ONE-CLASS THREAT DETECTION USING FEDERATED LEARNING

    公开(公告)号:US20250097242A1

    公开(公告)日:2025-03-20

    申请号:US18468213

    申请日:2023-09-15

    Abstract: A machine learning model is trained to classify data as malicious or benign, including receiving the machine learning model in a user device and training the machine learning model on the user device user-generated data that has been classified as known benign. A result of the training is sent to a remote server. Training samples on the user device may be classified automatically, such as classifying sent emails, instant messages, or other content generated by the user as benign.

    SYSTEMS AND METHODS FOR CREDENTIAL-BASED TRANSACTIONS OVER A NETWORK INCORPORATING TRANSACTION CODES

    公开(公告)号:US20250053974A1

    公开(公告)日:2025-02-13

    申请号:US18446068

    申请日:2023-08-08

    Abstract: Systems and methods for transacting over a network is provided. The system includes a first agent and second agent. The first agent is operable to receive from a third agent a transaction code associated with one or more credential types required to apply the transaction code or with one or more credential claim types required to apply the transaction code, transmit the transaction code to the second agent, and receive from the second agent a digitally signed transaction, a first verifiable proof, and the transaction code. The first agent is further operable to transmit to a fourth agent a second verifiable proof based on the first verifiable proof and the transaction code, receive from the fourth agent an unlock signature for a locked credential including one or more credential claims, and transmit the unlock signature to the second agent.

    Data sharing and storage control system and method

    公开(公告)号:US12197605B2

    公开(公告)日:2025-01-14

    申请号:US18314034

    申请日:2023-05-08

    Abstract: A data sharing control method. The method includes detecting a plurality of images on one or more devices operated by a first user, the one or more devices comprising a particular device. A plurality of tags are determined for the plurality of images, and a plurality of settings are received based on the plurality of tags from a second user. A particular image is detected on the particular device. One or more particular tags of the particular image on the particular device are determined, and a sharing action of the particular image by the particular device is blocked based on the plurality of settings and the one or more particular tags.

    MALICIOUS PATTERN MATCHING USING GRAPH NEURAL NETWORKS

    公开(公告)号:US20240354406A1

    公开(公告)日:2024-10-24

    申请号:US18305940

    申请日:2023-04-24

    CPC classification number: G06F21/554 G06N3/08 G06F2221/034

    Abstract: A method of detecting likely malicious activity in a sequence of computer instructions includes identifying a set of behaviors of the computer instructions and representing the identified behaviors as a graph. The graph is provided to a graph neural network that is trained to generate a geometric representation of the sequence of computer instructions, and a degree of relatedness between the geometric representation of the computer instructions and a set of base graphs including base graphs known to be malicious is determined. The sequence of computer instructions is determined to likely be malicious or clean based on a degree of relatedness between the geometric representation of the computer instructions and one or more base graphs known to be malicious.

    Reducing malware signature redundancy

    公开(公告)号:US12032695B2

    公开(公告)日:2024-07-09

    申请号:US17495185

    申请日:2021-10-06

    CPC classification number: G06F21/566 G06F21/554 G06F21/564 G06F21/568

    Abstract: Redundancy in a malware signature list is reduced by processing a plurality of pairs of records in a known malware signature list, where each pair of records comprises a file identifier and an associated malware detection. At least one of the file identifiers and the associated malware detections are mapped to symbols representing the file identifiers and the associated malware detections, the symbols taking less memory than the file identifiers and the associated malware detections. The mapped symbols representing the file identifiers and the associated malware detections are processed to remove at least some malware detections that are not needed to provide a desired degree of representation of each file identifier in the processed known malware signature list, and a processed known malware signature list is stored.

    Network resource privacy negotiation system and method

    公开(公告)号:US11924218B2

    公开(公告)日:2024-03-05

    申请号:US18315905

    申请日:2023-05-11

    CPC classification number: H04L63/102 G06F16/9535 G06F21/6263

    Abstract: A method for accessing a network resource including detecting an attempt by a user via a computing device to access a service enabled by a computing system via a network and transmitting via the network to the computing system a first request to access the service in response to detecting the attempt by the user to access the service, the first request including at least one empty personally identifiable data structure. A failure to access the service responsive to the first request is determined. A second request to access the service in response to the first failure to access the service is transmitted via the network to the computing system, the second request including artificial personally identifiable information, and access to the service from the computing system is received for the user.

    Managing network latency using buffer fill control

    公开(公告)号:US11882049B2

    公开(公告)日:2024-01-23

    申请号:US17370814

    申请日:2021-07-08

    Inventor: Michal Vaner

    CPC classification number: H04L47/30 H04L41/0896 H04L43/0852

    Abstract: A method of managing a fill state of a buffer in an external device includes monitoring the latency of a network connection to an external device having a network buffer via a managing device. A state of fill of the network buffer is determined based on at least the monitored latency of the network connection, and the effective network speed is estimated based on the state of fill of the network buffer. One or more network traffic scheduling parameters are adjusted in response to the estimated effective network speed, such as a maximum currently usable network speed that is lower than a maximum possible speed of the network. The maximum currently usable network speed of the network connection is periodically increased if the monitored latency is in a normal state and the maximum currently usable network speed is lower than the maximum possible speed of the network.

    NETWORK RESOURCE PRIVACY NEGOTIATION SYSTEM AND METHOD

    公开(公告)号:US20230283612A1

    公开(公告)日:2023-09-07

    申请号:US18316023

    申请日:2023-05-11

    CPC classification number: H04L63/102 G06F21/6263 G06F16/9535

    Abstract: A method for accessing a network resource including detecting an attempt by a user via a computing device to access a service enabled by a computing system via a network and transmitting via the network to the computing system a first request to access the service in response to detecting the attempt by the user to access the service, the first request including at least one empty personally identifiable data structure. A failure to access the service responsive to the first request is determined. A second request to access the service in response to the first failure to access the service is transmitted via the network to the computing system, the second request including artificial personally identifiable information, and access to the service from the computing system is received for the user.

Patent Agency Ranking