Malware detection system attack prevention

    公开(公告)号:US11349858B2

    公开(公告)日:2022-05-31

    申请号:US16421044

    申请日:2019-05-23

    Inventor: Li Chen

    Abstract: Systems and methods may be used to prevent attacks on a malware detection system. A method may include modeling a time series of directed graphs using incoming binary files during training of a machine learning system and detecting, during a time-window of the time series, an anomaly based on a directed graph of the time series of directed graphs. The method may include providing an alert that the anomaly has corrupted the machine learning system. The method may include preventing or remedying corruption of the machine learning system.

    MACHINE LEARNING-BASED DETERMINATION OF PROGRAM CODE CHARACTERISTICS

    公开(公告)号:US20190044959A1

    公开(公告)日:2019-02-07

    申请号:US15867251

    申请日:2018-01-10

    Inventor: Li Chen

    Abstract: A technique includes processing a plurality of sets of program code to extract call graphs; determining similarities between the call graphs; applying unsupervised machine learning to an input formed from the determined similarities to determine latent features of the input; clustering the determined latent features; and determining a characteristic of a given program code set of the plurality of program code sets based on a result of the clustering.

    MALWARE DETECTION SYSTEM ATTACK PREVENTION
    24.
    发明申请

    公开(公告)号:US20180375885A1

    公开(公告)日:2018-12-27

    申请号:US15634685

    申请日:2017-06-27

    Inventor: Li Chen

    CPC classification number: H04L63/1425 G06N20/00 H04L63/1416 H04L63/145

    Abstract: Systems and methods may be used to prevent attacks on a malware detection system. A method may include modeling a time series of directed graphs using incoming binary files during training of a machine learning system and detecting, during a time-window of the dine series, an anomaly based on a directed graph of the time series of directed graphs. The method may include providing an alert that the anomaly has corrupted the machine learning system. The method may include preventing or remedying corruption of the machine learning system.

    System, Apparatus And Method For Detecting A Data-Oriented Programming Attack

    公开(公告)号:US20180260562A1

    公开(公告)日:2018-09-13

    申请号:US15452991

    申请日:2017-03-08

    Abstract: In one embodiments, an apparatus includes: an execution circuit to execute a program; a monitor circuit to monitor the program execution to obtain information regarding a plurality of control transfers incurred during the execution of the program; a graph generation circuit, based on the information, to generate a plurality of control flow graphs each associated with a portion of the execution of the program; a statistic generation circuit to calculate a plurality of feature vectors each associated with one of the plurality of control flow graphs, each of the plurality of feature vectors including a plurality of graph statistics based on the associated control flow graph; and a comparison circuit to compare at least some of the plurality of graph statistics of one or more of the plurality of feature vectors to corresponding graph statistics of a statistical model of the execution of the program, to identify whether an anomaly has occurred in the execution of the program. Other embodiments are described and claimed.

    IDENTIFICATION OF INCOMPATIBLE CO-TENANT PAIRS IN CLOUD COMPUTING

    公开(公告)号:US20180241811A1

    公开(公告)日:2018-08-23

    申请号:US15439668

    申请日:2017-02-22

    CPC classification number: H04L67/1012 H04L67/1008

    Abstract: Disclosed is a mechanism for determining incompatible co-tenants in a cloud network. Cloud performance data is received indicating resource usage of tenants operating on a per server basis. Cross-correlation analysis is performed on past resource usage for each tenant pair operating on the server to determine correlated tenant pairs. Time series forecasting of predicted resource usage is performed for each tenant in the correlated tenant pairs. Cross-correlation analysis is then performed on the predicted resource usage for each correlated tenant pair to determine incompatible co-tenant pairs. The determined incompatible co-tenant pairs may be forwarded toward an orchestration system for hardware resource allocation in the cloud network.

    Malware detection system attack prevention

    公开(公告)号:US11032305B2

    公开(公告)日:2021-06-08

    申请号:US16727500

    申请日:2019-12-26

    Inventor: Li Chen

    Abstract: Systems and methods may be used to prevent attacks on a malware detection system. A method may include modeling a time series of directed graphs using incoming binary files during training of a machine learning system and detecting, during a time-window of the time series, an anomaly based on a directed graph of the time series of directed graphs. The method may include providing an alert that the anomaly has corrupted the machine learning system. The method may include preventing or remedying corruption of the machine learning system.

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