A method and system for edge data integrity auditing

Abstract

The present invention discloses an edge data integrity audit method and system, the method comprising: an application service provider uploads data to multiple edge servers; the application service provider selects at least one target edge server to initiate an audit challenge; the target edge server receives the audit challenge and returns corresponding data integrity evidence to the application service provider according to the audit challenge; the application service provider verifies the returned data integrity evidence. The present invention supports the application service provider to quickly upload data to each edge server, which is conducive to the efficient deployment of services, and when the application service provider initiates a challenge, each edge server calculates and returns the integrity evidence under the condition of only a small amount of computing overhead, and the application service provider as an auditor can quickly verify the data integrity of all challenged edge servers at one time, which can effectively improve the efficiency and security of the integrity audit of edge data.

Description

Technical Field

[0001] The present invention relates to the field of cloud auditing technology, and in particular to an edge data integrity auditing method and system. Background Art

[0002] Edge cloud services are developing rapidly. As 5G further increases the data transmission rate and the data scale grows significantly, edge computing service providers organize enterprise-level scalable and reliable edge computing infrastructure to provide some application service providers (SV) with distributed edge service networks for real-time computing and edge data storage. For these application service providers, planning and deploying edge service networks is an unstoppable trend in the future, because their businesses need to provide low-latency application services in places geographically close to users to meet the user experience and show sufficient competitiveness, such as smart IoT, online live broadcasts, virtual reality games, etc.

[0003] When SV stores data in a large number of edge servers, the integrity of this data becomes a challenge. Similar to the traditional cloud storage data integrity (CDI) problem, the data integrity in edge servers is questionable and needs to be reviewed. For complex edge service networks, data integrity audits are more necessary and more challenging, because edge networks composed of a large number of edge service nodes are more prone to data corruption and hardware damage, whether accidental or intentional.

[0004] At present, most of the solutions to edge data integrity audit still follow the idea of ​​traditional cloud storage data integrity audit. A well-known solution is the PDP method (Provable Data Possession Mechanism, PDP) based on homomorphic authentication tag technology. The correctness and security of the PDP method depend on the private key that only the data owner or challenger knows, and the method of calculating the homomorphic authentication tag block, or the data block Tag (which can be understood as the signature of the data block). Auditors regularly challenge the cloud and verify whether the cloud storage data is intact by calculating whether the authentication tag (Tag) of the challenge data copy is equal to the proof returned by the cloud. In essence, this type of solution regards edge data audit as a variant of traditional multi-cloud storage audit, combined with the homomorphic aggregation properties, and realizes data integrity audit in edge servers by directly deploying the cloud storage audit protocol.

[0005] Solutions based on traditional auditing ideas do not fully observe and utilize the differences in motivations and environments between cloud storage and edge data storage. First, from a high-level perspective, we find that data integrity issues under edge cloud architecture and traditional cloud storage data auditing issues have different motivations, and therefore have different needs and design requirements, and finally different solutions. Specifically, traditional cloud storage auditing issues focus on solving user local storage bottlenecks, and users will choose to delete local data after outsourcing data. Data storage services under edge cloud architecture are often provided by application service providers to meet users' needs for data latency and provide better application experience. Therefore, the current research on data auditing solutions for edge storage, whether SV or ES (Edge Server, edge server) bears a heavy computing burden, and the operating efficiency of the protocol is relatively low. In addition, the traditional single-cloud-based storage auditing protocol does not perform well in supporting data dynamics and data error correction. Summary of the invention

[0006] The embodiments of the present invention provide an edge data integrity audit method and system, aiming to improve the efficiency and security of edge data integrity audit.

[0007] An embodiment of the present invention provides an edge data integrity audit method, comprising:

[0008] The application service provider uploads the data in the form of data blocks to multiple edge servers;

[0009] The application service provider selects at least one target edge server from a plurality of edge servers to initiate an audit challenge;

[0010] The target edge server receives the audit challenge and returns corresponding data integrity evidence to the application service provider according to the audit challenge;

[0011] The application service provider verifies the returned data integrity evidence.

[0012] Furthermore, before the application service provider uploads the data in the form of data blocks to the multiple edge servers, the application service provider includes:

[0013] The application service provider generates a key through a registration machine and constructs a pseudo-random function generator.

