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公开(公告)号：US20240259420A1
公开(公告)日：2024-08-01
申请号：US18104137
申请日：2023-01-31
发明人： William Redington Hewlett, II , Sujit Rokka Chhetri , Brody James Kutt , Shan Huang , Nandini Ramanan , Sheng Yang , Min Du
CPC分类号： H04L63/145 , H04L41/16
摘要： The present application discloses a method, system, and computer system for classifying stream data at an edge device. The method includes obtaining a stream of a file at the edge device, aligning a predetermined amount of data in chunks associated with the stream of the file, processing a plurality of aligned chunks associated with the stream of the file using a machine learning model, and classifying, at the edge device, the file based at least in part on a classification of the plurality of aligned chunks.
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公开(公告)号：US11336664B2
公开(公告)日：2022-05-17
申请号：US16517463
申请日：2019-07-19
摘要： Detection of malicious files is disclosed. A set comprising one or more sample classification models is stored on a networked device. N-gram analysis is performed on a sequence of received packets associated with a received file. Performing the n-gram analysis includes using at least one stored sample classification model. A determination is made that the received file is malicious based at least in part on the n-gram analysis of the sequence of received packets. In response to determining that the file is malicious, propagation of the received file is prevented.
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公开(公告)号：US20240037158A1
公开(公告)日：2024-02-01
申请号：US17877199
申请日：2022-07-29
IPC分类号： G06F16/951 , G06F16/955 , G06F16/954 , G06N3/02
CPC分类号： G06F16/951 , G06F16/955 , G06F16/954 , G06N3/02
摘要： The present application discloses a method, system, and computer system for automatically detecting protocol compliance of applications. The method includes determining a URL of a webpage for a software-as-a-service (SaaS) product, extracting body text from the webpage, and using a classifier to determine whether the SaaS product is compliant with one or more protocols.
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公开(公告)号：US20210021611A1
公开(公告)日：2021-01-21
申请号：US16517463
申请日：2019-07-19
摘要： Detection of malicious files is disclosed. A set comprising one or more sample classification models is stored on a networked device. N-gram analysis is performed on a sequence of received packets associated with a received file. Performing the n-gram analysis includes using at least one stored sample classification model. A determination is made that the received file is malicious based at least in part on the n-gram analysis of the sequence of received packets. In response to determining that the file is malicious, propagation of the received file is prevented.
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公开(公告)号：US11636208B2
公开(公告)日：2023-04-25
申请号：US16517465
申请日：2019-07-19
摘要： Generating models usable by data appliances to perform inline malware analysis is disclosed. A set of features, including a plurality of n-grams, extracted from a set of files is received. A reduced set of features is determined that includes at least some of the plurality of n-grams. The reduced set of features is used to generate a model usable by a data appliance to perform inline malware analysis.
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公开(公告)号：US11374946B2
公开(公告)日：2022-06-28
申请号：US16517463
申请日：2019-07-19
摘要： Detection of malicious files is disclosed. A set comprising one or more sample classification models is stored on a networked device. N-gram analysis is performed on a sequence of received packets associated with a received file. Performing the n-gram analysis includes using at least one stored sample classification model. A determination is made that the received file is malicious based at least in part on the n-gram analysis of the sequence of received packets. In response to determining that the file is malicious, propagation of the received file is prevented.
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公开(公告)号：US20210019412A1
公开(公告)日：2021-01-21
申请号：US16517465
申请日：2019-07-19
摘要： Generating models usable by data appliances to perform inline malware analysis is disclosed. A set of features, including a plurality of n-grams, extracted from a set of files is received. A reduced set of features is determined that includes at least some of the plurality of n-grams. The reduced set of features is used to generate a model usable by a data appliance to perform inline malware analysis.
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公开(公告)号：US20220217164A1
公开(公告)日：2022-07-07
申请号：US17702687
申请日：2022-03-23
摘要： Detection of malicious files is disclosed. A set comprising a plurality of sample classification models is received and stored. A determination is made that n-gram analysis should be performed on a sequence of received packets associated with a received file. Performing the n-gram analysis includes using a determined filetype associated with the sequence of received packets to select at least one stored sample classification model included in the set for use in performing the n-gram analysis. A determination is made that the received file is malicious based at least in part on the n-gram analysis of the sequence of received packets. In response to determining that the file is malicious, propagation of the received file is prevented.
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