11 results about "Data outsourcing" patented technology

The application discloses a kind of unmanned plane identity anonymization and safe data outsourcing method and system, method is based on integrated supervision platform and unmanned plane, including system initialization stage, integrated supervision platform generates main private key and public parameter;User anonymous and private key generation stage, unmanned plane registers anonymous identity and obtains user private key;Data preprocessing and outsourcing stage, unmanned plane divides data into block and sub-block and encrypts, generates coding vector using erasure code coding, generates verification label for each coding data block, constructs random distribution table according to the number of cloud server, distributes coding vector and label to multiple cloud server storage.In this way, the unmanned plane identity anonymization and safe data outsourcing method described reduces storage redundancy, ensures that data can be reconstructed when multiple servers fail, and guarantees data availability and robust recovery.

The invention belongs to the technical field of electric digital data processing, and particularly relates to a multi-attribute fusion shortest path verifiable query method and device. According to the method, a compact encryption index structure is constructed to support efficient splicing of path segments, a pairing verification mechanism is designed to achieve verifiability of a result, and safe, efficient and credible query of the multi-attribute constraint path is completed on the premise that a graph structure and query intention are not leaked. Through collaborative design of key mechanisms such as structured indexing, fusion encryption, path verification and attribute optimization, the bottleneck of the prior art in terms of query efficiency and verification capability is broken through, personalized path selection and lightweight deployment under multi-attribute constraints are also realized, and the method has wide application prospects and is worthy of popularization and application. The method is suitable for various actual scenes such as cloud data outsourcing, privacy sensitive graph mining and trusted path query.

The application provides a homomorphic encryption-based plaintext data outsourcing encryption system and method. The outsourcing encryption system comprises a data provider and an encryption and decryption platform. The data provider comprises a data storage unit, a random number generation unit, a confusion unit, a data provider side communication unit and a de-confusion unit. The encryption and decryption platform comprises a platform side communication unit and a homomorphic encryption unit. The data storage unit stores plaintext data to be encrypted. The random number generation unit generates random numbers. The confusion unit uses the random numbers to perform confusion processing on the plaintext data to obtain plaintext confusion data. The data provider side communication unit sends the plaintext confusion data to the encryption and decryption platform. The homomorphic encryption unit uses an encryption key to perform homomorphic encryption on the plaintext confusion data to obtain ciphertext confusion data. The platform side communication unit sends the ciphertext confusion data to the data provider. The de-confusion unit uses the random numbers to perform de-confusion processing on the ciphertext confusion data to obtain ciphertext data.

The application discloses a random key encryption deduplication method supporting continuous updating. In order to enable a client to safely outsource private data to a server, the method comprises the following steps: after system parameters are initialized, the client selects a random key to encrypt data and sends the encrypted data to the server. The server checks and deduplicates the data of the user. The server verifies the ownership of the file of each uploader through a challenge-response mechanism to realize effective ownership management control. The application supports the replacement of the file key of the user and can guarantee that all legal users obtain the key updated for multiple times, thereby reducing the risk of private data leakage after the key leakage. Due to the randomness of the key selected by the client, the application can resist the brute force attack introduced by the deterministic convergent encryption. Compared with the encryption deduplication method assisted by a third-party independent server, the method is simpler in deployment. The application can provide data privacy in the field of encryption deduplication.

The invention relates to a multi-attribute secret state data efficient matching and self-adaptive task allocation method and system supporting dynamic updating, and the method comprises the steps: a data outsourcing step: a crowdsourcing platform constructs an index tree fusing multiple attributes of space, time and keywords, encrypts the index tree, and outsources the encrypted index tree to a cloud server; a privacy protection query step: a worker submits an encrypted query token, and the double cloud servers cooperatively traverse the index tree in a ciphertext state by executing a security comparison protocol and a security subset query protocol; and a dynamic updating step, wherein the double cloud servers support operations such as task insertion, task deletion and node splitting on the index tree in a ciphertext state. According to the crowdsourcing task allocation method, comprehensive privacy protection on the task data and the query request is realized in an untrusted cloud environment, meanwhile, efficient multi-attribute joint retrieval and dynamic data updating are supported, and the problems of single privacy protection dimension, low calculation efficiency and insufficient dynamic updating support in an existing crowdsourcing task allocation scheme are effectively solved.