[0014] Furthermore, the application service provider selects at least one target edge server from the plurality of edge servers to initiate an audit challenge, including:

[0015] When the application service provider is in a security model where the edge cloud server is untrustworthy and non-colluded, the application service provider selects a challenged data block for each of the target edge servers, and generates a data block index and a secret matrix of the challenged data block using the pseudo-random function generator; and then sends the data block index and the secret matrix as challenge data to the target edge server;

[0016] When the application service provider is in a security model where the edge cloud server is untrustworthy and colludes, the application service provider selects a challenged data block for each of the target edge servers, and uses the pseudo-random function generator to generate a data block index, a coefficient matrix and a secret number for the challenged data block; and then sends the data block index and the coefficient matrix as challenge data to the target edge server.

[0017] Further, the target edge server receives the audit challenge and returns corresponding data integrity evidence to the application service provider according to the audit challenge, including:

[0018] The target edge server obtains the corresponding challenged data block from the stored edge data copy according to the challenge data in the finite domain, and calculates the challenged data block and the challenge data in an agreed paradigm as data integrity evidence and returns it to the application service provider.

[0019] Furthermore, the application service provider verifies the returned data integrity evidence, including:

[0020] The application service provider locally calculates and obtains edge data integrity verification information for this challenge;

[0021] Aggregating the data integrity evidence returned by all the target edge servers to obtain an authentication evidence data block;

[0022] Comparing the edge data integrity check information with the authentication evidence data block;

[0023] When the edge data integrity check information is the same as the authentication evidence data block, it proves that the data stored in the target edge server is not damaged; when the edge data integrity check information is different from the authentication evidence data block, it proves that the data stored in the corresponding target edge server is damaged.

[0024] Further, when the edge data integrity check information is different from the authentication evidence data block, it is proved that the data stored in the corresponding target edge server is damaged, including:

[0025] The binary search method is used to locate the target edge server where data corruption occurs.

[0026] Furthermore, before the application service provider uploads the data in the form of data blocks to the multiple edge servers, the process further includes:

[0027] In the case where the edge server is accessible, the application service provider calculates a homomorphic authentication tag for the stored data block.

[0028] The embodiment of the present invention further provides an edge data integrity audit system, including an application service provider and multiple edge servers, wherein:

[0029] The application service providers include:

[0030] A data uploading unit, used by an application service provider to upload data in the form of data blocks to multiple edge servers;

[0031] An audit challenge unit, configured for the application service provider to select at least one target edge server from a plurality of edge servers to initiate an audit challenge;

[0032] An evidence verification unit, used by the application service provider to verify the returned data integrity evidence;

[0033] Each of the edge servers comprises:

[0034] The evidence returning unit is used for the target edge server to receive the audit challenge and return corresponding data integrity evidence to the application service provider according to the audit challenge.

[0035] Furthermore, the application service provider also includes:

[0036] A key generation unit, used for the application service provider to generate a key through a registration machine and construct a pseudo-random function generator;

[0037] The matrix generating unit is used to generate a secret matrix and a coefficient matrix by using the pseudo-random function generator, and to generate a data block index and a secret number of the challenged data block.

[0038] Furthermore, the edge server also includes:

[0039] The evidence calculation unit is used for the target edge server to obtain the corresponding challenged data block from the stored edge data copy according to the challenge data on the finite domain, and calculate the challenged data block and the challenge data in an agreed paradigm as data integrity evidence and return it to the application service provider.

[0040] The embodiment of the present invention provides an edge data integrity audit method and system, the method comprising: an application service provider uploads data in the form of data blocks to multiple edge servers; the application service provider selects at least one target edge server from the multiple edge servers to initiate an audit challenge; the target edge server receives the audit challenge and returns corresponding data integrity evidence to the application service provider according to the audit challenge; the application service provider verifies the returned data integrity evidence. The embodiment of the present invention supports the rapid deployment of services in the data outsourcing stage. In the face of malicious non-colliding edge servers, the application service provider only needs to upload data to each edge server. In the face of malicious collusion edge servers, it is necessary to calculate a homomorphic authentication tag to achieve efficient. In the data audit stage, when the application service provider initiates a challenge, each edge server calculates and returns the integrity evidence in an agreed paradigm. Finally, in the verification stage, the application service provider can quickly verify the data integrity of all challenged edge servers at one time. Through the above process, the efficiency and security of the integrity audit of edge data can be effectively improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying any creative work.

