Systems and methods for cloud-based threat alerts and monitoring

    公开(公告)号:US20240314169A1

    公开(公告)日:2024-09-19

    申请号:US18674428

    申请日:2024-05-24

    Applicant: Zscaler, Inc.

    Inventor: Rubin Azad

    CPC classification number: H04L63/1491 H04L63/1416 H04L63/1425

    Abstract: Systems and methods for cloud-based threat alerts and monitoring include monitoring network traffic via a cloud-based system of one or more tenants of the cloud-based system; receiving a plurality of alerts associated with the network traffic from a plurality of security tools of the cloud-based system; logging the plurality of alerts; and providing an event chain, including the plurality of alerts. Based on the event chain, alerts can be identified as being false positives or legitimate.

    Cyber threat deception method and system, and forwarding device

    公开(公告)号:US12074908B2

    公开(公告)日:2024-08-27

    申请号:US17369057

    申请日:2021-07-07

    Abstract: This application discloses a cyber threat deception method and system, and a forwarding device. The forwarding device obtains a deception target set, where the deception target set includes a deception target, and the deception target includes an unused internet protocol (IP) address or an unopened port number on a used IP address. The forwarding device receives an IP packet from a host, and determines whether a destination party that the IP packet requests to access belongs to the deception target set. If the destination party that the IP packet requests to access belongs to the deception target set, the forwarding device sends the IP packet to a honeypot management server. The forwarding device receives a response packet, returned by the honeypot management server, of the corresponding IP packet. The forwarding device sends the response packet to the host.

    LAYERED CYBERSECURITY USING SPURIOUS DATA SAMPLES

    公开(公告)号:US20240283822A1

    公开(公告)日:2024-08-22

    申请号:US18170492

    申请日:2023-02-16

    CPC classification number: H04L63/1491 H04L41/16 H04L63/1416

    Abstract: In some aspects, a computing system may iterate between adding spurious data to the dataset and training a model on the dataset. If the model's performance has not dropped by more than a threshold amount, then additional spurious data may be added to the dataset until the desired amount of performance decrease has been achieved. the computing system may determine the amount of impact each feature has on a model's output. The computing system may generate a spurious data sample by modifying values of features that are more impactful than other features. The computing system may repeatedly modify the spurious data that is stored in a dataset. If a cybersecurity incident occurs (e.g., the dataset is stolen or leaked), the system may identify when the cybersecurity incident took place based on the spurious data that is stored in the dataset.

    SYSTEMS, METHODS, AND APPARATUSES FOR ACTIVATING A DECOY RESOURCE BASED ON DURESS TRIGGERS IN AN ELECTRONIC NETWORK

    公开(公告)号:US20240275815A1

    公开(公告)日:2024-08-15

    申请号:US18109431

    申请日:2023-02-14

    CPC classification number: H04L63/1491 G06N20/00 H04L63/102

    Abstract: Systems, computer program products, and methods are described herein for activating a decoy resource based on duress triggers in an electronic network. The present invention is configured to receive a resource distribution request, wherein the resource distribution request comprises a resource account identifier; determine a verified unique identifier sequence associated with the resource account identifier; receive an unverified unique identifier sequence associated with the resource distribution request; compare the unverified unique identifier sequence with the verified unique identifier sequence; and determine, based on the comparison of the unverified unique identifier sequence with the verified unique identifier sequence, a duress trigger; and activate, in an instance where the duress trigger is positive, a decoy resource container, wherein the decoy resource container comprises at least one decoy resource.

    ATTACK DETECTION SYSTEM
    7.
    发明公开

    公开(公告)号:US20240155002A1

    公开(公告)日:2024-05-09

    申请号:US18499757

    申请日:2023-11-01

    Inventor: Kazuya OKADA

    CPC classification number: H04L63/1491 H04L67/12

    Abstract: A first controller of a first device monitors communication to a first vehicle connected to the network. Further, when it is detected that an attack on the first vehicle is being carried out from the attack source device, the first controller transmits a first command for activating a honeypot server simulating a vehicle system of the first vehicle to the second device and transmits a second command for transferring packets transmitted from the attacking device to the first vehicle to the second device to a communication device that relays communication to the first vehicle in the network. Further, a second controller of a second device processes packets transmitted from the attack source device to the first vehicle and transferred to the second device by the communication device.

    Methods for protecting pattern classification node from malicious requests and related networks and nodes

    公开(公告)号:US11916931B2

    公开(公告)日:2024-02-27

    申请号:US17606111

    申请日:2019-04-24

    CPC classification number: H04L63/1416 G06N3/04 H04L63/1425 H04L63/1491

    Abstract: A method of operating a protection node for protecting a pattern classification node from malicious requests may be provided. The protection node may receive, from a user node, a request containing an original pattern to be classified by a machine learning algorithm performed by the pattern classification node. The protection node may add noise to the original pattern to generate a noisy pattern. The protection node may obtain a first classification of the noisy pattern based on processing of the noisy pattern by a first clone of the machine learning algorithm at the protection node; obtain a second classification of the original pattern based forwarding the request for processing of the original pattern by the machine learning algorithm performed at the pattern classification node; and compare the first and second classifications to determine whether the first and second classifications satisfy a defined similarity rule. The protection node may use the comparison to manage the request from the user node.

    Cybersecurity Risk Analysis and Modeling of Risk Data on an Interactive Display

    公开(公告)号:US20240039954A1

    公开(公告)日:2024-02-01

    申请号:US18365371

    申请日:2023-08-04

    Applicant: Zscaler, Inc.

    CPC classification number: H04L63/1491 H04L63/1425 H04L63/1416

    Abstract: Systems and methods are provided for performing risk assessment activities and preparing attained risk data for display on one or more user interfaces. In one implementation, a method may include the step of detecting one or more cybersecurity risk factors associated with an organization to determine a risk posture of the organization. The method may further include the step of attaining one or more remediation recommendations for enabling a person associated with the organization to select one or more actions for mitigating the one or more cybersecurity risk factors and improving the risk posture of the organization. Then, the method is configured to communicate display information to a user device associated with the organization, the display information including at least the one or more cybersecurity risk factors and the one or more remediation recommendations to be exhibited on a Graphical User Interface (GUI) of the user device.

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