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    METHOD OF HYBRID SEARCHABLE ENCRYPTION AND SYSTEM USING THE SAME
    31.
    发明申请
    METHOD OF HYBRID SEARCHABLE ENCRYPTION AND SYSTEM USING THE SAME 审中-公开

    公开(公告)号：US20190229906A1

    公开(公告)日：2019-07-25

    申请号：US16207927

    申请日：2018-12-03

    Applicant: Huazhong University of Science and Technology

    Inventor： Hai JIN ,  Peng Xu ,  Tianyang Chen ,  Ye Tao

    IPC: H04L9/08 ,  H04L9/30 ,  H04L9/14

    Abstract: The present invention involves with a method of hybrid searchable encryption, involving using at least one first computing device that has a first processor configured to perform steps of: using a first symmetric key to encrypt data so as to obtain a data first ciphertext, using a second symmetric key to encrypt a keyword related to the data so as to obtain a searchable keyword first ciphertext that is related to the data first ciphertext, and saving the data first ciphertext and the keyword first ciphertext in a first memory of a first computing device; and using the first symmetric key to encrypt the keyword so as to generate a keyword second ciphertext, using a first public key to encrypt the keyword so as to obtain a searchable third keyword ciphertext related to the keyword second ciphertext, and sending the keyword second ciphertext and the searchable third keyword ciphertext to a second computing device; wherein the second computing device has a second processor that is configured to perform steps of: receiving the keyword second ciphertext and the searchable third keyword ciphertext from the first computing device and saving the two together with an identification of the first computing device relationally in a second memory of the second computing device.

    METHOD AND SYSTEM FOR AUTOMATIC DELETION OF INFORMATION BASED ON TIME SYNCHRONIZATION AND TRUSTED COUNTING
    32.
    发明公开
    METHOD AND SYSTEM FOR AUTOMATIC DELETION OF INFORMATION BASED ON TIME SYNCHRONIZATION AND TRUSTED COUNTING 审中-公开

    公开(公告)号：US20240362251A1

    公开(公告)日：2024-10-31

    申请号：US18631790

    申请日：2024-04-10

    Applicant: Huazhong University of Science and Technology

    Inventor： Peng XU ,  Yinjia PI ,  Wei WANG ,  Shuning XU ,  Yubo ZHENG ,  Hai JIN

    IPC: G06F16/27

    CPC classification number: G06F16/27

    Abstract: A method and system for automatic deletion of information based on time synchronization and trusted counting is provided, the method including: defining different data structures including configurations in a normalized manner; setting triggering conditions for automatic information deletion, including conditions for automatic deletion based on time synchronization and/or based on trusted counting; maintaining synchrony of the configurations across different domains; and after satisfying the triggering conditions, making an information source domain and/or an information propagation domain perform the automatic information deletion. Considering that existing data deletion mechanisms cannot delete information according to preset retention periods, the present application employs synchrony across system clocks to perform automatic deletion of authorization information under circulation after a certain time period, and further limits a circulation count for information of interest so as to ensure that the information and its copies are all deleted after reaching a preset maximum permittable circulation count.

    KNOWLEDGE-GRAPH EXTRAPOLATING METHOD AND SYSTEM BASED ON MULTI-LAYER PERCEPTION
    33.
    发明公开
    KNOWLEDGE-GRAPH EXTRAPOLATING METHOD AND SYSTEM BASED ON MULTI-LAYER PERCEPTION 审中-公开

    公开(公告)号：US20240086731A1

    公开(公告)日：2024-03-14

    申请号：US18154637

    申请日：2023-01-13

    Applicant: Huazhong University of Science and Technology

    Inventor： Feng ZHAO ,  Mingtao CHEN ,  Kangzheng LIU ,  Hai JIN

    IPC: G06N5/022

    CPC classification number: G06N5/022

    Abstract: The present invention relates to a knowledge-graph extrapolating method and system based on multi-layer perception, the method comprising: using relational graph convolutional network encoders to learn embedding representations, and capturing dynamic evolution of a fact; designing emerging task processing units to construct multiple layers of entity sets, and assigning a matching historical relevance; classifying prediction tasks into different reasoning scenes, and connecting them to the corresponding processing unit for partition of entity sets; and using a multi-class task solving method to acquire predicted probability distributions of target entities, and taking the highest one as a prediction answer, so as to accomplish extrapolation of a temporal knowledge graph, wherein the prediction tasks are classified into different reasoning scenes according to whether it contains any entity or relation that has never appeared historically. The knowledge-graph extrapolating system comprises a processor that can run program code information of the disclosed method.

