CN114866222A - Ciphertext data statistical analysis system and method supporting privacy protection - Google Patents
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Abstract
The scheme is based on the adoption of a homomorphic encryption algorithm and a digital signature algorithm, realizes the statistical analysis and energy supply of ciphertext data, supports the functions of statistical analysis function calculation and abnormal value detection statistical analysis in a ciphertext state, and provides data analysis service and system condition early warning for a supervision institution; the scheme reduces the calculation load of a single node by adopting a multilayer aggregation structure, namely, the edge node and the cloud node share the calculation task of statistics; the edge nodes and the cloud nodes perform homomorphic statistical operation in a ciphertext state, so that user data and statistical data are prevented from being stolen by an adversary, and malicious behaviors in a system are resisted; meanwhile, the scheme uses a secret sharing technology to ensure that the total number of the sensor devices cannot be obtained when the edge devices and the control center can calculate the average value.
Description
Technical Field
The disclosure belongs to the technical field of network information security, and particularly relates to a ciphertext data statistical analysis system and method supporting privacy protection.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
In recent years, the internet of things and the wireless sensor network are widely applied to application scenes such as smart agriculture, industrial manufacturing, smart transportation, smart home, automatic driving of automobiles, medical care and the like. Sensor equipment and terminals in the Internet of things are responsible for sensing real-time data and transmitting the sensed data to a control center for data analysis and intelligent control. Meanwhile, a supervision organization (such as scenes of security, environmental protection, electric power, agriculture, factories and the like) needs to perform real-time statistical analysis on abnormal conditions of terminal equipment and data through the internet of things to make corresponding management measures or emergency response.
In various internet of things and wireless sensor networks, edge computing equipment is deployed near a terminal and a sensor equipment area, and part of data statistics and computing tasks of the terminal and the sensor equipment can be distributed to the edge equipment, so that computing enhancement services are provided for the terminal and the sensor with limited resources. And the edge computing devices of the multiple areas transmit the aggregated data to the cloud control center for further statistical computation.
However, the inventors have found that the data aggregation, transmission and statistical analysis process may encounter some potential attacks and security risks such as illegal eavesdropping, malicious tampering, counterfeit and forgery. Because the internet of things terminal and the wireless sensor are usually deployed in an unattended environment, data may be captured or forged in the transmission process; an adversary can invade the edge gateway to steal the private data of the user; when the statistical analysis data is transmitted in a wireless local area network or the internet, an adversary may eavesdrop. Meanwhile, the cloud control center serves as a third-party service provider, and if the cloud control center knows the statistical data, corresponding business secrets can be deduced and utilized; the monitoring authority only has the right to acquire statistical data in the authority range, and the quantity of the sensors and the represented industrial scale need to be kept secret; in order to realize the security guarantee of data statistical analysis aiming at the security risks, the traditional encryption method cannot effectively solve the problem of ciphertext data statistical analysis of edge calculation enhancement.
Disclosure of Invention
In order to solve the above problems, the present disclosure provides a cryptograph data statistical analysis system and method supporting privacy protection, in the scheme, a plurality of parties including an edge aggregator, a cloud control center, a supervision agency participate in calculation, the number of sensors of the internet of things is not revealed to the cloud control center and the supervision agency, confidentiality and integrity of data are ensured by using an addition homomorphic encryption algorithm and a digital signature algorithm, and the number of sensors is blinded by using linear transformation, so that confidentiality of equipment scale is realized; the scheme supports the functions of statistical analysis function calculation and abnormal value detection statistical analysis in a ciphertext state, and provides data analysis service and system condition early warning for a supervision organization.
