Haider Al-Khateeb

Gregory Epiphaniou, Petros Karadimas, Dhouha Kbaier Ben Ismail et al.

The physical attributes of the dynamic vehicle-to-vehicle (V2V) propagation channel can be utilised for the generation of highly random and symmetric cryptographic keys. However, in a physical-layer key agreement scheme, non-reciprocity due to inherent channel noise and hardware impairments can propagate bit disagreements. This has to be addressed prior to the symmetric key generation which is inherently important in social Internet of Things (IoT) networks, including in adversarial settings (e.g. battlefields). In this paper, we parametrically incorporate temporal variability attributes, such as three-dimensional (3D) scattering and scatterers mobility. Accordingly, this is the first work to incorporate such features into the key generation process by combining non-reciprocity compensation with turbo codes. Preliminary results indicate a significant improvement when using Turbo Codes in bit mismatch rate (BMR) and key generation rate (KGR) in comparison to sample indexing techniques.

Hamish Haughey, Gregory Epiphaniou, Haider Al-Khateeb et al.

Darknet technology such as Tor has been used by various threat actors for organising illegal activities and data exfiltration. As such, there is a case for organisations to block such traffic, or to try and identify when it is used and for what purposes. However, anonymity in cyberspace has always been a domain of conflicting interests. While it gives enough power to nefarious actors to masquerade their illegal activities, it is also the cornerstone to facilitate freedom of speech and privacy. We present a proof of concept for a novel algorithm that could form the fundamental pillar of a darknet-capable Cyber Threat Intelligence platform. The solution can reduce anonymity of users of Tor, and considers the existing visibility of network traffic before optionally initiating targeted or widespread BGP interception. In combination with server HTTP response manipulation, the algorithm attempts to reduce the candidate data set to eliminate client-side traffic that is most unlikely to be responsible for server-side connections of interest. Our test results show that MITM manipulated server responses lead to expected changes received by the Tor client. Using simulation data generated by shadow, we show that the detection scheme is effective with false positive rate of 0.001, while sensitivity detecting non-targets was 0.016+-0.127. Our algorithm could assist collaborating organisations willing to share their threat intelligence or cooperate during investigations.