Visible to the public Biblio

Filters: Author is Limniotis, Konstantinos  [Clear All Filters]
2017-09-15
Iosifidis, Efthymios, Limniotis, Konstantinos.  2016.  A Study of Lightweight Block Ciphers in TLS: The Case of Speck. Proceedings of the 20th Pan-Hellenic Conference on Informatics. :64:1–64:5.

Application of lightweight block ciphers in the TLS protocol is studied in this paper. More precisely, since the use of lightweight cryptographic algorithms is prerequisite for addressing security in highly constrained environments such as the Internet of Things, we focus on the behavior of the TLS performance in case that AES is being replaced by a lightweight block cipher; to this end, the recently proposed Speck cipher is being used as a case study. Experimental results exhibit that significant gain in performance can be achieved in such constrained environments, whereas in some cases Speck with larger key size than AES may also result in higher throughput.

2019-10-23
Kontogeorgis, Dimitrios, Limniotis, Konstantinos, Kantzavelou, Ioanna.  2018.  An Evaluation of the HTTPS Adoption in Websites in Greece: Estimating the Users Awareness. Proceedings of the 22Nd Pan-Hellenic Conference on Informatics. :46-51.

The adoption of the HTTPS - i.e. HTTP over TLS - protocol by the Hellenic websites is studied in this work. Since this protocol constitutes a de-facto standard for secure communications in the web, our aim is to identify whether the underlying TLS protocol in popular websites in Greece is properly configured, so as to avoid known vulnerabilities. To this end, a systematic approach utilizing two well-known TLS scanner tools is adopted to evaluate 241 sites of high popularity. The results illustrate that only about half of the sites seem to be at a satisfactory level and, thus, there is still much room for improvement, mainly due to the fact that obsolete ciphers and/or protocol versions are still supported; there is also a small portion - i.e. about 3% of the sites - that do not implement the HTTPS at all, thus posing very high security risks for their users who provide their credentials via a totally insecure channel. We also examined, using an appropriate online questionnaire, whether the users are actually aware of what the HTTPS means and how they check the security of the websites. The outcome of this research shows that much work needs to be done to increase the knowledge and the security awareness of an average Internet user.

2020-02-24
Brotsis, Sotirios, Kolokotronis, Nicholas, Limniotis, Konstantinos, Shiaeles, Stavros, Kavallieros, Dimitris, Bellini, Emanuele, Pavué, Clément.  2019.  Blockchain Solutions for Forensic Evidence Preservation in IoT Environments. 2019 IEEE Conference on Network Softwarization (NetSoft). :110–114.
The technological evolution brought by the Internet of things (IoT) comes with new forms of cyber-attacks exploiting the complexity and heterogeneity of IoT networks, as well as, the existence of many vulnerabilities in IoT devices. The detection of compromised devices, as well as the collection and preservation of evidence regarding alleged malicious behavior in IoT networks, emerge as areas of high priority. This paper presents a blockchain-based solution, which is designed for the smart home domain, dealing with the collection and preservation of digital forensic evidence. The system utilizes a private forensic evidence database, where the captured evidence is stored, along with a permissioned blockchain that allows providing security services like integrity, authentication, and non-repudiation, so that the evidence can be used in a court of law. The blockchain stores evidences' metadata, which are critical for providing the aforementioned services, and interacts via smart contracts with the different entities involved in an investigation process, including Internet service providers, law enforcement agencies and prosecutors. A high-level architecture of the blockchain-based solution is presented that allows tackling the unique challenges posed by the need for digitally handling forensic evidence collected from IoT networks.