External malware data item clustering and analysis
Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, and provide results of the automated analysis in an optimized way to an analyst. The automated ana...
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| creator | Cohen, David Boortz, Julia Sprague, Matthew Fu, Bing Jie Nepomnyashchiy, Ilya Ma, Jason Grossman, Jack Smaliy, Alex Thompson, James Harris, Michael Kross, Michael Borochoff, Adam Berler, Steven Menon, Parvathy |
| description | Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, and provide results of the automated analysis in an optimized way to an analyst. The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a compact, human-readable analysis of the data clusters. The human-readable analyzes (also referred to herein as "summaries" or "conclusions") of the data clusters may be organized into an interactive user interface so as to enable an analyst to quickly navigate among information associated with various data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation. Embodiments of the present disclosure also relate to automated scoring of the clustered data structures. |
| format | Patent |
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The automated analysis of the clustered data structures (also referred to herein as data clusters) may include an automated application of various criteria or rules so as to generate a compact, human-readable analysis of the data clusters. The human-readable analyzes (also referred to herein as "summaries" or "conclusions") of the data clusters may be organized into an interactive user interface so as to enable an analyst to quickly navigate among information associated with various data clusters and efficiently evaluate those data clusters in the context of, for example, a fraud investigation. Embodiments of the present disclosure also relate to automated scoring of the clustered data structures.</description><language>eng</language><subject>ALARM SYSTEMS ; CALCULATING ; COMPUTING ; COUNTING ; ELECTRIC COMMUNICATION TECHNIQUE ; ELECTRIC DIGITAL DATA PROCESSING ; ELECTRICITY ; ORDER TELEGRAPHS ; PHYSICS ; SIGNALLING ; SIGNALLING OR CALLING SYSTEMS ; TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION</subject><creationdate>2018</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20180508&DB=EPODOC&CC=US&NR=9965937B2$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20180508&DB=EPODOC&CC=US&NR=9965937B2$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Cohen, David</creatorcontrib><creatorcontrib>Boortz, Julia</creatorcontrib><creatorcontrib>Sprague, Matthew</creatorcontrib><creatorcontrib>Fu, Bing Jie</creatorcontrib><creatorcontrib>Nepomnyashchiy, Ilya</creatorcontrib><creatorcontrib>Ma, Jason</creatorcontrib><creatorcontrib>Grossman, Jack</creatorcontrib><creatorcontrib>Smaliy, Alex</creatorcontrib><creatorcontrib>Thompson, James</creatorcontrib><creatorcontrib>Harris, Michael</creatorcontrib><creatorcontrib>Kross, Michael</creatorcontrib><creatorcontrib>Borochoff, Adam</creatorcontrib><creatorcontrib>Berler, Steven</creatorcontrib><creatorcontrib>Menon, Parvathy</creatorcontrib><title>External malware data item clustering and analysis</title><description>Embodiments of the present disclosure relate to a data analysis system that may automatically generate memory-efficient clustered data structures, automatically analyze those clustered data structures, and provide results of the automated analysis in an optimized way to an analyst. 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| subjects | ALARM SYSTEMS CALCULATING COMPUTING COUNTING ELECTRIC COMMUNICATION TECHNIQUE ELECTRIC DIGITAL DATA PROCESSING ELECTRICITY ORDER TELEGRAPHS PHYSICS SIGNALLING SIGNALLING OR CALLING SYSTEMS TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION |
| title | External malware data item clustering and analysis |
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