INSTRUMENTING OBSERVABILITY CONTROLS
    1.
    发明公开

    公开(公告)号:US20240143777A1

    公开(公告)日:2024-05-02

    申请号:US17977193

    申请日:2022-10-31

    CPC classification number: G06F21/577 G06F21/54 G06F21/552

    Abstract: In one embodiment, a device may identify one or more vulnerable portions of a program to be observed based on security vulnerability information. The device may instrument the program with an observability control to configure collecting of observability information regarding the one or more vulnerable portions of the program. The device may modify the observability control based on one or more attributes associated with the collecting of the observability information regarding the one or more vulnerable portions of the program. The device may the observability information regarding the one or more vulnerable portions of the program according to the observability control as modified.

    Adaptive qubit-based threshold handshaking for quantum safe protocols

    公开(公告)号:US12231548B2

    公开(公告)日:2025-02-18

    申请号:US18078223

    申请日:2022-12-09

    Abstract: In one embodiment, a first device in a network receives a quantum computing power metric indicative of a maximum available compute power of quantum computers. The first device receives, from a second device in the network, a listing of cryptographic suites available on the second device. The first device selects, based on the quantum computing power metric, a particular cryptographic suite from among the listing of cryptographic suites available on the second device. The first device sends, to the second device via the network, an indication that the particular cryptographic suite is to be used to encrypt and decrypt traffic exchanged between the first device and the second device.

    POST-QUANTUM RISK ANALYSIS USING CIPHER SUITE DEPENDENCY GRAPHS AND RISK SCORING USING CALL PATHS

    公开(公告)号:US20250045422A1

    公开(公告)日:2025-02-06

    申请号:US18365358

    申请日:2023-08-04

    Abstract: A method to identify and remediate unsafe cipher suite deployments. The method includes identifying a target to be analyzed, determining a collection of cipher suites used by the target, generating and displaying a cipher suite dependency graph for the target based on the collection of cipher suites, and classifying the target as being one of post-quantum computing safe and post-quantum computing unsafe based on the cipher suite dependency graph and based on a predetermined rule for each cipher suite in the collection of cipher suites. A cipher suite hosted by a target can be remediated to convert the target to a post-quantum computing safe state.

    ADAPTIVE QUBIT-BASED THRESHOLD HANDSHAKING FOR QUANTUM SAFE PROTOCOLS

    公开(公告)号:US20240195612A1

    公开(公告)日:2024-06-13

    申请号:US18078223

    申请日:2022-12-09

    CPC classification number: H04L9/0852

    Abstract: In one embodiment, a first device in a network receives a quantum computing power metric indicative of a maximum available compute power of quantum computers. The first device receives, from a second device in the network, a listing of cryptographic suites available on the second device. The first device selects, based on the quantum computing power metric, a particular cryptographic suite from among the listing of cryptographic suites available on the second device. The first device sends, to the second device via the network, an indication that the particular cryptographic suite is to be used to encrypt and decrypt traffic exchanged between the first device and the second device.

    UNCHEATABLE FEDERATED LEARNING
    5.
    发明公开

    公开(公告)号:US20230179630A1

    公开(公告)日:2023-06-08

    申请号:US17541508

    申请日:2021-12-03

    CPC classification number: H04L63/1491 G06N20/20

    Abstract: In one embodiment, a device identifies a plurality of nodes of a distributed or federated learning system. The device receives model training results from the plurality of nodes. The device determines, based in part on the model training results or information about the plurality of nodes, whether a particular node or subset of nodes in the plurality of nodes provided fraudulent model training results. The device initiates a corrective measure with respect to the particular node or subset of nodes, based on a determination that the particular node or subset of nodes provided fraudulent model training results, in accordance with a policy.

    OBSERVABILITY DATA RELATIONSHIP GRAPHS
    6.
    发明公开

    公开(公告)号:US20240311395A1

    公开(公告)日:2024-09-19

    申请号:US18120589

    申请日:2023-03-13

    CPC classification number: G06F16/285 G06F11/3476

    Abstract: According to one or more embodiments of the disclosure, an example process herein may comprise: obtaining observability data for a computer system for a given time period; determining observability entities from the observability data; converting the observability entities into contextual vertices having associated vertex attributes; determining relationships among the contextual vertices based on correlation of the observability data; selecting a subset of the relationships to be edges based on a quality of the relationships, the edges having associated edge attributes; and generating an observability graph for the observability data for the computer system for the given time period by connecting the contextual vertices via corresponding edges.

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