Reactive WiFi honeypot
Constantin Nilă, Marius Preda, Ioana Apostol, Victor-Valeriu Patriciu · 2021
Attackers move throughout all environments. They conduct reconnaissance, scan networks, and seek misconfigured and vulnerable stations. This aspect is especially true for wireless networks. As the COVID-19 pandemic pushed numerous employees to conduct business-related tasks over the home network, the WiFi spectrum's protection has become more critical and taken a front seat in developing cybersecurity best practices. Detection of an intruder will not suffice in today's environment. This paper presents our contribution in the form of a WiFi network honeypot. As we limited our framework to exploit artificial intelligence only in detecting aggressors and tailoring a hackback, we concur that machine learning techniques can be applied to answer other shortcomings of our design.