57 results about "Data outsourcing" patented technology

The invention discloses a safe data-outsourcing machine learning and data analysis method. A random tree is transformed in a homoenergetic mode into properties of a binary tree; a trained decision tree prediction model is transformed into the binary tree, the binary tree is induced into a special polynomial of which a shape is a sum of an infinite number of multiplier items, and each piece of data in the model is encrypted by an RSA and is uploaded to a cloud platform; then data which needs to be decided is also encrypted by the RSA and is uploaded to the cloud platform; the encrypted data of the model and the encrypted data which needs to be decided are correspondingly computed by utilizing the multiplication homomorphic encryption property of the RSA to obtain a ciphertext result of each multiplier item; and the results are returned to a data user for decryption so as to obtain a decision result. By transforming the binary tree into the polynomial, a decision tree which originally can be implemented by various computations is transformed into the decision tree which can be implemented by one computation, so that the machine learning process of the decision tree can be rapidly completed by using a multiplication homomorphic algorithm, a complex degree of carrying out such decision tree machine learning algorithm on a ciphertext is greatly reduced, and computing efficiency is promoted.

The invention belongs to the field of machine learning and privacy protection, and particularly relates to a decision tree classification service system and method supporting privacy protection. The service system comprises a model owner module, a client module, a cloud service module and a ciphertext operation module. The method comprises a preparation stage and a classification stage. The invention provides a decision tree classifier supporting privacy protection orienting cloud encryption data, and designs and implements a decision tree classification service system supporting privacy protection. Original data cannot be recovered through encrypted data uploaded by a user, privacy protection in the outsourcing calculation process is guaranteed, large-scale data are outsourced to a third-party server which is high in storage and calculation resource, local infrastructure investment and management of the user are reduced, and then more economic benefits are generated.

The present invention belongs to the cloud data technology field, and discloses a system and method for high-efficiency data integrity auditing supporting safety duplication eliminating in a cloud environment. A data owner module is configured to store local data after safety duplication eliminating on cloud, submit a data management task to a cloud service provider module and submit a data auditing task to a third-party audit module; the cloud service provider module is configured to provide data outsourcing storage and integrity auditing service to take the user' place to perform data storage and management; the third-party audit module is configured to replace the data owner module to provide the data integrity auditing service and return back an auditing result; and a certificate authority module is configured to generate a data owner module anonymous public key certificate, track the real identities of malicious users and generate public parameters and label aggregation secret keys. The safety duplication eliminating and high-efficiency data integrity auditing are realized so as to reach the expected safety target and improve the efficiency of the integrity auditing.

The invention discloses a cloud storage service-oriented dynamic data integrity auditing program, and aims to overcome the deficiency of an existing data integrity examination program of the cloud storage service in supporting the user dynamic operation. The cloud storage service-oriented dynamic data integrity auditing program includes a key generation phase in which a user generates a pair of public and private keys and transmits the public key to a cloud service supplier and an auditor; a data outsourcing phase in which the user transmits data blocks and labels to the cloud service supplier, and the cloud service supplier verifies the correctness of the labels; a cloud data integrity auditing phase in which the auditor transmits an audit request to the cloud service supplier, and a cloud server computes an evidence and returns the evidence to the auditor, and finally the auditor verifies the correctness of the evidence; and a cloud data dynamic updating phase in which the user transmits the data blocks and the labels to the cloud service supplier, and the cloud service supplier performs update operation and informs the user of an updated result. The cloud storage service-oriented dynamic data integrity auditing program can not only effectively satisfy a safety requirement of the data integrity auditing program of the cloud storage service but also effectively support dynamic operations of users.

The invention discloses a Merkle tree structure-based space inquiring integrity verification method. Based on an existing quadtree node generated by a self-adaption Hilbert curve, a Merkle tree structural construction method for supporting the inquiring integrity verification is provided, and an integrity verification method for range inquiring and KNN inquiring is provided, so that an integrity verification result provided by the Merkle tree structure-based space inquiring integrity verification method is free of phenomena of the misinformation and the false-information, and malevolence changing is difficult to carried out on a user inquired result by a service supplier. Under the mode of space data outsourcing service, the method can provide an efficient verification structural generating function, accurate range inquiring and a KNN inquiring integrity verification function for a user, and therefore the quality of space inquiring service can be guaranteed.