According to a first aspect of the embodiments of the present disclosure, there is provided a ciphertext data statistical analysis system supporting privacy protection, including:
a trusted authority for generating independent public and private keys for the sensor device, the edge aggregator, the control center, and the regulatory body;
the sensor equipment is used for performing basic preprocessing on the acquired data, encrypting the data through a homomorphic encryption algorithm, generating a digital signature of the sensor equipment by using a digital signature algorithm based on the ID of the sensor equipment to form a ciphertext data report, and sending the ciphertext data report to the edge aggregator;
the edge aggregator is used for receiving the ciphertext data report of the sensor equipment in the preset area and performing preset operation processing on encrypted data in the ciphertext data report; meanwhile, the equipment number of the current area is subjected to blinding processing based on a blinding number from a supervision mechanism, a ciphertext data report is formed based on the data subjected to the preset operation processing and the digital signature of the edge aggregator, and the ciphertext data report is sent to a control center;
the control center is used for receiving the ciphertext data report from the edge aggregator and carrying out preset operation processing on the encrypted data in the ciphertext data report; based on the processed encrypted data and the digital signature of the control center, a ciphertext data report is formed and sent to a supervision organization;
and the monitoring mechanism is used for receiving the ciphertext data report from the control center, carrying out decryption processing and de-blinding processing on the ciphertext data and obtaining a statistical analysis result.
Further, after receiving the ciphertext data report of the sensor device in the preset area, the edge aggregator specifically executes the following operations: verifying the validity of the signature of the ciphertext data report; for the ciphertext data report passing the verification, performing preset operation on the ciphertext data; and generating a digital signature of the edge aggregator based on the edge aggregator ID; forming a ciphertext data report based on the data subjected to the aggregation operation and the digital signature, and sending the ciphertext data report to a control center;
further, the trusted authority is further configured to: and generating an encryption public key and a decryption private key of a homomorphic encryption algorithm and a signature public key and a signature private key of a digital signature algorithm according to preset safety parameters, and distributing the keys based on preset rules.
Further, the blinding processing is performed on the number of devices in the current area based on the blinding number from the monitoring authority, specifically, the following formula is adopted for processing:
m′ k ＝αm k +β k
wherein m' k Number of devices after blinding, m k Alpha and beta are actual number of devices k Together forming the pair of blinded numbers.
Further, the distribution of the key specifically includes: the trusted authorization center encrypts the public key pk through a preset security channel AHE And the signature private key sk DS,i Distributing to sensor equipment; will encrypt the public key pk AHE The signature private key sk DS,EA And a signature public key pk DS,i Sending the data to an edge aggregator; will encrypt the public key pk AHE Signed private key sk DS,CC And a signature public key pk DS,EA Sending the data to a control center; will decrypt the private key sk AHE (p, q, λ) and a public signature verification key pk DS,CC And sending the information to a supervision agency.
Further, the generation of the digital signature specifically includes: and generating a digital signature corresponding to the equipment through a digital signature algorithm based on the equipment ID identification.
Further, the homomorphic encryption algorithm includes, but is not limited to, Paillier homomorphic encryption algorithm, and the digital signature algorithm includes, but is not limited to, ECDSA digital signature algorithm.
Further, the preset operation comprises a summation operation, an arithmetic mean, a quadratic mean, a weighted mean, a variance, a data anomaly number and a data anomaly ratio.
Further, the basic preprocessing includes representing the collected data as a data vector, a squared sensing data vector, a weighted sensing data vector, and determining whether the data is abnormal.
According to a second aspect of the embodiments of the present disclosure, there is provided a ciphertext data statistical analysis method supporting privacy protection, based on the above ciphertext data statistical analysis system supporting privacy protection, including:
the trusted authorization center generates independent public keys and private keys for the sensor equipment, the edge aggregator, the control center and the monitoring authority;
the sensor equipment performs basic preprocessing on the acquired data, encrypts the data through a homomorphic encryption algorithm, generates a digital signature of the sensor equipment by using a digital signature algorithm based on the ID of the sensor equipment to form a ciphertext data report, and transmits the ciphertext data report to an edge aggregator;
the edge aggregator receives a ciphertext data report of the sensor equipment in a preset area, and performs preset operation processing on encrypted data in the ciphertext data report; meanwhile, the equipment number of the current area is subjected to blinding processing based on a blinding number from a supervision mechanism, a ciphertext data report is formed based on the data subjected to preset operation processing and the digital signature of the edge aggregator, and the ciphertext data report is sent to a control center;
the control center receives the ciphertext data report from the edge aggregator and performs preset operation processing on the encrypted data in the ciphertext data report; based on the processed encrypted data and the digital signature of the control center, a ciphertext data report is formed and sent to a supervision organization;
and the supervision mechanism receives the ciphertext data report from the control center, decrypts and de-blinds the ciphertext data, and obtains a statistical analysis result.
