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公开(公告)号：US20240364502A1
公开(公告)日：2024-10-31
申请号：US18631621
申请日：2024-04-10
Inventor： Peng XU , Mengyang YU , Wei WANG , Yixin SU , Yubo ZHENG , Hai JIN
CPC classification number: H04L9/0819 , H04L9/0869 , H04L9/3236
Abstract: A method and system for encryption and assured deletion of information is provided, the method at least includes: sorting fields of the information into at least two sensitivity levels by sensitivity; generating encryption keys and key shards thereof based on predetermined thresholds, and creating mapping between targets and the key shards, based on the encryption keys for the sensitivity levels, encrypting the information fields of the corresponding sensitivity levels and deleting the original information and encryption keys; and in response to reception of a recover request, recovering the encryption keys based on the key shards and performing decryption, so as to recover the original information. The present disclosure aims at the problem that information is difficult to be safely stored and assuredly deleted, and realizes multi-party security key deletion of encrypted personal information.
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2.发明公开公开(公告)号：US20240362187A1
公开(公告)日：2024-10-31
申请号：US18631660
申请日：2024-04-10
Inventor： Peng XU , Shuning XU , Wei WANG , Runze XU , Tingting RAO , Hai JIN
CPC classification number: G06F16/162 , G06F21/60 , G06F2221/2143
Abstract: A method and system for overwriting-based deletion of information and verification of deletion is provided, wherein the method at least includes: receiving a deletion request and/or a random seed; performing fine-grained overwriting on the information by means of random overwriting; in response to an extraction request for a post-deletion state, making a master node in a source domain of the information broadcast the extraction request to at least one slave node; and sending the post-deletion state fed back by the slave node and a related state-verification parameter to a verifying terminal, so that the verifying terminal verifies an overwriting result based on a verifiable pseudo-random function. Thus, the present application can effectively prevent information recovery after being logically deleted, and efficaciously ensure verifiability as well as non-recoverability of deleted information, thereby assuring non-recoverable deletion and providing verifiability of deletion to information subjects.
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3.发明公开公开(公告)号：US20240192929A1
公开(公告)日：2024-06-13
申请号：US18475447
申请日：2023-09-27
Inventor： Zhen LI , Ruqian ZHANG , Deqing ZOU , Hai JIN , Yangrui LI
Abstract: A sample-difference-based method and system for interpreting a deep-learning model for code classification is provided, wherein the method includes a step of off-line training an interpreter: constructing code transformation for every code sample in a training set to generate difference samples; generating difference samples respectively through feature deletion and code snippets extraction and then calculating feature importance scores accordingly; and inputting the original code samples, the difference samples and the feature importance scores into a neural network to get a trained interpreter; and a step of on-line interpreting the code samples: using the trained interpreter to extract important features from the snippets, then using an influence-function-based method to identify training samples that are most contributive to prediction, comparing the obtained important features and the most contributive training samples, and generating interpretation results for the object samples. The inventive system includes an off-line training module and an on-line interpretation module.
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公开(公告)号：US20220255739A1
公开(公告)日：2022-08-11
申请号：US17444224
申请日：2021-08-02
Inventor： Peng XU , Tianyang CHEN , Yubo ZHENG , Hai JIN , Wei WANG
Abstract: The present invention relates a method for ensuring search completeness of searchable public key encryption, applicable to a blockchain network formed by a plurality of computer nodes. The method at least comprises: the blockchain network receiving a keyword ciphertext and a corresponding file-identifier ciphertext generated by a transmitting end based on the public key encryption, and at least one miner storing the ciphertexts in a ciphertext table; the blockchain network receiving a search trapdoor Tw transmitted by a receiving end, generated according to a private key and a keyword w to be searched; the at least one miner in the blockchain network performing a secure search based on information of a state table and the search trapdoor Tw, and outputting a search result to the blockchain network; and the blockchain network feeding the search result back to the receiving end. The invention uses the blockchain technology to solve the long-standing search completeness problem in searchable public key encryption, and the proposed method has universality.
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公开(公告)号：US20210250299A1
公开(公告)日：2021-08-12
申请号：US17248519
申请日：2021-01-28
Inventor： Fangming LIU , Hai JIN , Miao LI
IPC: H04L12/851 , H04L12/803 , G06F16/22 , H04L12/24
Abstract: The present invention relates to a container-based network function virtualization (NFV) platform, comprising at least one master node and at least one slave node, the master node is configured to, based on interference awareness, assign container-based network functions (NFs) in a master-slave-model-based, distributed computing system that has at least two slave nodes to each said slave node in a manner that relations among characteristics of the to-be-assigned NFs, info of load flows of the to-be-assigned NFs, communication overheads between the individual slave nodes, processing performance inside individual slave nodes, and load statuses inside individual said slave nodes are measured.
