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公开(公告)号：US20220012365A1
公开(公告)日：2022-01-13
申请号：US16926645
申请日：2020-07-11
Applicant: Avast Software s.r.o.
Inventor： Deepali Garg , Rajarshi Gupta
Abstract: A method for applying electronic data sharing settings. The method includes determining a first image or a first plurality of images shared by a user to a first network-enabled application. A first plurality of image components are extracted from the first image or the first plurality of images, and access by the first network-enabled application to a second image or a second plurality of images stored on a computing device of the user is enabled based on the first plurality of image components extracted from the first image or the first plurality of images. A method for controlling internet browsing is further provided.
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公开(公告)号：US20210336990A1
公开(公告)日：2021-10-28
申请号：US16857924
申请日：2020-04-24
Applicant: Avast Software s.r.o.
Inventor： Dan Martinec
IPC: H04L29/06 , H04L29/08 , G06F16/953
Abstract: A method of identifying network devices such as a router includes accessing an HTTP server on at least one network device, and evaluating a web page served by the device's HTTP server. The web page is evaluated to determine whether it is similar to a page group from a plurality of page groups, where each of the plurality of page groups comprises a group of web pages similar to other pages in the page group. If the evaluated web page is determined similar to a page group, the page group most similar to the evaluated web page is identified as corresponding to the identity of the network device.
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23.发明申请公开(公告)号：US20210097179A1
公开(公告)日：2021-04-01
申请号：US16588704
申请日：2019-09-30
Applicant: Avast Software s.r.o.
Inventor： Peter Kovác
Abstract: Systems and methods use negative feedback to create generic rules for a high dimensional sparse feature space. A system receives a set of fingerprints, where a fingerprint can be a set of features of a file. The fingerprints can be clustered according to similarity. For each cluster, a proto-rule is created that has a condition for each feature. The proto-rule is simplified using negative feedback to create a well-formed rule having a comparatively small subset of the conditions in the proto-rule that are useful in determining malware. The well-formed rule can be added to a set of rules used in a malware detection system.
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公开(公告)号：US10965802B2
公开(公告)日：2021-03-30
申请号：US16446105
申请日：2019-06-19
Applicant: Avast Software s.r.o.
Inventor： Juyong Do , Rajarshi Gupta
IPC: H04M3/00 , H04M1/72463 , H04L12/58 , G06N3/04 , G10L15/26 , H04L29/08 , G06F40/279
Abstract: A method of controlling use of network-connectable devices is provided. The method includes monitoring by a first computational process, operating at a first processor utilization level, communication on a user device operated by a particular user and determining based on the monitoring by the first computational process a trigger event. The method further includes monitoring by a second computational process, operating at a second processor utilization level higher than the first processor utilization level, the communication on the user device responsive to determining the trigger event. Use of the user device is restricted based at least on the monitoring by the second computational process of the communication.
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公开(公告)号：US10909179B2
公开(公告)日：2021-02-02
申请号：US15941668
申请日：2018-03-30
Applicant: Avast Software s.r.o.
Inventor： Peter Ková{hacek over (c)}
IPC: G06F16/901 , G06F17/11 , G06F21/56 , G06F21/55
Abstract: Analyzing a large number of files to identify malicious software including evaluating a multigraph including determining a graph having a plurality of nodes, including a source node and target nodes from a data set and merging the graph into a multigraph in response to a node score above a threshold level, for each target node; determining one or more specificity indexes for target node and determining a node score for the target node based, at least in part, on a specificity index.
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Patent Agency Ranking
公开(公告)号：US20210019408A1
公开(公告)日：2021-01-21
申请号：US16513639
申请日：2019-07-16
Applicant: Avast Software s.r.o.
Inventor： Nikolaos Chrysaidos
Abstract: A malware analysis system is operable to select a family of related malware for evaluation from a database of observed malware. The system extracts static and dynamic features of the malware samples from the selected malware family in the database, and an observation time of each of the malware samples from the selected malware family. The system then creates a visualization illustrating change in at least one of static and dynamic features of the selected malware family over time. The system extracts a geographic location of a command and control server associated with malware samples if present, and the created visualization further illustrates the geographic areas in which the malware was found. The system illustrates a group of malware detections as an object having characteristics indicating one or more of the features in the clustered malware detections, and/or the number of features that vary between the clustered malware detections.
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公开(公告)号：US20200380335A1
公开(公告)日：2020-12-03
申请号：US16426958
申请日：2019-05-30
Applicant: Avast Software s.r.o.
Inventor： Martin Neznal
Abstract: A method of identifying anomalous traffic in a sequence of commercial transaction data includes preprocessing the commercial transaction data into a sequential time series of commercial transaction data, and providing the time series of commercial transaction data to a recurrent neural network. The recurrent neural network evaluates the provided time series of commercial transaction data to generate and output a predicted next element in the time series of commercial transaction data, which is compared with an observed actual next element in the time series of commercial transaction data. The observed next element in the time series of commercial transaction data is determined to be anomalous if it is sufficiently different from the predicted next element in the time series of commercial transaction data.
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公开(公告)号：US20200210871A1
公开(公告)日：2020-07-02
申请号：US16725906
申请日：2019-12-23
Applicant: Avast Software s.r.o.
Inventor： Galina Alperovich , Dmitry Kuznetsov , Rajarshi Gupta
Abstract: Systems and methods for device type classification system include a rules engine and a machine learning engine. The machine learning engine can be trained using device type data from multiple networks. The machine learning engine and the rules engine can receive data for devices on a network at a first point in time. The data can be submitted to a rules engine and the machine learning engine, which each produce device type probabilities for devices on the network. The device type probabilities from the rules engine and the machine learning engine can be processed to determine device types for one or more devices on the network. As more data becomes available at later points in time, the additional data can be provided to the rules engine and the machine learning engine to update the device type determinations for the network.
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公开(公告)号：US10686813B2
公开(公告)日：2020-06-16
申请号：US15468769
申请日：2017-03-24
Applicant: Avast Software s.r.o.
IPC: H04L29/06
Abstract: A similarity fingerprint for a data object such as a file can be automatically determined using one or more anchor values. The one or more anchor values can be provided or determined. For each anchor value, a set of distances between each instance of the anchor value in the data object is determined. The set of distances for the instance of the anchor value is aggregated into a single value. The single value is added as a component of the similarity fingerprint. Thus, if there are N anchor values, there can be N components of the similarity fingerprint. The similarity fingerprints of different data objects can be compared and the results of the comparison can be used to determine how similar the data objects are.
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公开(公告)号：US10667077B2
公开(公告)日：2020-05-26
申请号：US16024606
申请日：2018-06-29
Applicant: Avast Software s.r.o.
Inventor： Virginia Howard , Dan Hodges
Abstract: A hybrid location service maintains a user state for each of a plurality of mobile devices communicably coupled to the hybrid location service via one or more networks. The hybrid location service can receive a request for a location of a mobile device. In response, the hybrid location service can determine a consent source. The consent source can include the mobile device or a network operator of the network used by the mobile device. The hybrid location service determines a response to the request for the location of the mobile device based, at least in part, on a user state of the mobile device and a user consent obtained from the consent source.
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