure channel1,sk2}, random key kiAnd a public key pms to each node SiEach node SiRespectively generate random numbers riCarrying out random encryption;
secondly, the base station distributes to the jth fusion node DAjIt and node SiShared random key kiAnd a secret key shared by the base station and the fusion nodeAnd a public key pms;
thirdly, the base station terminal deploys the MAC key { sk shared by the nodes1,sk2Key shared by base station and fusion nodePublic key pms and private key λ generated in the first step of step S1;
step S3, generating a node data homomorphic MAC, the method includes:
in the first step, node i collects data miSplitting into d pieces with maximum length of lMComponent (m) ofi1,mi2,…mid) At time txInternal use random function generator G and key sk1Generating a random number vector u-G (sk)1);
Second, using random function generator F, key sk2Node ID IDiGenerating random number v with packet ID ridi=F(sk2,idi,rid);
Thirdly, using the random number vector u and the random number v generated previouslyiAnd a plaintext miGenerating node data miIs expressed as TiThe generation method comprises the following steps:(symbol)representing vectors u and miIn a limited domainInner product of (d);
fourthly, the generated homomorphic MAC is connected with the original plaintext, and the connected plaintextIs composed of
Step S4, the node data is encrypted and transmitted, the method includes:
first, for belonging to the application setSensing node SiUsing n in the first step of step S1 and β in the fourth step of step S10And betaiStep S1 fifthHash function h in step2Random number r in the first step in step S2iT in the third step in step S3iIn the fourth step in step S3And a time parameter txComputing the ciphertext cixThe method comprises the following steps:
second, using the key k in the fifth step of step S1ixAnd a hash function h1Computing the ciphertext cixMAC value of (d): macix=h1(cix||kix);
Third step, node SiTransmission (c)ix,macix) Giving the fusion node;
step S5, fusing multi-application data, the method is:
first, the fusion node calculates kix=h1(ki||tx) And then calculating MAC value MAC 'of received ciphertext'ix=h1(cix||kix) Comparing the received MAC value with the received MAC value, if the two MAC values are equal, receiving the ciphertext, otherwise refusing to receive;
second, the nodes DA are fusedjAfter receiving the ciphertext data of all child nodes, accumulating and multiplying all the received ciphertext data, and accumulating and multiplying the result with n2Performing modular search to obtain the final fusion ciphertext CjxThen combined with that in the second step of step S2And a time parameter txComputing the fused ciphertext CjxMAC value MAC ofjxThe method comprises the following steps:
thirdly, after all the fusion nodes complete the data fusion operation, uploading the fusion result and the MAC value thereof to the base station;
step S6, the base station decrypts the data, the method is:
first, the base station at time txReceiving a fusion value (C) sent by a fusion node jjx,macjx) Then throughCalculating MAC value MAC of data'jxJudging whether the calculated MAC value is the same as the received MAC value, if so, receiving the fusion value, otherwise, discarding;
secondly, decrypting the data by using the property of homomorphic Paillier encryption, wherein the method comprises the following steps:
first, the base station is at time txCalculating fused ciphertexts C 'of k application environments by using private key lambda after receiving fused values uploaded by all r fused nodes'xThe method comprises the following steps:
then, define the function L asThe base station is according to a fusion value C'xCalculating fusion results Y of k application environments:wherein n is calculated in the first step of step S1, and Q is calculated in the fourth step of step S1;
step S7, the base station splits the multi-application data, the method includes:
in the first step, the base station calculates each application group using the properties of the Chinese Remainder Theorem (CRT)Fusion result of (2)jThe method comprises the following steps:
secondly, the base station extracts a fusion plaintext from the fusion resultAnd its fused homomorphic MAC valuesThe method comprises the following steps:
step S8, the base station analyzes the data integrity, the method includes:
first, base station uses (sk)1,sk2,rid,idi) Calculating homomorphic MAC parameters u 'and v':
thirdly, the base station compares the calculated homomorphic MAC value with the received MAC value, namely, the judgment is carried out
If the two values are equal, the base station receives the fusion result, otherwise, the fusion result is discarded.
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