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Patent Agency Ranking
公开(公告)号：US20210081347A1
公开(公告)日：2021-03-18
申请号：US16896464
申请日：2020-06-09
Inventor： Xiaofei LIAO , Fan ZHANG , Long ZHENG , Hai JIN , Zhiyuan SHAO
Abstract: A graph processing optimization method that addresses the problems such as the low computation-to-communication ratio in graph environments, and high communication overhead as well as load imbalance in heterogeneous environments for graph processing. The method reduces communication overhead between accelerators by optimizing graph partitioning so as to improve system scalability.
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公开(公告)号：US20230092214A1
公开(公告)日：2023-03-23
申请号：US17661991
申请日：2022-05-04
Inventor： Song WU , Hang HUANG , Kun WANG , Honglei WANG , Hai JIN
Abstract: The present invention relates to a container-oriented Linux kernel virtualizing system, at least comprising: a virtual kernel constructing module, being configured to provide a virtual kernel customization template for a user to edit and customize a virtual kernel of a container, and generate the virtual kernel taking a form of a loadable kernel module based on the edited virtual kernel customization template; and a virtual kernel instance module, being configured to reconstruct and isolate a Linux kernel, and operate a virtual kernel instance in a separate address space in response to a kernel request from a corresponding container. The container-oriented Linux kernel virtualizing system of the present invention is based on the use of a loadable module.
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公开(公告)号：US20230085807A1
公开(公告)日：2023-03-23
申请号：US17664767
申请日：2022-05-24
Inventor： Weiqi DAI , Jinkai LIU , Hai JIN , Deqing ZOU
Abstract: The present invention provides an anti-trapdoor-leakage on-chain data restoration system, at least comprising: a blockchain node, for broadcasting transaction data of a request-initiating person to blockchain nodes and proposer nodes in other groups, respectively; and a proposer node, for performing computation of a Chameleon-Hash function using a key set that is generated by a key-generating module provided in the proposer node, packaging the transaction data to generate a new block, and distributing the new block to all the blockchain nodes so that the blockchain nodes update their respective underlying ledgers according to the new blocks broadcasted by the proposer. The system of the present invention not only realizes such functions as restoration and editing of the transaction data, but also protects operational security and reliability of blockchains.
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公开(公告)号：US20220309080A1
公开(公告)日：2022-09-29
申请号：US17455502
申请日：2021-11-18
Inventor： Jiang XIAO , Jian CHANG , Rui HAN , Xiaohai DAI , Hai JIN
IPC: G06F16/28 , G06F16/2457 , G06F16/248 , G06Q20/38
Abstract: The present invention relates a method for high-performance traceability query oriented to multi-chain data association, comprising: identifying a target transaction needing the traceability query; searching out all corresponding target chains based on cross-chain transaction data association; making query requests parallelly; and executing the query among the target chains according to a key value of the target transaction and returning query results. The blockchain traceability query method proposed by the present invention is different from serialized block data query conducted in the chain-type structure, and the disclosed cross-chain query operation can be parallelly executed, leading to improved efficiency of traceability query. Opposite to the conventional blockchain where blocks are used as nodes of chains, the present invention directly uses sub blockchains as nodes of the SRB. Since sub blockchains can be dynamically added or removed, the present invention enhances the scalability of the entire system.
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公开(公告)号：US20220147836A1
公开(公告)日：2022-05-12
申请号：US17169869
申请日：2021-02-08
Inventor： Feng ZHAO , Tao XU , Langjunqing JIN , Hai JIN
IPC: G06N5/02 , G06F40/295 , G06N3/08 , G06N3/04 , G06F40/30
Abstract: The present invention relates to method and device for text-enhanced knowledge graph joint representation learning, the method at least comprises: learning a structure vector representation based on entity objects and their relation linking in a knowledge graph and forming structure representation vectors; discriminating credibility of reliable feature information and building an attention mechanism model, aggregating vectors of different sentences and obtain association-discriminated text representation vectors; and building a joint representation learning model, and using a dynamic parameter-generating strategy to perform joint learning for the text representation vectors and the structure representation vectors based on the joint representation learning model. The present invention selective enhances entity/relation vectors based on significance of associated texts, so as to provide improved semantic expressiveness, and uses 2D convolution operations to train joint representation vectors. As compared to traditional translation models, the disclosed model has better performance in tasks like link prediction and triad classification.
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