The invention discloses a decentralized collaborative verification model and verification algorithm. The model comprises four key components: a data owner, a cloud service provider, a collaboration network and a blockchain, wherein the block storage of the blockchain is composed of a POR Merkle tree generated by a POR record, a leaf node of the POR Merkle tree consists of a two-tuples, and the two-tuples records the POR record and a digital signature of the data owner. The decentralized collaborative verification model disclosed by the invention brings the characteristics of the blockchain into the process of outsourcing data storage and verification in an untrusted environment, so that the data security can be improved, the security problem that may be caused by handing over a data verification process to a third party in the traditional data outsourcing service is avoided, the efficiency is improved, and the security is improved.

The present invention discloses a multiple users-based outsourcing database audit method, aiming to solve problems of low signature verification efficiency and complex decryption in the prior art. The method comprises a first step that a data owner encrypts data by using a proxy re-encryption method so as to form a second-level ciphertext, generates a re-encryption secret key by inquiring a public key of a user, generates a searching label by using an Evdokimov encryption manner, and generates hash tree root signature by using aggregate signature; and the signature, second-level ciphertext, re-encryption secret key and the searching label are transmitted to a cloud server; a second step that the cloud server encrypts the second-level ciphertext so as to generate a first-level ciphertext; a third step that a user sends a search request to the cloud server, and the cloud server searches and returns a corresponding first-level ciphertext; and a fourth step that the user decrypts the first-level ciphertext so as to form a plaintext, and performs aggregate verification on the plaintext. Through adoption of the method, the burden on the data owner is greatly reduced, interaction is reduced for one time, data privacy protection is improved, and the method can be applied to safe data outsourcing in a cloud calculation environment.

The invention discloses a publicly verifiable outsourcing statistical method. Three entities of a data owner, an outsourcing server and a requester are included, first the data owner uploads data to the outsourcing server, then the outsourcing server conducts statistical operation on the data according to the need of the requester, finally the requester detects and verifies effectiveness of the statistical result. By means of the method, the requester can conducts various statistical operations on data under the condition that massive data are not downloaded locally, and the method has good safety, effectiveness, function independence and variability. On one hand, the requester can verify correctness of response returned by the outsourcing server, the expenses of calculation and communication are irrelevant with the amount of data input by verification, and the algorithm time complexity is maintained in the O (1) range; on the other hand, the data owner can conduct data outsourcing under the condition that the function details to be calculated are not required to be understood. In addition, statistical operation can be conducted on the whole both on the whole and partially through the function.

The invention discloses a data structure construction and matching method for secure character string pattern matching. The method comprises a construction method of a data structure S2PASTree and a method for carrying out character string mode matching based on the data structure. The data structure comprises a group of keywords, so that a program applying the data structure can quickly respond to a character string mode matching query requirement supporting privacy protection, and the memory resource expenditure of a service provider and an authorized user is reduced. Based on the construction method, aiming at cloud computing and data outsourcing situations, a service provider can quickly respond to the requirements of an authorized client for security character string mode matching query on the premise of protecting the privacy security of original data, query conditions and query results. Based on the matching method, compared with a common character string mode matching query method, the query speed is higher, the communication overhead is lower, and the query processing efficiency and the service quality of a service provider are improved.

The invention discloses a fully homomorphic data packaging method for lightweight single-user multi-data, which is characterized by comprising the following five stages of system initialization, key generation, data encryption, encryption data outsourcing calculation and decryption. Compared with the prior art, the method is simple and easy to implement, the efficiency is high, and efficient privacy protection outsourcing calculation is realized in a scene of a single user and a plurality of input data; according to the method, a cloud server and an unauthorized receiver are combined, additionand multiplication operations on a ciphertext domain are supported at the same time, input privacy can achieve unconditional security (information theory security) under collusion attacks of the cloud server and the unauthorized receiver, calculation result privacy can achieve adaptive ciphertext security selection (CCA2 security) for the unauthorized receiver, and the requirements for high efficiency and privacy are met.