[0042] Figure 1 A schematic diagram of a flow chart of an edge data integrity audit method provided by an embodiment of the present invention;

[0043] Figure 2 The following is a schematic diagram of the audit paradigm of the traditional cloud storage data integrity (CDI) audit method;

[0044] Figure 3 Schematic diagram of the audit paradigm for edge data integrity (EDI) audit methods in edge computing environments;

[0045] Figure 4 A schematic block diagram of an edge data integrity audit system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0048] It should also be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0049] It should be further understood that the term "and / or" used in the present description and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0050] See below Figure 1 , Figure 1 A flow chart of an edge data integrity audit method provided by an embodiment of the present invention specifically includes: steps S101 to S104.

[0051] S101, the application service provider uploads data in the form of data blocks to multiple edge servers;

[0052] S102, the application service provider selects at least one target edge server from multiple edge servers to initiate an audit challenge;

[0053] S103, the target edge server receives the audit challenge, and returns corresponding data integrity evidence to the application service provider according to the audit challenge;

[0054] S104: The application service provider verifies the returned data integrity evidence.

[0055] The embodiments of the present invention support rapid deployment of services during the data outsourcing stage. When faced with malicious edge servers that are not connected, the application service provider only needs to upload data to each edge server. When faced with malicious edge servers that are connected, it is necessary to calculate a homomorphic authentication tag to achieve efficient authentication. During the data audit stage, when the application service provider initiates a challenge, each edge server calculates and returns integrity evidence in an agreed format. Finally, during the verification stage, the application service provider can quickly verify the data integrity of all challenged edge servers at one time. Through the above process, the audit efficiency and security of edge data integrity can be effectively improved.

[0056] Combination Figure 2 Generally speaking, the CDI protocol is deployed in the classic Client-Server (CS) model. Before outsourcing data, the user generates a key through KeyGen (registration machine) and uses the private key to calculate the data label. Subsequently, in the OutSource (data outsourcing) stage, the data and label blocks are uploaded to the cloud together, and T represents the homomorphic authentication information corresponding to the source data. After that, the user or authorized challenger will initiate an audit to the cloud and require the cloud to return a data integrity certificate, including the challenged aggregate source data block D' and the corresponding aggregate homomorphic authentication label block T'. After receiving the certificate returned by the cloud, the auditor will execute the Verify algorithm to verify whether the challenged data is complete.

[0057] The security and correctness of the traditional cloud storage data integrity audit paradigm are based on the confidentiality of private keys and the method of calculating data authentication tags. The motivation for users to choose cloud storage services is to solve the bottleneck of local storage resources. Therefore, after users upload data, they will delete the original data locally. Therefore, in order for the audit to be successful, users need to protect the secret of the calculated authentication tag from being known by the cloud server.

[0058] Edge data integrity (EDI) audit issues, like CDI issues, belong to big data integrity audit issues. The two have strong similarities, and most of the current edge data integrity research still follows the traditional CDI audit ideas. But the two are actually significantly different.

[0059] like Figure 3As shown in the figure, the application service provider (SV) always keeps the original data during the edge audit process. This is because SV, as the owner of the data, has different motivations from CS (Cloud Storage) users. In EDI audit, the application service provider stores data in the edge server (ES) mainly to solve the network delay caused by the service rather than to solve the local storage bottleneck. In contrast to CDI, SV must always hold the original data. In the CDI audit paradigm, since the client (user) deletes the outsourced data locally, this imposes a strong constraint on the data audit scheme. In CDI audit, since the data is no longer owned locally, the client must calculate the data authentication label in advance when outsourcing the data; when challenged, CS does not know how to calculate the authentication label, it is required and only knows how to calculate the aggregated data block and label block. In the EDI audit paradigm, since ES always has the original data, the task of calculating the verification information can be completed by ES. The key to the EDI audit protocol becomes how to make ES honestly calculate the data possession proof based on its own stored data copy every time it receives a challenge, and cannot deceive SV.

[0060] This embodiment provides an edge data integrity audit paradigm. First, in the data outsourcing stage, SV only needs to upload data to each edge server, which is conducive to the rapid deployment of services. In the data audit stage, when SV initiates a challenge, each ES calculates a fast message digest (T′ i (D′ i )) form and returns the integrity proof. Finally, in the Verify phase, SV can quickly verify the data integrity of all challenged edge servers at one time.