Compared with the prior art, the beneficial effect of this disclosure is:
(1) the scheme supports the functions of statistical analysis function calculation and abnormal numerical value detection statistical analysis in a ciphertext state, and provides data analysis service and system condition early warning for a supervision organization.
(2) The scheme disclosed by the invention adopts a multilayer aggregation structure, namely the edge nodes and the cloud nodes share the statistical computing task, so that the computing load at a single node is reduced. Meanwhile, homomorphic statistical operation is carried out on the edge nodes and the cloud nodes in a ciphertext state, user data and statistical data are prevented from being stolen by an adversary, and malicious behaviors in the system are resisted.
(3) The scheme of the disclosure uses a secret sharing technology to ensure that the total number of the sensor devices cannot be known when the edge devices and the control center can calculate the average value. The control center executes statistical function calculation in a ciphertext state by using the encrypted ciphertext and the blinded total number of the equipment; and after receiving the ciphertext, the monitoring mechanism processes the decrypted average value by using an improved extended Euclidean algorithm and calculates a correct average value. The method avoids the control center from explicitly calculating 'numerical value and/or total number' based on plaintext, thereby realizing privacy protection of equipment scale.
Advantages of additional aspects of the disclosure will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the disclosure.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure and are not to limit the disclosure.
Fig. 1 is a data transmission flow diagram of a ciphertext data statistics analysis system supporting privacy protection according to an embodiment of the present disclosure;
FIG. 2 is a flowchart illustrating the generation and distribution of a trusted authority TA key as a whole in an embodiment of the present disclosure;
FIG. 3 is a flow chart illustrating the sensor cluster transmitting a ciphertext data report to the edge aggregator EA, in accordance with an embodiment of the present disclosure;
fig. 4 is a flowchart illustrating the edge aggregator EA transmitting a ciphertext statistical analysis report to the control center CC according to an embodiment of the disclosure;
fig. 5 is a flowchart illustrating the transmission of a ciphertext statistical analysis report to a supervisory authority SV by the control center CC according to an embodiment of the present disclosure.
Detailed Description
The present disclosure is further described with reference to the following drawings and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present disclosure. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict.
The first embodiment is as follows:
the embodiment aims to provide a ciphertext data statistical analysis system supporting privacy protection.
A ciphertext data statistics analysis system that supports privacy protection, comprising:
a trusted authority for generating independent public and private keys for the sensor device, the edge aggregator, the control center, and the regulatory body;
the sensor equipment is used for performing basic preprocessing on the acquired data, encrypting the data through a homomorphic encryption algorithm, generating a digital signature of the sensor equipment by using a digital signature algorithm based on the ID of the sensor equipment to form a ciphertext data report, and sending the ciphertext data report to the edge aggregator;
the edge aggregator is used for receiving the ciphertext data report of the sensor equipment in the preset area and performing preset operation processing on encrypted data in the ciphertext data report; meanwhile, the equipment number of the current area is subjected to blinding processing based on a blinding number from a supervision mechanism, a ciphertext data report is formed based on the data subjected to the preset operation processing and the digital signature of the edge aggregator, and the ciphertext data report is sent to a control center;
the control center is used for receiving the ciphertext data report from the edge aggregator and carrying out preset operation processing on the encrypted data in the ciphertext data report; based on the processed encrypted data and the digital signature of the control center, a ciphertext data report is formed and sent to a supervision organization;
and the monitoring mechanism is used for receiving the ciphertext data report from the control center, carrying out decryption processing and de-blinding processing on the ciphertext data and obtaining a statistical analysis result.