The invention provides a privacy-protecting outsourcing data and backup integrity checking method based on a blockchain for an Internet-of-things scene by utilizing the characteristics of openness, tamper resistance and the like of the blockchain and combining related knowledge of smart contracts and cryptography. Compared with an existing data outsourcing and outsourcing data integrity checking process, the method solves the problem that the expenditure of self-verification data of a user is too large, or outsourcing depends on a trusted third party; in addition, the invention provides a newcontribution degree measurement standard and a reward distribution mechanism, so that each participant can obtain corresponding incentives.

The invention discloses a data structure. The data structure comprises a property dimension set. Through the data structure, a readable storage medium storing a data structure program can respond to multi-user space query, a multi-dimension query request is processed quickly and efficiently, the extendibility of the readable storage medium is enhanced, and memory resource expenditure is reduced for a service provider and users. The invention furthermore discloses a method for processing an external multi-user query request based on the data structure. Through the method, diversified query demands of a large number of users can be correctly reflected, the blank of multi-user space query processing in a data outsourcing scene is filled up, and the query processing efficiency and service quality of the service provider are improved. The invention furthermore discloses a verification method. Through the verification method, the authenticity, correctness and integrity of multi-user space query can be verified at the same time, and the reliability of data, used by the users, of the service provider is ensured. In the data outsourcing scene, the invention furthermore provides a multi-user space query verification method according to user preferences, an application device and a query verification system.

The invention provides a cloud data outsourcing and integrity verification method supporting preprocessing, which comprises the following steps that: a data outsourcer selects a security parameter andan anti-collision hash function to generate a public key and a private key; The data outsourcer executes a first pre-calculation process according to the public key to generate offline data processing parameters; The data outsourcer executes a data processing process according to the private key and the offline data processing parameters, generates processed data and data labels and uploads the processed data and data labels to the cloud storage server; The data verifier executes a second pre-calculation process according to the public key and the data label to generate an offline data verification parameter; The data verifier verifies the data label of the outsourced data according to the public key of the data outsourcer and the offline data verification parameter, and generates a challenge if the data label of the outsourced data is legal; The cloud storage server responds to the received challenge calculation according to the stored outsourcing data; And the data verifier verifiesthe received response according to the public key and the offline data verification parameters so as to judge the integrity of the corresponding outsourcing data.

The invention discloses a data monitoring method, a data monitoring system, data monitoring equipment based on virtualization technology, and storage medium. The data monitoring method comprises stepsthat a digital asset distribution condition of a virtualization platform is identified; according to the digital asset distribution condition, to-be-emphasized risk data and risk users on the virtualization platform are determined; according to different risk degrees, corresponding data outsourcing authorities are set for different risk users. By using the identified digital asset distribution condition of the virtualization platform, the to-be-emphasized risk data and the corresponding risk users on the virtualization platform are determined, and based on the different risk degrees, the corresponding data outsourcing authorities are set for the different users, and then the risk users are prevented from having unmatched data outsourcing authorities, and therefore data safety performanceis improved, and data leakage conditions are reduced.

The invention relates to a hierarchical security multi-party computing method and device based on the Chinese remainder theorem, and the method comprises the steps: enabling a computing task to be divided into an outer package subtask and an autonomous subtask through a computing father node, and distributing a writing subkey and a reading subkey for each outer package subtask; sending each outer packet sub-task and the corresponding write-in sub-key to each computing sub-node in a safe mode; enabling the computing father node and the computing child nodes to obtain data of respective child tasks through computing, and storing outsourcing computing data in a public result ciphertext through writing of child keys and sharing and transmitting the outsourcing computing data in the public result ciphertext; enabling the computing father node to obtain outsourcing computing data calculated by each computing child node from the public result ciphertext by reading the child key, and calculating a final result of the calculation task. According to the method, the computing sub-nodes can assist each other to complete the computing task together, but the computing data of other computing sub-nodes and the final computing data of the computing task cannot be obtained, so that secure multi-party computing is realized.

