IoT Device Fingerprinting

Juniper Networks Engineering, 2019-20

Liaison(s): Mounir Hahad
Advisor(s): Qimin Yang
Students(s): Jonah Cartwright (TL-S), Jonathan Schallert (TL-F), Leonardo Vilchez (S), Caleb Norfleet (S), Radja Saminada (F), Maia Gibson (F)

The proliferation of IoT devices worldwide comes with increased network vulnerabilities, with unsecured devices potentially capable of exposing personal and corporate information. Therefore, it is essential for Juniper Networks to identify all the IoT devices on a customer’s network. In order to help Juniper Networks accomplish this goal, the Juniper Networks Clinic team has developed an algorithm combining the intrusion detection system, Zeek, and machine learning to fingerprint devices based on behavioral patterns of network traffic.