Further, after receiving the ciphertext data report of the sensor device in the preset area, the edge aggregator specifically executes the following operations: verifying the validity of the signature of the ciphertext data report; for the ciphertext data report passing the verification, performing preset operation on the ciphertext data; and generating a digital signature of the edge aggregator based on the edge aggregator ID; forming a ciphertext data report based on the data subjected to the aggregation operation and the digital signature, and sending the ciphertext data report to a control center;
further, the trusted authority is further configured to: and generating an encryption public key and a decryption private key of a homomorphic encryption algorithm and a signature public key and a signature private key of a digital signature algorithm according to preset safety parameters, and distributing the keys based on preset rules.
Further, the blinding processing is performed on the number of devices in the current area based on the blinding number from the monitoring authority, specifically, the following formula is adopted for processing:
m′ k ＝αm k +β k
wherein m' k Number of devices after blinding, m k Alpha and beta are actual number of devices k Together forming the pair of blinded numbers.
Further, the distribution of the key specifically includes: the trusted authorization center encrypts the public key pk through a preset security channel AHE And the signature private key sk DS,i Distributing to sensor equipment; will encrypt the public key pk AHE The signature private key sk DS,EA And a signature public key pk DS,i Sending the data to an edge aggregator; will encrypt the public key pk AHE Signed private key sk DS,CC And a signature public key pk DS,EA Sending the data to a control center; will decrypt the private key sk AHE (p, q, λ) and a public signature verification key pk DS,CC And sending the information to a supervision agency.
Further, the generation of the digital signature specifically includes: and generating a digital signature corresponding to the equipment through a digital signature algorithm based on the equipment ID identification.
Further, the homomorphic encryption algorithm includes, but is not limited to, Paillier homomorphic encryption algorithm, and the digital signature algorithm includes, but is not limited to, ECDSA digital signature algorithm.
Further, the preset operation comprises a summation operation, an arithmetic mean, a quadratic mean, a weighted mean, a variance, a data anomaly number and a data anomaly ratio.
Further, the basic preprocessing includes representing the collected data as a data vector, a squared sensing data vector, a weighted sensing data vector, and determining whether the data is abnormal.
Specifically, for the convenience of understanding, the scheme of the present embodiment is described in detail below with reference to the accompanying drawings:
in order to solve the problems in the prior art, this embodiment provides a ciphertext data statistical analysis system supporting privacy protection, where the system includes the following five entities: a trusted authority TA; a sensor device SD; an edge aggregator EA; a control center CC; the regulatory agency SV. As shown in fig. 1, a data transmission flow chart of the system is shown, and the following describes the scheme of this embodiment in detail from the roles of different entities and the interaction among the entities:
trusted authority center TA
As shown in fig. 2, the following steps are specifically performed:
step A: and the TA generates a public and private key pair of the Paillier homomorphic encryption algorithm according to a given security parameter. Two large prime numbers p, q are randomly generated, and let N ═ pq and λ ═ lcm (p-1, q-1). Selecting
The order of g is a multiple of N.
And B: and the trusted authority center TA generates a public and private key pair of the ECDSA digital signature algorithm according to a given security parameter. Let G be a finite field
Base point of upper elliptic curve with order q 1 TA for each SD i TA selection of a Limited Domain
As its private key
And calculates out its public key pk DS,i ＝sk Ds,i ·G，SD i The public and private key pair is (pk) DS,i ,sk DS,i ) (ii) a Similarly, TA generates corresponding public and private key pair (pk) for EA, CC and SV DS,EA ,sk DS,EA )、(pk DS,CC ,sk DS,CC )、(pk DS,SV ,sk DS,SV ) (ii) a The system selects a secure hash function
And C: the trusted authority center TA encrypts the public key pair pk through a secure channel AHE (N, g) and the signature private key sk DS,i To sensor devices SD i (ii) a Will encrypt the public key pk AHE The signature private key sk DS,EA And a signature public key pk DS,i To the edge aggregator EA; will encrypt the public key pk AHE Signed private key sk DS,CC And a signature public key pk DS,EA Sending the data to a control center CC; will decrypt the private key sk AHE (p, q, λ) and a public signature verification key pk DS,CC To the regulatory authority SV.