The invention provides a circular range query method and system in a cloud environment based on position privacy protection. The method and the system belong to the technical field of location privacyprotection. The method comprises the steps of converting a relational expression between the spatial data point and a circular range which takes the query position as a circle center and r as a radius into an inner product of two vector sums, and judging a relationship between the inner product and zero by utilizing SSW confidentiality, so as to determine the relationship between the spatial datapoint and the circular range under the condition of not leaking the spatial data point and the query position; meanwhile, a Hilbert curve is used for dividing a region into atomic regions, and a spatial data set is stored and managed according to the atomic regions, so that the query efficiency is improved; the circular range query can be realized while the query privacy of the position query terminal and the data privacy of the position server are protected, and the potential safety hazard caused by spatial data outsourcing is solved.

The invention requests to protect a data outsourcing privacy protection method and system and a storage medium, and the method comprises the following steps: in a system initialization stage, a location-based service provider (LBSP) generates a system public parameter and a secret key, and then a new user registers to the LBSP to obtain the secret key to inquire a trap door structure and decrypt data; in the data encryption stage, the LBSP encrypts a location based service (LBS) data set, the LBS data confidentiality is achieved, and ciphertext data is uploaded to a cloud server. In order to protect personal privacy, a user encrypts a query request of the user and sends the query request to a cloud server for query; the cloud server performs matching calculation after receiving the LBS ciphertext data set and the query trap door, and returns ciphertext data conforming to query to the user; and finally, the user decrypts the ciphertext data to obtain actual data. According to the invention, the requirements of user interval query and privacy protection can be well met, the query efficiency is greatly improved, and the query communication overhead is remarkably reduced.

The invention relates to a query integrity verification system and method for outsourcing streaming data. The system comprises an initialization module, a data management module and a query verification module. The initialization module is used to generate the public and private keys and other parameters needed by the data owner when the system starts, and distributes the public keys to the serverand the data user. The data management module is used for the data owner to outsource the real-time streaming data to the server. When the data stored before the server needs to be changed, the update data sub-module is used to update the data and the corresponding evidence. The user data user of the query verification module will query the data stored in the server, and will get the data of thecorresponding query index returned by the server and the corresponding evidence, and use the evidence returned by the server to verify whether the query result is correct.

The invention discloses a service provider reputation-based query verification method for a data outsourcing scene. The method comprises the steps of weighing a possibility of returning a false result by a service provider by using a reputation value through a probability-based query verification policy in a query service of the data outsourcing scene; selectively requiring the service provider to return a verifiable object (VO) according to the reputation value; and verifying the authenticity, correctness and integrity of a query result by using the VO. According to the method, the communication and calculation overheads between the service provider and a user can be remarkably reduced; the efficiency of a query process is improved; and the query result is ensured to be real and reliable with high probability.

The invention discloses an outsourcing data access control system based on a block chain, and belongs to the technical field of block chains. The system comprises a user side, a cloud server and a block chain network, the user side is accessed to the cloud server and the block chain network, data interaction can be performed between the cloud server and the block chain network, and a user corresponding to the user side is a data stakeholder, comprising a data owner and a data user requesting data and operating the data, and is an entity authorized by the data owner to use the data; the cloud server is a storage end for a data owner to upload data, namely a platform for data outsourcing storage, and the data user accesses the data through the cloud server; a block chain network records logs of data access and operation of a data owner and a data user, and the security and reliability of outsourcing data access platform data are provided.

The invention discloses a multivariate identity authentication method and system for power grid data outsourcing calculation, and the method comprises the steps: collecting various biological information of a user at the same time through a biological information collection device, transmitting the biological information to an identity authentication server, and carrying out the identity authentication of the user through the identity authentication server; enabling a calculation entrusting party and a calculation party of the power grid data to generate a session key in a mode of continuously exchanging intermediate values through a PAKE protocol, and encrypting and decrypting transmission data by using the session key to complete identity authentication between the calculation entrusting party and the calculation party; performing authentication verification on the power grid data needing to be subjected to outsourcing calculation, and performing authentication verification on a calculation result by a calculation entrusting party when a calculation party returns the calculation result; and enabling the encryption machine to write the IP address of the privacy computing server into the IP white list, and completing authentication of the privacy computing server. The method is compatible with various authentication requirements of personnel, equipment, systems, data and the like, and ensures the safety of power consumption data outsourcing calculation.