The invention discloses an unmanned aerial vehicle identity anonymization and security data outsourcing method and system, and the method is based on a comprehensive supervision platform and an unmanned aerial vehicle, and comprises the steps: a system initialization stage: the comprehensive supervision platform generates a main private key and public parameters; in a user anonymous and private key generation stage, an unmanned aerial vehicle registers an anonymous identity to obtain a user private key; in the data preprocessing and outsourcing stage, the unmanned aerial vehicle divides data into blocks and sub-blocks, encrypts the blocks and the sub-blocks, encodes the blocks and the sub-blocks by using erasure codes to generate encoding vectors, generates verification labels for each encoding data block, constructs a random distribution table according to the number of the cloud servers, and allocates the encoding vectors and the labels to a plurality of cloud servers for storage. Therefore, through the unmanned aerial vehicle identity anonymization and security data outsourcing method, storage redundancy is reduced, it is ensured that data can be reconstructed when multiple servers fail, and data availability and robust recovery are guaranteed.

This invention belongs to the field of electronic digital data processing technology, specifically relating to a method and apparatus for verifying shortest paths with multi-attribute fusion. The method constructs a compact encrypted index structure to support efficient path segment concatenation and designs a pairing verification mechanism to ensure the verifiability of the results. Without revealing the graph structure or query intent, it achieves secure, efficient, and reliable querying of multi-attribute constrained paths. Through the collaborative design of key mechanisms such as structured indexing, fusion encryption, path verification, and attribute optimization, it not only overcomes the bottlenecks of existing technologies in query efficiency and verification capabilities but also realizes personalized path selection and lightweight deployment under multi-attribute constraints. It has broad application prospects and is suitable for various practical scenarios such as cloud data outsourcing, privacy-sensitive graph mining, and trusted path querying.

The application provides a ciphertext data outsourcing decryption system and method based on homomorphic encryption. The outsourcing decryption system comprises a data application party and a decryption platform. The data application party comprises a data storage unit, a random number generation unit, a confusion unit, a data application side communication unit and a de-confusion unit. The decryption platform comprises a platform side communication unit and a homomorphic decryption unit. The data storage unit stores ciphertext data. The random number generation unit generates random numbers. The confusion unit uses the random numbers to perform confusion processing on the ciphertext data to obtain ciphertext confusion data based on the characteristic that homomorphic encryption can perform plaintext and ciphertext operation. The data application side communication unit sends the ciphertext confusion data to the decryption platform. The homomorphic decryption unit uses a decryption key to perform homomorphic decryption on the ciphertext confusion data to obtain plaintext confusion data. The platform side communication unit sends the plaintext confusion data to the data application party. The de-confusion unit uses the random numbers to perform de-confusion processing on the plaintext confusion data to obtain plaintext data.

The application discloses a database sensitive data sending behavior marking and traceability tracking system and method, and the system comprises six units, i.e., a data feature perception and acquisition unit, a behavior feature extraction unit of an optimized bat algorithm and the like. The data sending parameters are acquired through the data feature perception and acquisition unit, the behavior features are extracted through the optimized bat algorithm, the state transition is analyzed by improving the Markov chain model, the data marking code is generated, the traceability index is constructed, and the tracking feedback is performed. The method comprises six steps, i.e., data acquisition, feature extraction, state analysis, code generation, index construction and tracking feedback. Through the cooperation of the units of the system and the specific method, the application realizes accurate marking and efficient traceability tracking of the database sensitive data sending behavior, and provides a reliable technical means for data security protection.

The application discloses a non-equilibrium privacy set intersection method suitable for an untrusted cloud. A client C has a set X={x1,...,x n}, a server S has a private set Y={y1,...,y N}, and an untrusted cloud server H has no input, wherein n

The application discloses a TEE-assisted safe and efficient distributed high-dimensional data similarity query method, which comprises the following steps: constructing a TEE-assisted safe and efficient distributed high-dimensional data similarity query system and initializing the query system; a data owner constructs the data in a data set into a TPSS form and distributes the data to a first cloud server and a second cloud server; a PB tree is constructed by using the distributed data; when an update data is added or deleted in the data set, the first cloud server, the second cloud server and a trusted execution environment search the PB tree by cooperative operation to add or delete the update data; and according to a similarity query request proposed by a query agent, the first cloud server, the second cloud server and the trusted execution environment provide query services for the query agent. The application can support safe query index construction, efficient similarity query processing and data dynamic updating based on distributed high-dimensional data outsourcing.