Step D: random selection of a set of random numbers alpha, beta by a supervisory authority SV 1 ,β 2 ,…β n Wherein n is the number of edge gateways and satisfies beta 1 +β 2 +…+β n When the number is 0, the number is paired with (alpha, beta) k ) Sent to the corresponding edge aggregator EA over a secure channel k 。
(II) sensor device SD
When the sensor cluster generates the perception data, the multidimensional data is combined into a vector. Meanwhile, in order to realize a diversified statistical function, a square data vector and a weighted data vector are generated at the same time. As shown in fig. 3, the sensor device SD specifically performs the following steps:
step A: optional sensor SD i First, a l-dimensional perceptual data vector d is generated i ＝(d i,1 ,d i,2 ,...,d i,j ,...d i,l ) (ii) a Then, by calculating the square
Generating a squared perceptual data vector
Position weight w according to the present sensor i Through d i,j,wei ＝d i,j w i Calculating to obtain a weighted sensing data vector d i,wei ＝(d i,1,wei ,d i,2,wei ,...,d i,j,wei ,...,d i,l,wei )。
And B: each sensor has a range interval of normal values, if the value of any dimension of the sensing data exceeds the normal interval of the values, the value is judged to be abnormal, and the SD is judged i Is abnormal counter d i,cnt Set to 1, otherwise set to 0.
And C: at SD i Generation of d i ,
d i,wei And d cnt,i Then, the sensor encrypts data of each dimension respectively by using a Paillier homomorphic encryption algorithm to obtain corresponding ciphertext vectors
c i,wei ＝(c i,1,wei ,…,c i,l,wei ) And c i,cnt 。
Step D: given the current time stamp TS, SD i Identification name ID of i The sensor generates a digital signature using the ECDSA algorithm. SD i Selecting a random number
Calculating (r) x,i ,r y,i )＝k i G and
then the signature value sigma is obtained i ＝(sig i mod q 1 ,r x,i mod q 1 )。
And E, step E: sensor SD i Opt-in to send ciphertext data report to edge aggregator EA (c) i ,
c i,wei ,c i,cnt ,σ i ,TS,ID i )。
(III) edge aggregator EA
Edge aggregator EA received sensor SD i And after the sent data report, carrying out aggregation operation. If the aggregation operation is done in clear text, the private data is exposed to the untrusted edge aggregator. Therefore, we perform these statistical analysis operations on a ciphertext basis. The perceptual data aggregation under the ciphertext is based on the addition homomorphism property of the Paillier encryption algorithm, and a statistical analysis report under the ciphertext is generated, as shown in fig. 4, and specifically includes:
step A: the EA first verifies the validity of the signature received from the report. EA calculation
EA passed verification of r' x,i mod q 1 ＝r x,i mod q 1 And judging the validity of the signature if the signature is established.
And B, step B: and after the signature is verified, the edge aggregator EA executes the ciphertext aggregation operation. Utilizing the homomorphic nature of the Paillier algorithm, Dec (Enc (d) 1 )Enc(d 2 )mod N 2 )＝d 1 +d 2 mod N, EA calculation of c i ＝(c i,1 ,…,c i,l )，
c i,wei ＝(c i,1,wei ,…,c i,l,wei ) The sum c of each dimension j,sum ,c j,qsum ,c j,wsum (j is more than or equal to 1 and less than or equal to l). With c i For the example of the jth dimension of (c),
and C: the edge aggregator EA aggregates the counter ciphertext to obtain the total number ciphertext of the abnormal devices within the administration range of the EA, namely
Step D: the edge aggregator EA performs a blind processing on the sensing device number m in the area by using the blind number pair (α, β) transmitted by SV, and obtains m ═ α m + β.
