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. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection
| Identifer | oai:union.ndltd.org:fau.edu/oai:fau.digital.flvc.org:fau_40745 |
| Contributors | Neshenko, Nataliia (author), Bou-Harb, Elias (Thesis advisor), Florida Atlantic University (Degree grantor), College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science |
| Publisher | Florida Atlantic University |
| Source Sets | Florida Atlantic University |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation, Text |
| Format | 137 p., application/pdf |
| Rights | Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder., http://rightsstatements.org/vocab/InC/1.0/ |
Page generated in 0.0019 seconds