FIGHT-THROUGH NODES WITH DISPOSABLE VIRTUAL MACHINES AND ROLLBACK OF PERSISTENT STATE
    61.
    发明申请
    FIGHT-THROUGH NODES WITH DISPOSABLE VIRTUAL MACHINES AND ROLLBACK OF PERSISTENT STATE 有权
    具有可扩展的虚拟机和持续状态的扭曲的数字

    公开(公告)号:US20150309831A1

    公开(公告)日:2015-10-29

    申请号:US14791089

    申请日:2015-07-02

    Abstract: A server system receives messages from client computing devices. Each of the messages corresponds to a transaction. The server system assigns each respective transaction to a respective fresh virtual machine. Furthermore, the server system performs, as part of a respective virtual machine processing a respective transaction, a modification associated with the respective transaction to a shared database. The shared database is persisted independently of the plurality of virtual machines. In response to determining that processing of the respective transaction is complete, the server system discards the respective virtual machine. In response to a trigger, such as determining that the respective transaction is associated with a cyber-attack, the server system uses checkpoint data associated with the respective transaction to roll back the modifications associated with the respective transaction to the shared database.

    Abstract translation: 服务器系统从客户端计算设备接收消息。 每个消息都对应一个事务。 服务器系统将每个相应的事务分配给相应的新鲜虚拟机。 此外,服务器系统作为处理相应事务的相应虚拟机的一部分执行与相应事务相关联的修改到共享数据库。 独立于多个虚拟机来保持共享数据库。 响应于确定相应交易的处理完成,服务器系统丢弃相应的虚拟机。 响应于诸如确定相应交易与网络攻击相关联的触发,服务器系统使用与相应交易相关联的检查点数据将与相应交易相关联的修改回滚到共享数据库。

    System for cyber-attack simulation using artificial intelligence modeling

    公开(公告)号:US12032681B1

    公开(公告)日:2024-07-09

    申请号:US17896974

    申请日:2022-08-26

    CPC classification number: G06F21/53 G06F21/552 G06N3/04 H04L63/1458

    Abstract: The methods and systems disclosed herein generally relate to automated execution and evaluation of computer network training exercises, such as in a virtual environment. A server executes a first attack action by a virtual attack machine against a virtual target machine based on a cyber-attack scenario, wherein the virtual target machine is configured to be controlled by the user computer. The server receives a user response to the first attack action, determines, using a decision tree, a first proposed attack action based on the user response, and executes an artificial intelligence model to determine a second proposed attack action based on the user response. The server selects a subsequent attack action from the first proposed attack action and the second proposed attack action and executes the subsequent attack action by the virtual attack machine against the virtual target machine.

    Systems and methods for legacy source code optimization and modernization

    公开(公告)号:US11599356B1

    公开(公告)日:2023-03-07

    申请号:US17353501

    申请日:2021-06-21

    Abstract: Disclosed herein are embodiments of systems, methods, and products for modernizing and optimizing legacy software. A computing device may perform an automated runtime performance profiling process. The performance profiler may automatically profile the legacy software at runtime, monitor the memory usage and module activities of the legacy software, and pinpoint/identify a subset of inefficient functions in the legacy software that scale poorly or otherwise inefficient. The computing device may further perform a source code analysis and refactoring process. The computing device may parse the source code of the subset of inefficient functions and identify code violations within the source code. The computing device may provide one or more refactoring options to optimize the source code. Each refactoring option may comprise a change to the source code configured to correct the code violations. The computing device may refactor the source code based on a selected refactoring option.

    Systems and methods for malware detection and mitigation

    公开(公告)号:US11451581B2

    公开(公告)日:2022-09-20

    申请号:US16417531

    申请日:2019-05-20

    Abstract: Disclosed herein are embodiments of systems, methods, and products comprise an analytic server, which detects and defends against malware in-flight regardless of the specific nature and methodology of the underlying attack. The analytic server learns the system's normal behavior during testing and evaluation phase and trains a machine-learning model based on the normal behavior. The analytic server monitors the system behavior during runtime comprising the runtime behavior of each sub-system of the system. The analytic server executes the machine-learning model and compares the system runtime behavior with the normal behavior to identify anomalous behavior. The analytic server executes one or more mitigation instructions to mitigate malware. Based on multiple available options for mitigating malware, the analytic server makes an intelligent decision and takes the least impactful action that have the least impact on the system to maintain mission assurance.

    Bandwidth-dependent media stream compression

    公开(公告)号:US11349894B1

    公开(公告)日:2022-05-31

    申请号:US16952981

    申请日:2020-11-19

    Abstract: In general, this disclosure describes media stream transmission techniques for a computing device. The computing device captures a first media item and identifies a primary portion of the first media item and a secondary portion of the first media item different than the primary portion. The computing device applies a first compression algorithm to the primary portion of the first media item to generate a compressed primary portion. The computing device applies a second compression algorithm to the secondary portion of the first media item to generate a compressed secondary portion, where a data compression ratio of the second compression algorithm is greater than a data compression ratio of the first compression algorithm. The computing device transmits, to a central computing device, the compressed primary portion of the first media item and the compressed secondary portion of the first media item.

    Systems and methods for used learned representations to determine terrain type

    公开(公告)号:US11275940B1

    公开(公告)日:2022-03-15

    申请号:US16924409

    申请日:2020-07-09

    Abstract: Disclosed herein are embodiments of systems, methods, and products comprise an analytic server, which provides a terrain segmentation and classification tool for synthetic aperture radar (SAR) imagery. The server accurately segments and classifies terrain types in SAR imagery and automatically adapts to new radar sensors data. The server receives a first SAR imagery and trains an autoencoder based on the first SAR imagery to generate learned representations of the first SAR imagery. The server trains a classifier based on labeled data of the first SAR imagery data to recognize terrain types from the learned representations of the first SAR imagery. The server receives a terrain query for a second SAR imagery. The server translates the second imagery data into the first imagery data and classifies the second SAR imagery terrain types using the classifier trained for the first SAR imagery. By reusing the original classifier, the server improves system efficiency.

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