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US Patent 10176321 Leveraging behavior-based rules for malware family classification

Patent 10176321 was granted and assigned to FireEye on January, 2019 by the United States Patent and Trademark Office.

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Contents

Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent
1

Patent attributes

Patent Applicant
FireEye
FireEye
1
Current Assignee
FireEye
FireEye
1
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
1
Patent Number
101763211
Patent Inventor Names
Abdul Salam1
Fahim H. Abbasi1
Farrukh Shahzad1
Date of Patent
January 8, 2019
1
Patent Application Number
149671801
Date Filed
December 11, 2015
1
Patent Citations Received
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US Patent 11997111 Attribute-controlled malware detection
2
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US Patent 11856011 Multi-vector malware detection data sharing system for improved detection
3
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US Patent 11882140 System and method for detecting repetitive cybersecurity attacks constituting an email campaign
4
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US Patent 11888875 Subscription and key management system
5
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US Patent 11949698 Dynamically remote tuning of a malware content detection system
6
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US Patent 11979428 Technique for verifying exploit/malware at malware detection appliance through correlation with endpoints
7
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US Patent 11985149 System and method for automated system for triage of cybersecurity threats
8
‌
US Patent 11522884 Subscription and key management system
...
Patent Primary Examiner
‌
Ghazal B Shehni
1
Patent abstract

According to one embodiment, a malware classification scheme operating with an electronic device, configured with one or more hardware processors and a memory that stores the software handling the malware classification scheme that is conducted through analysis of behavior-based rules, is described. This malware classification scheme (i) conducts a determination whether a sequence of rules correspond to potential malicious behaviors detected during analysis of a malware sample within one or more virtual machines, and in response to determining that the sequence of rules corresponds to potential malicious behaviors, (ii) conducts an attempt to classify the malware sample to at least one known malware family based on an analysis of the sequence of rules.

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