[0061] At the same time, combined with the characteristics of the edge audit environment, this embodiment proposes the design requirements for edge storage auditing:

[0062] -Req1: Data corruption check. This is the most basic requirement of the edge data integrity audit protocol, which can monitor the integrity of data in the edge server and detect edge data corruption.

[0063] -Req2: Location of damaged data. For highly distributed edge service networks, SV can locate edge servers where data damage occurs and inform edge service providers to restore data without having to check each server one by one or redeploy all of them.

[0064] -Req3: Efficient auditing. Faced with a large number of edge servers, SV must be able to verify the data integrity of all ES at once. For ES, it must be able to quickly calculate the proof after receiving the challenge. For SV, most of the deployed edge services are delay-sensitive. A fast audit protocol can detect and solve problems as early as possible when data corruption occurs, reducing the impact of unexpected events.

[0065] -Req4: Do not incur high computing overhead on edge servers. The computing power of ES is limited, and EC (Edge Computing) does not have as strong computing power as traditional cloud computing (CC). In addition, implementing Req4 is also to better implement Req3.

[0066] In one embodiment, before step S101, the following steps are included:

[0067] The application service provider generates a key through a registration machine and constructs a pseudo-random function generator;

[0068] The pseudo-random function generator is used to generate a secret matrix, and a data block index and a secret number of a challenged data block are generated.

[0069] Furthermore, the step S102 includes:

[0070] When the application service provider is in a security model where the edge cloud server is untrustworthy and non-colluded, the application service provider selects a challenged data block for each of the target edge servers, and uses the pseudo-random function generator to generate a data block index and a secret matrix for the challenged data block; and then sends the data block index and the secret matrix as challenge data to the target edge server.

[0071] The step S103 includes:

[0072] The target edge server obtains the corresponding challenged data block from the stored edge data copy according to the challenge data in the finite domain, and calculates the challenged data block and the challenge data in an agreed paradigm as data integrity evidence and returns it to the application service provider.

[0073] The step S104 includes:

[0074] The application service provider locally calculates and obtains edge data integrity verification information for this challenge;

[0075] Aggregating the data integrity evidence returned by all the target edge servers to obtain an authentication evidence data block;

[0076] Comparing the edge data integrity check information with the authentication evidence data block;

[0077] When the edge data integrity check information is the same as the authentication evidence data block, it proves that the data stored in the target edge server is not damaged; when the edge data integrity check information is different from the authentication evidence data block, it proves that the data stored in the corresponding target edge server is damaged.

[0078] The embodiment of the present invention creates the first audit protocol EDC-L through the above content, and its specific workflow is as follows:

[0079] Setup: This phase is used to determine protocol specific parameters and avoid large integer operations by treating each data block as a k-dimensional vector over a selected finite field.

[0080] KeyGen (registration machine): In this stage, the key is generated and two pseudo-random function generators are constructed. One pseudo-random function is used to generate the secret matrix A, and the other is used to generate the data block index of the challenged data block.

[0081] OutSource (data outsourcing): At this stage, the advantages of the EDI audit paradigm were demonstrated for the first time. For edge service data to be deployed on a large scale, if the PDP protocol that follows the traditional CDI audit paradigm is adopted, SV needs to calculate the corresponding homomorphic authentication tag for each data block uploaded to different edge servers. For EDC-L, SV only needs to upload the original data to each edge server. EDC-L requires a data warehouse to perform an audit in the form of a random hash summary of a copy of the data at each audit. Therefore, unlike the traditional PDP solution, homomorphic authentication tags need to be calculated before outsourcing data.

[0082] At this stage, users only need to outsource data directly to each edge server.

[0083] Audit: To challenge each edge server, SV needs to randomly select l challenged data blocks for each edge server. In addition, SV needs to generate a secret matrix for ES to calculate authentication information (in the form of random hash digest). Matrix A and l challenged data block indexes are sent to each ES as challenge data.

[0084] Prove, in order to calculate the proof and respond, the audited edge node obtains the challenged data block from the stored edge data copy to calculate the proof. The algorithm for calculating the proof is simple and efficient. This process is performed on the finite field GF(q) and does not involve large integers or any exponentiation operations. EDC-L will not add too much computational burden to ES, satisfying Req4.

