A Network Telescope Approach for Inferring and Characterizing IoT Exploitations

While the seamless interconnection of IoT devices with the physical realm
is envisioned to bring a plethora of critical improvements on many aspects and in
diverse domains, it will undoubtedly pave the way for attackers that will target and
exploit such devices, threatening the integrity of their data and the reliability of
critical infrastructure. The aim of this thesis is to generate cyber threat intelligence
related to Internet-scale inference and evaluation of malicious activities generated by
compromised IoT devices to facilitate prompt detection, mitigation and prevention of
IoT exploitation.
In this context, we initially provide a unique taxonomy, which sheds the light
on IoT vulnerabilities from five di↵erent perspectives. Subsequently, we address the
task of inference and characterization of IoT maliciousness by leveraging active and
passive measurements. To support large-scale empirical data analytics in the context
of IoT, we made available corresponding raw data through an authenticated platform.