And E, step E: given the current timestamp TS, EA identification ID EA The EA generates a digital signature. EA selects a random number
Calculating (r) x,EA ,r y,EA )＝k EA G and sig EA ＝(H(c 1,sum ||…||c l,sum ||c 1,qsum ||…||c l,qsum ||c 1,wsum ||…||c l,wsum ||c i,cnt ||TS||ID i )+sk DS,EA r x,EA )/k EA Then obtain the signature value sigma EA ＝(sig EA mod q 1 ,r x,EA mod q 1 )。
And E, step E: the edge aggregator EA sends a ciphertext data report to the control center CC (c) j,sum ,c j,qsum ,c j,wsum ,c cnt ,m′,σ EA ,TS,ID EA ),(1≤j≤l)。
(IV) control center CC
And after receiving the statistical analysis report sent by the edge aggregator EA, the control center CC performs ciphertext averaging. Since the total number of devices is blinded and hidden by the EA, the control center CC cannot know each EA k The specific number of devices governed and the total number of devices. Therefore, the average value obtained by CC is a blinded average value. As shown in fig. 5, the control center CC specifically executes the following steps:
step A: the CC verifies the validity of the statistical report signature. Calculating (r' x,EA ,r′ y,EA )＝G/(sig EA ·H(c 1,sum ||…||c l,sum ||c 1,qsum ||…||c l,qsum ||c 1,wsum ||…||c l,wsum ||c cnt ||m′||TS||ID EA )+pk EA /sig EA r x,EA EA pass verification of r' x,EA mod q 1 ＝r x,i mod q 1 And judging the validity of the signature if the signature is established.
And B: after the signature verification is passed, the control center CC transmits the blinded device number m 'for each EA' k And (k is more than or equal to 1 and less than or equal to n) are added. The result of the summation is m 'due to the nature of the blinding parameter' sum ＝m′ 1 +m′ 2 +…+m′ n ＝α(m 1 +m 1 +…+m n )+β 1 +β 2 +…+β n ＝α(m 1 +m 1 +…+m n )。
And C: utilizing homomorphism property of Paillier homomorphism encryption algorithm
And total number of blinded devices m' sum CC calculation of c i ,
c i,wei The blinded mean value c of each dimension j,mean ,c j,qmean ,c j,wmean . Taking the j-th dimension as an example,
abnormal equipment ratio example after CC calculation blinding
Step D: given the current timestamp TS, the ID of the identification name of CC CC The EA generates a digital signature. CC selects a random number
Calculating (r) x,CC ,r y,CC )＝k CC G and sig CC ＝(H(c 1,mean ||…||c l,mean ||c 1,qmean ||…||c l,qmean ||c 1,wmean ||…||c l,wmean ||c rat,cnt ||TS||ID CC )+sk DS,CC r x,CC )/k CC Then obtain the signature value sigma CC ＝(sig CC mod q 1 ,r x,CC mod q 1 )。
Step E: the control center CC sends a ciphertext data report to the supervision authority SV (c) j,mean ,c j,qmean ,c j,wmean ,c rat,cnt ,σ CC ,TS,ID CC ),(1≤j≤l)。
(V) supervision agency SV
And after receiving the statistical analysis report sent by the control center CC, the SV of the supervision institution performs decryption and post-processing work. The supervisory authority SV visualizes the decrypted mean value (ratio). If the statistical data (e.g., mean) is itself a fractional number, decryption will result in a meaningless large number. Therefore, in post-processing, an improved extended euclidean algorithm is introduced to perform reduction to obtain an approximation of the fractional number. The supervision authority SV specifically executes the following steps:
step A: the control center CC first verifies the validity of the signature received with the statistical report. SV calculation (r' x,CC ,r′ y,CC )＝G/(sig CC ·H(c 1,mean ||…||c l,mean ||c 1,qmean ||…||c l,qmean ||c 1,wmean ||…||c l,wmean ||c rat,cnt ||TS||ID CC )+pk CC /sig CC ·r x,CC SV passes verification of r' x,CC mod q 1 ＝r x,i mod q 1 And judging the validity of the signature if the signature is established.