[0085] Specifically, after receiving the challenge data, the i-th edge server quickly calculates a random hash summary that meets the security requirements in the following way:

[0086]

[0087] Verify can be divided into three steps to verify the integrity of all edge data. First, SV calculates the edge data integrity check information R' in a challenge process locally. After receiving the integrity proof returned by all edge servers, calculate the returned aggregated authentication evidence data block R. Finally, by comparing R == R', it is determined whether the edge service data is damaged. Such an EDC-L scheme satisfies Req1 and Req3.

[0088] Specifically, the user first calculates the returned aggregated authentication evidence data block R:

[0089]

[0090] The user calculates the edge data integrity check block R' locally and compares it with the returned aggregated authentication evidence data block R:

[0091]

[0092] δ=1: audit passed;

[0093] δ=0: The audit failed.

[0094] The EDC-L audit protocol provided in this embodiment has the following advantages: EDC-L can resist malicious edge cloud nodes, compared with, for example, the ICL solution in the prior art cannot resist replay attacks and cannot resist malicious edge clouds; it can perform a one-time check on the data integrity of a large number of edge cloud nodes; it is highly efficient and does not add too much additional computing burden to edge nodes; it avoids large integer operations and complex modular exponentiation operations; it is more efficient than the traditional homomorphic labeling solution; it is more efficient than the ICL solution; compared with the traditional homomorphic authentication labeling solution, it does not constrain the data dynamic function. No additional control protocol is required to support the data dynamic function.

[0095] In one embodiment, when the edge data integrity check information is different from the authentication evidence data block, it is proved that the data stored in the corresponding target edge server is damaged, including:

[0096] The binary search method is used to locate the target edge server where data corruption occurs.

[0097] In this embodiment, the available edge data integrity audit protocol is also required to be able to locate the corresponding edge server when data corruption occurs, that is, to meet Req2. In the ICL scheme, an idea of ​​binary search is proposed, but this requires the protocol to be efficient in calculating Verify. In principle, an audit protocol that meets Req3 can use the idea of ​​binary search to determine the location where data corruption occurs. The audit protocols in this embodiment can all use the binary method to locate the edge server where data corruption occurs. The advantage of using the binary search idea to locate errors is that when SV receives the proof data returned by any ES, it can start calculating the aggregate authentication evidence data block R. When the data proof returned by the last edge server is received, the final aggregate authentication evidence data block can be quickly obtained.

[0098] Of course, in other embodiments, there are many other ways to locate corrupted data. SV can store the proof data returned by all servers and then verify them one by one. This is obviously faster, but at the cost of more storage space.

[0099] In one embodiment, before step S101, the method further includes:

[0100] In the case where the edge server is accessible, the application service provider calculates a homomorphic authentication tag for the stored data block.

[0101] The step S102 further includes:

[0102] When the application service provider is in a security model where the edge cloud server is untrustworthy and colludes, the application service provider selects a challenged data block for each target edge server, and uses the pseudo-random function generator to generate a data block index, a coefficient matrix and a secret number of the challenged data block; and then sends the data block index and the coefficient matrix as challenge data to the target edge server. Among them, the secret number can be understood as a vector composed of finite field elements.

[0103] In this embodiment, before uploading the data to the edge server, the application service provider will also calculate the corresponding homomorphic authentication data tag for the data, which leads to the second audit protocol EDC-R of the embodiment of the present invention.

[0104] Specifically, the work in the Setup and KeyGen stages is very similar to that of EDC-L. In the Setup stage, this embodiment selects the same finite field as EDC-L. Except for the need to re-specify the data block partitioning parameters and the homomorphic label block size parameters, the other main control parameters are consistent with those of ECL-L. In the KeyGen stage, EDC-R needs to prepare the coefficient matrix for generating the challenge data and the key for the secret number, and other parts are the same as EDC-L.

[0105] At the Outsource stage, this embodiment needs to calculate the homomorphic authentication data tag (AuthenticationTag) corresponding to the data block. First, SV needs to generate a secret matrix A for each edge server i And the number of secrets required to calculate each authentication tag block. For simplicity, A i It can be a diagonal matrix. After calculating all authentication tag blocks, SV deploys the source data and authentication tag data to the edge server.

[0106] In order to support application service providers to quickly deploy services to each edge server, the embodiment of the present invention provides the homomorphic authentication tag block σ of the jth data block of the i-th edge data. ij The calculation method is as follows:

[0107]

[0108] (D i ,σ i ): Final source data and corresponding homomorphic authentication label data (D i ,σ i ) constitutes the outsourced data stored in the i-th edge node.

