Biblio

Currently, due to improvements in defensive systems network covert channels are increasingly drawing attention of cybercriminals and malware developers as they can provide stealthiness of the malicious communication and thus to bypass existing security solutions. On the other hand, the utilized data hiding methods are getting increasingly sophisticated as the attackers, in order to stay under the radar, distribute the covert data among many connections, protocols, etc. That is why, the detection of such threats becomes a pressing issue. In this paper we make an initial step in this direction by presenting a data mining-based detection of such advanced threats which relies on pattern discovery technique. The obtained, initial experimental results indicate that such solution has potential and should be further investigated.

Currently 5G communication networks are gaining on importance among industry, academia, and governments worldwide as they are envisioned to offer wide range of high-quality services and unfaltering user experiences. However, certain security, privacy and trust challenges need to be addressed in order for the 5G networks to be widely welcomed and accepted. That is why in this paper, we take a step towards these requirements and we introduce a dedicated SDN-based integrated security framework for the Internet of Radio Light (IoRL) system that is following 5G architecture design. In particular, we present how TCP SYN-based scanning activities which typically comprise the first phase of the attack chain can be detected and mitigated using such an approach. Enclosed experimental results prove that the proposed security framework has potential to become an effective defensive solution.