    RELATION EXTRACTION SYSTEM AND METHOD ADAPTED TO FINANCIAL ENTITIES AND FUSED WITH PRIOR KNOWLEDGE
    34.
    发明公开
    RELATION EXTRACTION SYSTEM AND METHOD ADAPTED TO FINANCIAL ENTITIES AND FUSED WITH PRIOR KNOWLEDGE 审中-公开

    公开(公告)号：US20240086650A1

    公开(公告)日：2024-03-14

    申请号：US18217207

    申请日：2023-06-30

    Applicant: Huazhong University Of Science And Technology

    Inventor： Xuanhua SHI ,  Yao WAN ,  Teng ZHANG ,  Hai JIN ,  Nan CAO ,  Mengfan LI

    IPC: G06F40/53 ,  G06F40/295 ,  G06F40/30

    CPC classification number: G06F40/53 ,  G06F40/295 ,  G06F40/30

    Abstract: The present invention relates to a relation extraction system adapted to financial entities and fused with prior knowledge and a method thereof, the system at least comprising: a deep pretraining module, for training and generating a deep pretrained model for recognizing attributes of the financial entities; a keyword analyzing module, for extracting and outputting positional information and importance vectors of keywords in a Chinese finance-related text; an attention mechanism module, for encoding the positional information of the keywords to obtain attention masks, and inputting them with entity information into the deep pretrained model to acquire text feature vectors; and an optimal margin distribution model module, for predicting financial-entity relations based on the text feature vectors and the importance vectors. Aiming at low applicability of existing models to specific Chinese fields, the present invention obtains more accurate extraction results of entities and related features in Chinese finance-related texts.

    GRAPHIC-BLOCKCHAIN-ORIENTATED HYBRID CONSENSUS IMPLEMENTATION APPARATUS AND IMPLEMENTATION METHOD THEREOF
    35.
    发明申请
    GRAPHIC-BLOCKCHAIN-ORIENTATED HYBRID CONSENSUS IMPLEMENTATION APPARATUS AND IMPLEMENTATION METHOD THEREOF 有权

    公开(公告)号：US20230017790A1

    公开(公告)日：2023-01-19

    申请号：US17806668

    申请日：2022-06-13

    Applicant: Huazhong University of Science and Technology

    Inventor： Jiang XIAO ,  Shuohua DONG ,  Jingtao YUE ,  Xiaohai DAI ,  Jian CHANG ,  Shijie ZHANG ,  Hai JIN

    IPC: G06F16/23 ,  G06F16/27

    Abstract: The present invention relates to an implementation method for graphic-blockchain-orientated hybrid consensus, at least comprising: calling at least one module to generate a new data block and broadcast it; calling at least one module to check and validate the received new block based on predetermined rules; calling at least one module to generate a void block; and calling at least one module to update a committee member list. The existing graphic blockchain can only achieve probabilistic consensus, yet the present invention achieves deterministic consensus on graphic blockchain for the first time, thereby reaching consensus faster. The present invention decouples generation and consensus of blocks for the first time, so that the two parts can be designed separately in a modularized manner. The present invention provides the first totally decentralized hybrid consensus algorithm in the graphic blockchain. This is unachievable to many existing graphic blockchain such as IOTA and Obyte.