[0109] In the Audit phase, when a challenge is initiated, the SV sends the challenge data to each ES. The SV needs to randomly select l data blocks and generate calculation coefficients for each edge server to ensure the freshness of each challenge. The selection of l here is the same as EDC-L.

[0110] In the Prove phase, the edge server returns the challenge source data block and the corresponding authentication tag information in an aggregated form. The specific operation is to add the challenged data block on the finite field and finally multiply it by the coefficient matrix. Specifically, the i-th edge server calculates the aggregated homomorphic authentication data tag:

[0111]

[0112] Compute aggregate source data blocks:

[0113]

[0114] In the Verify phase, SV first calculates the aggregated authentication evidence data block R. Then, SV calculates the edge data integrity verification information, R'. By comparing whether the two are equal, SV can verify whether the data in all edge servers is complete at once.

[0115] Specifically, the user first calculates the returned aggregated authentication evidence data block:

[0116]

[0117] Based on the homomorphic nature of the designed authentication tag, the user calculates the edge data integrity check block R' through the aggregated data block returned by each edge audit node and compares it with R:

[0118]

[0119] δ=1: audit passed;

[0120] δ=0: The audit failed.

[0121] Although the process of EDC-L and EDC-R audits is similar, there are still some differences between the two, as follows:

[0122] The threat models they work in are different: EDC-L can deal with malicious edge nodes, but does not allow edge nodes to collude with each other; EDC-R can work in malicious edge nodes, and the edge server can collude in this extreme threat model.

[0123] Different efficiency: EDC-L has a faster audit rate, while EDC-R has relatively poor performance and requires additional space to store homomorphic authentication information.

[0124] Protocol type: EDC-L completes the audit by verifying the random hash summary of the data copy; EDC-R completes the audit by verifying the homomorphic authentication information.

[0125] More scalability: EDC-L can support data dynamics without additional control and calculation; EDC-R requires additional control details to support data dynamics.

[0126] In general, compared with existing studies, the first audit protocol EDC-L and the second audit protocol EDC-R provided by the embodiment of the present invention consume less time in the three stages of (1) user OutSource, (2) cloud computing ProofData, and (3) user Verify under the same number of edge servers (esNum) and data scale (DataSize).

[0127] The EDC-R audit protocol provided in this embodiment has the following advantages: it can resist malicious and colluding edge cloud nodes; it can perform a one-time verification of the data integrity of a large number of edge cloud nodes; it is more efficient than traditional homomorphic solutions; and it avoids large integer operations and complex modular exponentiation operations.

[0128] like Figure 4 As shown, the embodiment of the present invention further provides an edge data integrity audit system 400, including an application service provider 401 and multiple edge servers 402, wherein:

[0129] The application service provider 401 includes:

[0130] The data uploading unit 4011 is used for the application service provider 401 to upload data in the form of data blocks to the multiple edge servers 402;

[0131] An audit challenge unit 4012, configured for the application service provider 401 to select at least one target edge server from the plurality of edge servers 402 to initiate an audit challenge;

[0132] The evidence verification unit 4013 is used for the application service provider 401 to verify the returned data integrity evidence;

[0133] Each of the edge servers 402 includes:

[0134] The evidence returning unit 4021 is configured for the target edge server to receive the audit challenge and return corresponding data integrity evidence to the application service provider 401 according to the audit challenge.

[0135] In one embodiment, the application service provider 401 further includes:

[0136] The key generation unit is used for the application service provider to generate a key through a registration machine and construct a pseudo-random function generator.

[0137] In one embodiment, the edge server 402 further includes:

[0138] The evidence calculation unit is used for the target edge server to obtain the corresponding challenged data block from the stored edge data copy according to the challenge data on the finite domain, and return the challenged data block and the challenge data as evidence of data integrity to the application service provider in the agreed paradigm.

[0139] The various embodiments in the specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same and similar parts between the various embodiments can be referred to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description. It should be pointed out that for ordinary technicians in this technical field, without departing from the principles of this application, several improvements and modifications can be made to the present application, and these improvements and modifications also fall within the scope of protection of the claims of this application.

