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...

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Main Authors Pandian, Gnanaprakasam, Doraiswami, Vijayaraghavan, Vinayagam, Vivekanandan, Yang, Sheausong
Format Patent
LanguageEnglish
Published 13.02.2024
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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.
AbstractList 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.
Author Vinayagam, Vivekanandan
Doraiswami, Vijayaraghavan
Yang, Sheausong
Pandian, Gnanaprakasam
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Snippet Machine learning techniques are described for analyzing information network traffic to identify different devices connected to a network. Transmitted network...
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SubjectTerms CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC COMMUNICATION TECHNIQUE
ELECTRICITY
PHYSICS
TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION
Title Network device identification
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