INTERNAL 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...
Gespeichert in:
Hauptverfasser: | , , , , , , , , , , , , , |
---|---|
Format: | Patent |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | |
container_start_page | |
container_title | |
container_volume | |
creator | HARRIS MICHAEL KROSS MICHAEL GROSSMAN JACK SPRAGUE MATTHEW COHEN DAVID MENON PARVATHY BOROCHOFF ADAM THOMPSON JAMES FU BING JIE MA JASON BERLER STEVEN BOORTZ JULIA NEPOMNYASHCHIY ILYA SMALIY ALEX |
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 analyses (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 |
fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_US2016006749A1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>US2016006749A1</sourcerecordid><originalsourceid>FETCH-epo_espacenet_US2016006749A13</originalsourceid><addsrcrecordid>eNrjZDDy9AtxDfJz9FHwdfQJdwxyVXBxDHFU8Axx9VVw9gkNBkp6-rkrOPq5ALGjT2SwZzAPA2taYk5xKi-U5mZQdnMNcfbQTS3Ij08tLkhMTs1LLYkPDTYyMDQzMDAzN7F0NDQmThUADUwnuQ</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>INTERNAL MALWARE DATA ITEM CLUSTERING AND ANALYSIS</title><source>esp@cenet</source><creator>HARRIS MICHAEL ; KROSS MICHAEL ; GROSSMAN JACK ; SPRAGUE MATTHEW ; COHEN DAVID ; MENON PARVATHY ; BOROCHOFF ADAM ; THOMPSON JAMES ; FU BING JIE ; MA JASON ; BERLER STEVEN ; BOORTZ JULIA ; NEPOMNYASHCHIY ILYA ; SMALIY ALEX</creator><creatorcontrib>HARRIS MICHAEL ; KROSS MICHAEL ; GROSSMAN JACK ; SPRAGUE MATTHEW ; COHEN DAVID ; MENON PARVATHY ; BOROCHOFF ADAM ; THOMPSON JAMES ; FU BING JIE ; MA JASON ; BERLER STEVEN ; BOORTZ JULIA ; NEPOMNYASHCHIY ILYA ; SMALIY ALEX</creatorcontrib><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 analyses (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>CALCULATING ; COMPUTING ; COUNTING ; ELECTRIC COMMUNICATION TECHNIQUE ; ELECTRIC DIGITAL DATA PROCESSING ; ELECTRICITY ; PHYSICS ; TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION</subject><creationdate>2016</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=20160107&DB=EPODOC&CC=US&NR=2016006749A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20160107&DB=EPODOC&CC=US&NR=2016006749A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>HARRIS MICHAEL</creatorcontrib><creatorcontrib>KROSS MICHAEL</creatorcontrib><creatorcontrib>GROSSMAN JACK</creatorcontrib><creatorcontrib>SPRAGUE MATTHEW</creatorcontrib><creatorcontrib>COHEN DAVID</creatorcontrib><creatorcontrib>MENON PARVATHY</creatorcontrib><creatorcontrib>BOROCHOFF ADAM</creatorcontrib><creatorcontrib>THOMPSON JAMES</creatorcontrib><creatorcontrib>FU BING JIE</creatorcontrib><creatorcontrib>MA JASON</creatorcontrib><creatorcontrib>BERLER STEVEN</creatorcontrib><creatorcontrib>BOORTZ JULIA</creatorcontrib><creatorcontrib>NEPOMNYASHCHIY ILYA</creatorcontrib><creatorcontrib>SMALIY ALEX</creatorcontrib><title>INTERNAL 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. 