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公开(公告)号:US12160429B2
公开(公告)日:2024-12-03
申请号:US18225517
申请日:2023-07-24
Applicant: Cisco Technology, Inc.
Inventor: Petr Somol , Martin Kopp , Jan Kohout , Jan Brabec , Marc René Jacques Marie Dupont , Cenek Skarda , Lukas Bajer , Danila Khikhlukha
Abstract: In one embodiment, a device obtains input features for a neural network-based model. The device pre-defines a set of neurons of the model to represent known behaviors associated with the input features. The device constrains weights for a plurality of outputs of the model. The device trains the neural network-based model using the constrained weights for the plurality of outputs of the model and by excluding the pre-defined set of neurons from updates during the training.
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公开(公告)号:US11038900B2
公开(公告)日:2021-06-15
申请号:US16120580
申请日:2018-09-04
Applicant: Cisco Technology, Inc.
Inventor: Jan Jusko , Martin Rehak , Danila Khikhlukha , Harshit Nayyar
IPC: H04L29/06
Abstract: In one embodiment, a service receives a plurality of process hashes for processes executed by a plurality of devices. The service receives traffic data indicative of traffic between the plurality of devices and a plurality of remote server domains. The service forms a bipartite graph based on the processes hashes and the traffic data. A node of the graph represents a particular process hash or server domain and an edge between nodes in the graph represents network traffic between a process and a server domain. The service identifies, based on the bipartite graph, a subset of the plurality of processes as exhibiting polymorphic malware behavior. The service causes performance of a mitigation action in the network based on the identified subset of processes identified as exhibiting polymorphic malware behavior.
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公开(公告)号:US11451561B2
公开(公告)日:2022-09-20
申请号:US16131146
申请日:2018-09-14
Applicant: Cisco Technology, inc.
Inventor: Jan Jusko , Danila Khikhlukha , Harshit Nayyar
Abstract: In one embodiment, a device obtains execution records regarding executions of a plurality of binaries. The execution records comprise command line arguments used during the execution. The device determines measures of similarity between the executions of the binaries based on their command line arguments. The device clusters the executions into clusters based on the determined measures of similarity. The device flags the command line arguments for a particular one of the clusters as an indicator of compromise for malware, based on at least one of the binaries associated with the particular cluster being malware.
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公开(公告)号:US20200092306A1
公开(公告)日:2020-03-19
申请号:US16131146
申请日:2018-09-14
Applicant: Cisco Technology, Inc.
Inventor: Jan Jusko , Danila Khikhlukha , Harshit Nayyar
Abstract: In one embodiment, a device obtains execution records regarding executions of a plurality of binaries. The execution records comprise command line arguments used during the execution. The device determines measures of similarity between the executions of the binaries based on their command line arguments. The device clusters the executions into clusters based on the determined measures of similarity. The device flags the command line arguments for a particular one of the clusters as an indicator of compromise for malware, based on at least one of the binaries associated with the particular cluster being malware.
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公开(公告)号:US20200076832A1
公开(公告)日:2020-03-05
申请号:US16120580
申请日:2018-09-04
Applicant: Cisco Technology, Inc.
Inventor: Jan Jusko , Martin Rehak , Danila Khikhlukha , Harshit Nayyar
IPC: H04L29/06
Abstract: In one embodiment, a service receives a plurality of process hashes for processes executed by a plurality of devices. The service receives traffic data indicative of traffic between the plurality of devices and a plurality of remote server domains. The service forms a bipartite graph based on the processes hashes and the traffic data. A node of the graph represents a particular process hash or server domain and an edge between nodes in the graph represents network traffic between a process and a server domain. The service identifies, based on the bipartite graph, a subset of the plurality of processes as exhibiting polymorphic malware behavior. The service causes performance of a mitigation action in the network based on the identified subset of processes identified as exhibiting polymorphic malware behavior.
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公开(公告)号:US20240106836A1
公开(公告)日:2024-03-28
申请号:US18225517
申请日:2023-07-24
Applicant: Cisco Technology, Inc.
Inventor: Petr Somol , Martin Kopp , Jan Kohout , Jan Brabec , Marc René Jacques Marie Dupont , Cenek Skarda , Lukas Bajer , Danila Khikhlukha
Abstract: In one embodiment, a device obtains input features for a neural network-based model. The device pre-defines a set of neurons of the model to represent known behaviors associated with the input features. The device constrains weights for a plurality of outputs of the model. The device trains the neural network-based model using the constrained weights for the plurality of outputs of the model and by excluding the pre-defined set of neurons from updates during the training.
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公开(公告)号:US11750621B2
公开(公告)日:2023-09-05
申请号:US16831197
申请日:2020-03-26
Applicant: Cisco Technology, Inc.
Inventor: Petr Somol , Martin Kopp , Jan Kohout , Jan Brabec , Marc René Jacques Marie Dupont , Cenek Skarda , Lukas Bajer , Danila Khikhlukha
Abstract: In one embodiment, a device obtains input features for a neural network-based model. The device pre-defines a set of neurons of the model to represent known behaviors associated with the input features. The device constrains weights for a plurality of outputs of the model. The device trains the neural network-based model using the constrained weights for the plurality of outputs of the model and by excluding the pre-defined set of neurons from updates during the training.
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公开(公告)号:US20210306350A1
公开(公告)日:2021-09-30
申请号:US16831197
申请日:2020-03-26
Applicant: Cisco Technology, Inc.
Inventor: Petr Somol , Martin Kopp , Jan Kohout , Jan Brabec , Marc René Jacques Marie Dupont , Cenek Skarda , Lukas Bajer , Danila Khikhlukha
Abstract: In one embodiment, a device obtains input features for a neural network-based model. The device pre-defines a set of neurons of the model to represent known behaviors associated with the input features. The device constrains weights for a plurality of outputs of the model. The device trains the neural network-based model using the constrained weights for the plurality of outputs of the model and by excluding the pre-defined set of neurons from updates during the training.
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