[0140] It should also be noted that, in this specification, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprises", "comprising" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprising a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

Claims

1. An edge data integrity audit method, characterized in that: include: The application service provider uploads the data in the form of data blocks to multiple edge servers; The application service provider selects at least one target edge server from a plurality of edge servers to initiate an audit challenge; The target edge server receives the audit challenge and returns corresponding data integrity evidence to the application service provider according to the audit challenge; The application service provider verifies the returned data integrity evidence; Before the application service provider uploads the data in the form of data blocks to multiple edge servers, it includes: The application service provider generates a key through a registration machine and constructs a pseudo-random function generator; The application service provider selects at least one target edge server from a plurality of edge servers to initiate an audit challenge, including: When the application service provider is in a security model where the edge cloud server is untrustworthy and non-colluded, the application service provider selects a challenged data block for each of the target edge servers, and generates a data block index and a secret matrix of the challenged data block using the pseudo-random function generator; and then sends the data block index and the secret matrix as challenge data to the target edge server; When the application service provider is in a security model where the edge cloud server is untrustworthy and colludes, the application service provider selects a challenged data block for each of the target edge servers, and uses the pseudo-random function generator to generate a data block index, a coefficient matrix and a secret number for the challenged data block; and then sends the data block index and the coefficient matrix as challenge data to the target edge server.

2. The edge data integrity audit method according to claim 1, characterized in that: The target edge server receives the audit challenge and returns corresponding data integrity evidence to the application service provider according to the audit challenge, including: The target edge server obtains the corresponding challenged data block from the stored edge data copy according to the challenge data in the finite domain, and calculates the challenged data block and the challenge data in an agreed paradigm as data integrity evidence and returns it to the application service provider.

3. The edge data integrity audit method according to claim 2, characterized in that: The application service provider verifies the returned data integrity evidence, including: The application service provider locally calculates and obtains edge data integrity verification information for this challenge; Aggregating the data integrity evidence returned by all the target edge servers to obtain an authentication evidence data block; Comparing the edge data integrity check information with the authentication evidence data block; When the edge data integrity check information is the same as the authentication evidence data block, it proves that the data stored in the target edge server is not damaged; when the edge data integrity check information is different from the authentication evidence data block, it proves that the data stored in the corresponding target edge server is damaged.

4. The edge data integrity audit method according to claim 3, characterized in that: When the edge data integrity check information is different from the authentication evidence data block, it is proved that the data stored in the corresponding target edge server is damaged, including: The binary search method is used to locate the target edge server where data corruption occurs.

5. The edge data integrity audit method according to claim 1, characterized in that: Before the application service provider uploads the data in the form of data blocks to the multiple edge servers, the method further includes: In the case where the edge server is accessible, the application service provider calculates a homomorphic authentication tag for the stored data block.

6. An edge data integrity audit system, characterized in that: Includes application service providers and multiple edge servers, including: The application service providers include: A key generation unit, used for the application service provider to generate a key through a registration machine and construct a pseudo-random function generator; A data uploading unit, used by an application service provider to upload data in the form of data blocks to multiple edge servers; An audit challenge unit, configured for the application service provider to select at least one target edge server from a plurality of edge servers to initiate an audit challenge; The application service provider selects at least one target edge server from a plurality of edge servers to initiate an audit challenge, including: When the application service provider is in a security model where the edge cloud server is untrustworthy and non-colluded, the application service provider selects a challenged data block for each of the target edge servers, and generates a data block index and a secret matrix of the challenged data block using the pseudo-random function generator; and then sends the data block index and the secret matrix as challenge data to the target edge server; When the application service provider is in a security model where the edge cloud server is untrustworthy and colludes, the application service provider selects a challenged data block for each of the target edge servers, and generates a data block index, a coefficient matrix and a secret number of the challenged data block using the pseudo-random function generator; and then sends the data block index and the coefficient matrix as challenge data to the target edge server; An evidence verification unit, used by the application service provider to verify the returned data integrity evidence; Each of the edge servers comprises: The evidence returning unit is used for the target edge server to receive the audit challenge and return corresponding data integrity evidence to the application service provider according to the audit challenge.

7. The edge data integrity audit system according to claim 6, characterized in that: The edge server also includes: The evidence calculation unit is used for the target edge server to obtain the corresponding challenged data block from the stored edge data copy according to the challenge data on the finite domain, and calculate the challenged data block and the challenge data in an agreed paradigm as data integrity evidence and return it to the application service provider.

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