And B: after the signature verification is passed, the supervision agency SV executes Paillier decryption operation. SV calculation d ═ L (c) λ mod n 2 ) μ mod n, here
μ＝(L(g λ mod n 2 )) -1 mod N. The decrypted mean value and abnormal device proportion of each dimension are still in a blinded and hidden state and are expressed as (d' 1,mean ,…,d′ l,mean ,d′ 1,qmean ,…,d′ l,qmean ,d′ 1,wmean ,…,d′ l,wmean ,d′ rat,cnt )。
And C: after decryption, the supervision authority SV performs a de-blinding operation. D' j,mean De-blinding is exemplified by SV calculation d j,mean ＝αd′ j,mean . After de-blinding, the mean value of each dimension and the abnormal equipment ratio are expressed as (d) 1,mean ,…,d l,mean ,d 1,qmean ,…,d l,qmean ,d 1,wmean ,…,d l,wmean ,d rat,cnt )。
Step D: and carrying out the expansion Euclidean reduction on the decrypted average value, and converting the average value into a correct floating point number. The reduction algorithm as described in table 1 was performed:
the reduced mean value is expressed as (D) 1,mean ,…,D l,mean ,D 1,qmean ,…,D l,qmean ,D 1,wmean ,…,D l,wmean ,D rat,cnt )。
Step D: and calculating quadratic mean and variance. CC calculation of quadratic mean values in different dimensions
Calculating the variance D in different dimensions j,var ＝D j,qmean -(D j,mean ) 2 。
Example two:
the embodiment aims to provide a ciphertext data statistical analysis method supporting privacy protection.
A ciphertext data statistical analysis method supporting privacy protection is based on the ciphertext data statistical analysis system supporting privacy protection, and comprises the following steps:
the trusted authorization center generates independent public keys and private keys for the sensor equipment, the edge aggregator, the control center and the monitoring authority;
the sensor equipment performs basic preprocessing on the acquired data, encrypts the data through a homomorphic encryption algorithm, generates a digital signature of the sensor equipment by using a digital signature algorithm based on the ID of the sensor equipment to form a ciphertext data report, and sends the ciphertext data report to an edge aggregator;
the edge aggregator receives a ciphertext data report of the sensor equipment in a preset area, and performs preset operation processing on encrypted data in the ciphertext data report; meanwhile, the equipment number of the current area is subjected to blinding processing based on a blinding number from a supervision mechanism, a ciphertext data report is formed based on the data subjected to the preset operation processing and the digital signature of the edge aggregator, and the ciphertext data report is sent to a control center;
the control center receives the ciphertext data report from the edge aggregator and performs preset operation processing on the encrypted data in the ciphertext data report; based on the processed encrypted data and the digital signature of the control center, a ciphertext data report is formed and sent to a supervision organization;
and the supervision mechanism receives the ciphertext data report from the control center, decrypts and de-blinds the ciphertext data, and obtains a statistical analysis result.
Further, the method of this embodiment is based on the system described in the first embodiment, and the technical details thereof have been described in detail in the first embodiment, so that details are not repeated herein.
The cryptograph data statistical analysis system and the cryptograph data statistical analysis method supporting privacy protection can be achieved, and have wide application prospects.
The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure, and various modifications and changes may be made to the present disclosure by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.
Claims (10)
1. A ciphertext data statistics analysis system that supports privacy protection, comprising:
a trusted authority for generating independent public and private keys for the sensor device, the edge aggregator, the control center, and the regulatory body;
the sensor equipment is used for performing basic preprocessing on the acquired data, encrypting the data through a homomorphic encryption algorithm, generating a digital signature of the sensor equipment by using a digital signature algorithm based on the ID of the sensor equipment to form a ciphertext data report, and sending the ciphertext data report to the edge aggregator;
the edge aggregator is used for receiving ciphertext data reports of the sensor equipment in the preset area and performing preset operation processing on encrypted data in the ciphertext data reports; meanwhile, the equipment number of the current area is subjected to blinding processing based on a blinding number from a supervision mechanism, a ciphertext data report is formed based on the data subjected to the preset operation processing and the digital signature of the edge aggregator, and the ciphertext data report is sent to a control center;
the control center is used for receiving the ciphertext data report from the edge aggregator and carrying out preset operation processing on the encrypted data in the ciphertext data report; forming a ciphertext data report based on the processed encrypted data and a digital signature of a control center, and sending the ciphertext data report to a supervision agency;
and the monitoring mechanism is used for receiving the ciphertext data report from the control center, carrying out decryption processing and de-blinding processing on the ciphertext data and obtaining a statistical analysis result.
