NETWORK DEVICE IDENTIFICATION

NETWORK DEVICE IDENTIFICATION

Machine learning techniques are described for analyzing information network traffic to identify different devices connected to a network. Transmitted network packets may be passively collected and analyzed. In some cases the described techniques may be used to identify distinct devices connected to...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Pandian, Gnanaprakasam, Doraiswami, Vijayaraghavan, Vinayagam, Vivekanandan, Yang, Sheausong
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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 Pandian, Gnanaprakasam
Doraiswami, Vijayaraghavan
Vinayagam, Vivekanandan
Yang, Sheausong
description Machine learning techniques are described for analyzing information network traffic to identify different devices connected to a network. Transmitted network packets may be passively collected and analyzed. In some cases the described techniques may be used to identify distinct devices connected to a network even though the collected and analyzed packets may lack a unique device identifier, such as a media access control (MAC) identifier, corresponding to a device that originated the packets.
format Patent
fullrecord <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_US2022159039A1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>US2022159039A1</sourcerecordid><originalsourceid>FETCH-epo_espacenet_US2022159039A13</originalsourceid><addsrcrecordid>eNrjZJD1cw0J9w_yVnBxDfN0dlXwdHH1C_F083R2DPH09-NhYE1LzClO5YXS3AzKbq4hzh66qQX58anFBYnJqXmpJfGhwUYGRkaGppYGxpaOhsbEqQIAIesiHg</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>NETWORK DEVICE IDENTIFICATION</title><source>esp@cenet</source><creator>Pandian, Gnanaprakasam ; Doraiswami, Vijayaraghavan ; Vinayagam, Vivekanandan ; Yang, Sheausong</creator><creatorcontrib>Pandian, Gnanaprakasam ; Doraiswami, Vijayaraghavan ; Vinayagam, Vivekanandan ; Yang, Sheausong</creatorcontrib><description>Machine learning techniques are described for analyzing information network traffic to identify different devices connected to a network. Transmitted network packets may be passively collected and analyzed. In some cases the described techniques may be used to identify distinct devices connected to a network even though the collected and analyzed packets may lack a unique device identifier, such as a media access control (MAC) identifier, corresponding to a device that originated the packets.</description><language>eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; PHYSICS</subject><creationdate>2022</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&amp;date=20220519&amp;DB=EPODOC&amp;CC=US&amp;NR=2022159039A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20220519&amp;DB=EPODOC&amp;CC=US&amp;NR=2022159039A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Pandian, Gnanaprakasam</creatorcontrib><creatorcontrib>Doraiswami, Vijayaraghavan</creatorcontrib><creatorcontrib>Vinayagam, Vivekanandan</creatorcontrib><creatorcontrib>Yang, Sheausong</creatorcontrib><title>NETWORK DEVICE IDENTIFICATION</title><description>Machine learning techniques are described for analyzing information network traffic to identify different devices connected to a network. Transmitted network packets may be passively collected and analyzed. In some cases the described techniques may be used to identify distinct devices connected to a network even though the collected and analyzed packets may lack a unique device identifier, such as a media access control (MAC) identifier, corresponding to a device that originated the packets.</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2022</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZJD1cw0J9w_yVnBxDfN0dlXwdHH1C_F083R2DPH09-NhYE1LzClO5YXS3AzKbq4hzh66qQX58anFBYnJqXmpJfGhwUYGRkaGppYGxpaOhsbEqQIAIesiHg</recordid><startdate>20220519</startdate><enddate>20220519</enddate><creator>Pandian, Gnanaprakasam</creator><creator>Doraiswami, Vijayaraghavan</creator><creator>Vinayagam, Vivekanandan</creator><creator>Yang, Sheausong</creator><scope>EVB</scope></search><sort><creationdate>20220519</creationdate><title>NETWORK DEVICE IDENTIFICATION</title><author>Pandian, Gnanaprakasam ; Doraiswami, Vijayaraghavan ; Vinayagam, Vivekanandan ; Yang, Sheausong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US2022159039A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2022</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>Pandian, Gnanaprakasam</creatorcontrib><creatorcontrib>Doraiswami, Vijayaraghavan</creatorcontrib><creatorcontrib>Vinayagam, Vivekanandan</creatorcontrib><creatorcontrib>Yang, Sheausong</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Pandian, Gnanaprakasam</au><au>Doraiswami, Vijayaraghavan</au><au>Vinayagam, Vivekanandan</au><au>Yang, Sheausong</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>NETWORK DEVICE IDENTIFICATION</title><date>2022-05-19</date><risdate>2022</risdate><abstract>Machine learning techniques are described for analyzing information network traffic to identify different devices connected to a network. Transmitted network packets may be passively collected and analyzed. In some cases the described techniques may be used to identify distinct devices connected to a network even though the collected and analyzed packets may lack a unique device identifier, such as a media access control (MAC) identifier, corresponding to a device that originated the packets.</abstract><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier
ispartof
issn
language eng
recordid cdi_epo_espacenet_US2022159039A1
source esp@cenet
subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
title NETWORK DEVICE IDENTIFICATION
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-27T17%3A04%3A13IST&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=Pandian,%20Gnanaprakasam&rft.date=2022-05-19&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EUS2022159039A1%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