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US Patent 9571512 Threat detection using endpoint variance

Patent 9571512 was granted and assigned to Sophos Group PLC on February, 2017 by the United States Patent and Trademark Office.

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Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent
1

Patent attributes

Patent Applicant
Sophos Group PLC
Sophos Group PLC
1
Current Assignee
Sophos Group PLC
Sophos Group PLC
1
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
1
Patent Number
95715121
Patent Inventor Names
Neil Robert Tyndale Watkiss1
Simon Neil Reed1
Andrew J. Thomas1
Kenneth D. Ray1
Mark D. Harris1
Date of Patent
February 14, 2017
1
Patent Application Number
145701881
Date Filed
December 15, 2014
1
Patent Citations Received
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US Patent 12130923 Methods and apparatus for augmenting training data using large language models
2
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US Patent 11706247 Detection and prevention of external fraud
3
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US Patent 11755974 Computer augmented threat evaluation
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US Patent 11836664 Enterprise network threat detection
4
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US Patent 11928631 Threat detection with business impact scoring
5
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US Patent 11949713 Abuse mailbox for facilitating discovery, investigation, and analysis of email-based threats
6
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US Patent 11973772 Multistage analysis of emails to identify security threats
7
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US Patent 12081522 Discovering email account compromise through assessments of digital activities
8
...
Patent Primary Examiner
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Kenneth Chang
1
Patent abstract

Threat detection is improved by monitoring variations in observable events and correlating these variations to malicious activity. The disclosed techniques can be usefully employed with any attribute or other metric that can be instrumented on an endpoint and tracked over time including observable events such as changes to files, data, software configurations, operating systems, and so forth. Correlations may be based on historical data for a particular machine, or a group of machines such as similarly configured endpoints. Similar inferences of malicious activity can be based on the nature of a variation, including specific patterns of variation known to be associated with malware and any other unexpected patterns that deviate from normal behavior. Embodiments described herein use variations in, e.g., server software updates or URL cache hits on an endpoint, but the techniques are more generally applicable to any endpoint attribute that varies in a manner correlated with malicious activity.

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