2. The system for statistical analysis of ciphertext data supporting privacy protection as claimed in claim 1, wherein the edge aggregator, after receiving the ciphertext data report of the sensor device in the preset area, specifically performs the following operations: verifying the validity of the signature of the ciphertext data report; for the ciphertext data report passing the verification, performing preset operation on the ciphertext data; and generating a digital signature of the edge aggregator based on the edge aggregator ID; and forming a ciphertext data report based on the data subjected to the aggregation operation and the digital signature, and sending the ciphertext data report to a control center.
3. The system for statistically analyzing ciphertext data supporting privacy protection as claimed in claim 1, wherein the trusted authority is further configured to: and generating an encryption public key and a decryption private key of a homomorphic encryption algorithm and a signature public key and a signature private key of a digital signature algorithm according to preset safety parameters, and distributing the keys based on preset rules.
4. The system for statistically analyzing ciphertext data supporting privacy protection as claimed in claim 1, wherein the distribution of the key specifically comprises: the trusted authorization center encrypts the public key pk through a preset security channel AHE And the signature private key sk DS,i Distributing to sensor equipment; will encrypt the public key pk AHE The signature private key sk DS,EA And a signature public key pk DS,i Sending the data to an edge aggregator; will encrypt the public key pk AHE Signed private key sk DS,CC And a signature public key pk DS,EA Sending the data to a control center; will decrypt the private key sk AHE (p, q, λ) and a public signature verification key pk DS,CC And sending the information to a supervision agency.
5. The system for statistically analyzing ciphertext data supporting privacy protection as claimed in claim 1, wherein the number of devices in the current area is blinded based on the blinded number from the monitoring authority, and is specifically processed by using the following formula:
m′ k ＝αm k +β k
wherein m' k Number of devices after blinding, m k Alpha and beta are actual number of devices k Together forming the pair of blinded numbers.
6. The system for statistically analyzing ciphertext data supporting privacy protection as claimed in claim 1, wherein the digital signature is generated by: and generating a digital signature corresponding to the equipment through a digital signature algorithm based on the equipment ID identification.
7. The ciphertext data statistical analysis system in support of privacy protection as claimed in claim 6, wherein the homomorphic encryption algorithm includes but is not limited to Paillier homomorphic encryption algorithm and the digital signature algorithm includes but is not limited to ECDSA digital signature algorithm.
8. The ciphertext data statistical analysis system supporting privacy protection of claim 1, wherein the predetermined operations include a summation operation, an arithmetic mean, a quadratic mean, a weighted mean, a variance, a number of data anomalies, and a data anomaly percentage.
9. The system for statistical analysis of ciphertext data supporting privacy protection as claimed in claim 1, wherein the basic preprocessing comprises representing the collected data as data vectors, square perceptual data vectors, weighted perceptual data vectors and determining whether the data is abnormal.
10. A ciphertext data statistical analysis method supporting privacy protection, which is based on the ciphertext data statistical analysis system supporting privacy protection as claimed in any one of claims 1-9, and comprises:
the trusted authorization center generates independent public keys and private keys for the sensor equipment, the edge aggregator, the control center and the monitoring authority;
the sensor equipment performs basic preprocessing on the acquired data, encrypts the data through a homomorphic encryption algorithm, generates a digital signature of the sensor equipment by using a digital signature algorithm based on the ID of the sensor equipment to form a ciphertext data report, and sends the ciphertext data report to an edge aggregator;
the edge aggregator receives a ciphertext data report of the sensor equipment in a preset area, and performs preset operation processing on encrypted data in the ciphertext data report; meanwhile, the equipment number of the current area is subjected to blinding processing based on a blinding number from a supervision mechanism, a ciphertext data report is formed based on the data subjected to the preset operation processing and the digital signature of the edge aggregator, and the ciphertext data report is sent to a control center;
the control center receives the ciphertext data report from the edge aggregator and performs preset operation processing on the encrypted data in the ciphertext data report; based on the processed encrypted data and the digital signature of the control center, a ciphertext data report is formed and sent to a supervision organization;
and the supervision mechanism receives the ciphertext data report from the control center, decrypts and de-blinds the ciphertext data, and obtains a statistical analysis result.
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