    LIGHTWEIGHT DATA STORAGE APPARATUS FOR GRAPHIC BLOCKCHAIN AND METHOD THEREOF
    36.
    发明申请
    LIGHTWEIGHT DATA STORAGE APPARATUS FOR GRAPHIC BLOCKCHAIN AND METHOD THEREOF 有权

    公开(公告)号：US20230015556A1

    公开(公告)日：2023-01-19

    申请号：US17664750

    申请日：2022-05-24

    Applicant: Huazhong University of Science and Technology

    Inventor： Jiang XIAO ,  Xiaohai DAI ,  Shijie ZHANG ,  Hai JIN

    IPC: H04L9/00 ,  H04L9/40 ,  G06Q20/38

    Abstract: The present invention relates to a lightweight data storage apparatus for graphic blockchains, at least comprising a common transaction construction module for a user to initiate new transactions and a network broadcast module for broadcasting the transactions, wherein the apparatus further comprises a combined-transaction constructing module and a transaction deleting module, wherein the combined-transaction constructing module serves to determine whether number of transactions initiated by an account satisfies a first predetermined condition, and if yes, execute a first lightening procedure on the transactions, and the transaction deleting module serves to execute a second lightening procedure on the transactions that have been processed by the first lightening procedure and now have validation references satisfying a second predetermined condition, after which the network broadcast module broadcasts the transactions obtained after the second lightening procedure. With the disclosed transaction-combining and reference-transaction-deleting scheme, data storage overheads of a graphic blockchain can be reduced.

    METHOD OF TIME-DELAY ENCRYPTION WITH KEYWORD SEARCH AND SYSTEM USING THE SAME
    37.
    发明申请
    METHOD OF TIME-DELAY ENCRYPTION WITH KEYWORD SEARCH AND SYSTEM USING THE SAME 有权

    公开(公告)号：US20220255744A1

    公开(公告)日：2022-08-11

    申请号：US17444613

    申请日：2021-08-06

    Applicant: Huazhong University of Science and Technology

    Inventor： Peng XU ,  Yubo ZHENG ,  Tianyang CHEN ,  Hai JIN ,  Wei WANG

    IPC: H04L9/30 ,  H04L9/06 ,  G06F16/903

    Abstract: The present invention relates to a method of time-delay encryption with keyword search and system using the same, at least comprising: based on a public key PK, generating searchable ciphertexts Cw and/or file ciphertexts for keywords w of at least one to-be-uploaded file by means of time-delay encryption and uploading the ciphertexts to a cloud server; sending at least one keyword search trapdoor Tw generated for one said to-be-searched keyword w based on a private key SK to the cloud server; and the cloud server, based on the keyword search trapdoor Tw performing keyword search on all the searchable ciphertexts Cw so as to obtain the corresponding searchable ciphertexts Cw, and determining the corresponding file ciphertexts based on the searched searchable ciphertexts Cw and feeding the corresponding file ciphertexts to a receiving end. The present invention increases the difficulty for attackers to launch keyword guessing attacks.

    TENSOR-BASED OPTIMIZATION METHOD FOR MEMORY MANAGEMENT OF A DEEP-LEARNING GPU AND SYSTEM THEREOF
    39.
    发明申请
    TENSOR-BASED OPTIMIZATION METHOD FOR MEMORY MANAGEMENT OF A DEEP-LEARNING GPU AND SYSTEM THEREOF 有权

    公开(公告)号：US20210142178A1

    公开(公告)日：2021-05-13

    申请号：US16946690

    申请日：2020-07-01

    Applicant: Huazhong University of Science and Technology

    Inventor： Xuanhua SHI ,  Xuan PENG ,  Hai JIN ,  Hulin DAI ,  Weiliang MA ,  Qian XIONG

    IPC: G06N3/08 ,  G06N3/063 ,  G06N5/04 ,  G06F12/02 ,  G06F12/0806 ,  G06T1/60

    Abstract: The present disclosure relates to a tensor-based optimization method for GPU memory management of deep learning, at least comprising steps of: executing at least one computing operation, which gets tensors as input and generates tensors as output; when one said computing operation is executed, tracking access information of the tensors, and setting up a memory management optimization decision based on the access information, during a first iteration of training, performing memory swapping operations passively between a CPU memory and a GPU memory so as to obtain the access information about the tensors regarding a complete iteration; according to the obtained access information about the tensors regarding the complete iteration, setting up a memory management optimization decision; and in a successive iteration, dynamically adjusting the set optimization decision of memory management according to operational feedbacks.

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