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 analyses (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><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC COMMUNICATION TECHNIQUE</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>ELECTRICITY</subject><subject>PHYSICS</subject><subject>TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2016</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZDDy9AtxDfJz9FHwdfQJdwxyVXBxDHFU8Axx9VVw9gkNBkp6-rkrOPq5ALGjT2SwZzAPA2taYk5xKi-U5mZQdnMNcfbQTS3Ij08tLkhMTs1LLYkPDTYyMDQzMDAzN7F0NDQmThUADUwnuQ</recordid><startdate>20160107</startdate><enddate>20160107</enddate><creator>HARRIS MICHAEL</creator><creator>KROSS MICHAEL</creator><creator>GROSSMAN JACK</creator><creator>SPRAGUE MATTHEW</creator><creator>COHEN DAVID</creator><creator>MENON PARVATHY</creator><creator>BOROCHOFF ADAM</creator><creator>THOMPSON JAMES</creator><creator>FU BING JIE</creator><creator>MA JASON</creator><creator>BERLER STEVEN</creator><creator>BOORTZ JULIA</creator><creator>NEPOMNYASHCHIY ILYA</creator><creator>SMALIY ALEX</creator><scope>EVB</scope></search><sort><creationdate>20160107</creationdate><title>INTERNAL MALWARE DATA ITEM CLUSTERING AND ANALYSIS</title><author>HARRIS MICHAEL ; KROSS MICHAEL ; GROSSMAN JACK ; SPRAGUE MATTHEW ; COHEN DAVID ; MENON PARVATHY ; BOROCHOFF ADAM ; THOMPSON JAMES ; FU BING JIE ; MA JASON ; BERLER STEVEN ; BOORTZ JULIA ; NEPOMNYASHCHIY ILYA ; SMALIY ALEX</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US2016006749A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2016</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC COMMUNICATION TECHNIQUE</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>ELECTRICITY</topic><topic>PHYSICS</topic><topic>TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION</topic><toplevel>online_resources</toplevel><creatorcontrib>HARRIS MICHAEL</creatorcontrib><creatorcontrib>KROSS MICHAEL</creatorcontrib><creatorcontrib>GROSSMAN JACK</creatorcontrib><creatorcontrib>SPRAGUE MATTHEW</creatorcontrib><creatorcontrib>COHEN DAVID</creatorcontrib><creatorcontrib>MENON PARVATHY</creatorcontrib><creatorcontrib>BOROCHOFF ADAM</creatorcontrib><creatorcontrib>THOMPSON JAMES</creatorcontrib><creatorcontrib>FU BING JIE</creatorcontrib><creatorcontrib>MA JASON</creatorcontrib><creatorcontrib>BERLER STEVEN</creatorcontrib><creatorcontrib>BOORTZ JULIA</creatorcontrib><creatorcontrib>NEPOMNYASHCHIY ILYA</creatorcontrib><creatorcontrib>SMALIY ALEX</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>HARRIS MICHAEL</au><au>KROSS MICHAEL</au><au>GROSSMAN JACK</au><au>SPRAGUE MATTHEW</au><au>COHEN DAVID</au><au>MENON PARVATHY</au><au>BOROCHOFF ADAM</au><au>THOMPSON JAMES</au><au>FU BING JIE</au><au>MA JASON</au><au>BERLER STEVEN</au><au>BOORTZ JULIA</au><au>NEPOMNYASHCHIY ILYA</au><au>SMALIY ALEX</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>INTERNAL MALWARE DATA ITEM CLUSTERING AND ANALYSIS</title><date>2016-01-07</date><risdate>2016</risdate><abstract>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 analyses (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.</abstract><oa>free_for_read</oa></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | |
ispartof | |
issn | |
language | eng |
recordid | cdi_epo_espacenet_US2016006749A1 |
source | esp@cenet |
subjects | CALCULATING COMPUTING COUNTING ELECTRIC COMMUNICATION TECHNIQUE ELECTRIC DIGITAL DATA PROCESSING ELECTRICITY PHYSICS TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION |
title | INTERNAL MALWARE DATA ITEM CLUSTERING AND ANALYSIS |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-06T11%3A53%3A28IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=HARRIS%20MICHAEL&rft.date=2016-01-07&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EUS2016006749A1%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |