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    Securing applications through similarity-based risk assessment
    83.
    发明授权
    Securing applications through similarity-based risk assessment 有权

    公开(公告)号：US11895134B2

    公开(公告)日：2024-02-06

    申请号：US17228118

    申请日：2021-04-12

    Applicant: SAP SE

    Inventor： Sudhir Verma ,  Ayushi Singla ,  Sumit Kumar ,  Sarma Adithe Venkata Ram ,  Jani Mahammad

    IPC: H04L67/50 ,  H04L9/40

    CPC classification number: H04L63/1425 ,  H04L63/105 ,  H04L63/1433 ,  H04L63/1441 ,  H04L63/168 ,  H04L67/535

    Abstract: Systems, methods, and computer media are described for user risk assessment using similarity analysis. Records of transactions performed by a user while in previous enhanced application access sessions can be evaluated against records of transactions performed by other users in previous sessions. The more similar a user is to other users, the more likely it is the user was acting in a typical manner, and the less likely the user poses a security risk. A similarity analysis can be performed using a bipartite graph linking a group of users and a group of application transactions. By examining an edge between a user and a performed transaction, other edges (and corresponding other users) can be identified that also performed the transaction. A similarity score can be calculated based on the bipartite graph and can be used to determine a risk classification and allow or deny an enhanced application access session request.

    Detecting and blocking a malicious file early in transit on a network
    84.
    发明授权
    Detecting and blocking a malicious file early in transit on a network 有权

    公开(公告)号：US11895129B2

    公开(公告)日：2024-02-06

    申请号：US17304958

    申请日：2021-06-29

    Applicant: Juniper Networks, Inc.

    Inventor： Paul Randee Dilim Kimayong ,  Mounir Hahad

    IPC: G06F21/56 ,  H04L9/40

    CPC classification number: H04L63/1416 ,  G06F21/563 ,  G06F21/564 ,  H04L63/1441

    Abstract: A device may receive a malicious file associated with a network of network devices and may identify a file type and file characteristics associated with the malicious file. The device may determine one or more rules to apply to the malicious file based on the file type and the file characteristics associated with the malicious file and may apply the one or more rules to the malicious file to generate a partial file signature for the malicious file. The device may provide the partial file signature for the malicious file to one or more of the network devices of the network. The partial file signature may cause the one or more of the network devices to block the malicious file.

    Securing against network vulnerabilities
    86.
    发明授权
    Securing against network vulnerabilities 有权

    公开(公告)号：US11888889B2

    公开(公告)日：2024-01-30

    申请号：US17687603

    申请日：2022-03-05

    Applicant: UAB 360 IT

    Inventor： Adrianus Warmenhoven

    IPC: H04L9/40 ,  H04L41/16 ,  G06F16/955

    CPC classification number: H04L63/1433 ,  G06F16/9566 ,  H04L41/16 ,  H04L63/08 ,  H04L63/0876 ,  H04L63/1441

    Abstract: A method determining, by an infrastructure device in communication with a user device, authentic feature information that indicates a characteristic associated with an authentic feature included in an authentic communication associated with an authentic entity, with which the user device intends to communicate over a network; and transmitting, by the infrastructure device to the user device, authentic entity information that includes the authentic feature information and an association between the characteristic associated with the authentic feature and authentic communication information associated with the authentic communication. Various other aspects are contemplated.

    Data protection automatic optimization system and method
    89.
    发明授权
    Data protection automatic optimization system and method 有权

    公开(公告)号：US11882094B2

    公开(公告)日：2024-01-23

    申请号：US17348476

    申请日：2021-06-15

    Applicant: Cobalt Iron Inc.

    Inventor： Richard Raymond Spurlock ,  Robert Merrill Marett ,  James Thomas Kost ,  Gregory John Tevis

    IPC: H04L9/40 ,  H04L47/10

    CPC classification number: H04L63/0227 ,  H04L47/10 ,  H04L63/1441 ,  H04L63/166

    Abstract: A system includes a memory and at least one processor to set a network throughput level setting to a default network traffic rate in a computer network, begin a data protection operation at the network throughput level setting in the computer network, continually monitor the computer network and determine that a condition has occurred in the computer network, dynamically adjust the network throughput level setting in response to the condition by one of decreasing the network throughput level setting by a network traffic rate increment and increasing the network throughput level setting by the network traffic rate increment, and dynamically shape network or storage traffic for the data protection operation using the network throughput level setting.

    Real-time detection of online new-account creation fraud using graph-based neural network modeling
    90.
    发明公开
    Real-time detection of online new-account creation fraud using graph-based neural network modeling 审中-公开

    公开(公告)号：US20240022593A1

    公开(公告)日：2024-01-18

    申请号：US17862460

    申请日：2022-07-12

    Applicant: Akamai Technologies, Inc.

    Inventor： Nadav George Costa ,  Ziv Eli

    IPC: H04L9/40 ,  H04L41/16

    CPC classification number: H04L63/1441 ,  H04L63/102 ,  H04L41/16

    Abstract: A method executes upon receiving data (email, IP address) associated with an account registration. In response, an encoding is applied to the data to generate a node vector. The node vector indexes a database of such node vectors that the system maintains (from prior registrations). The database potentially includes one or more node vector(s) that may have a given similarity to the encoded node vector. To determine whether there are such vectors present, a set of k-nearest neighbors to the encoded node vector are then obtained from the database. This set of k-nearest neighbors together with the encoded node vector comprise a virtual graph that is then fed as a graph input to a Graph Neural Network previously trained on a set of training data. The GNN generates a probability that the virtual graph represents a NAF. If the probability exceeds a configurable threshold, the system outputs an indication that the registration is potentially fraudulent, and a mitigation action is taken.

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