Biblio

Multiple-input multiple-output (MIMO) techniques are currently the de facto approach for increasing the capacity and reliability of communication systems. Spatial modulation (SM) is presently one of the most eminent MIMO techniques. As, it combines the advantages of having higher spectral efficiency than repetition coding (RC) while overcoming the inter-channel interference (ICI) faced by spatial multiplexing (SMP). Moreover, SM reduces system complexity. In this paper, for the first time in literature, the use of MIMO techniques is explored in Internet-of-Things(IoT) deployments by introducing a novel technique called security aware spatial modulation (SA-SM).SA-SM provides a low complexity, secure and spectrally efficient technique that harvests the advantages of SM, while facing the arising security concerns of IoT systems. Using an undemanding modification at the receiver, SA-SM gives an extra degree of technology independent physical layer security. Our results show that SA-SM forces the bit-error-rate (BER) of an eavesdropper to not exceed the range of 10-2, which is below the forward-error-correction (FEC) threshold. Hence, it eradicates the ability of an eavesdropper to properly decode the transmitted signal. Additionally, the efficiency of SA-SM is verified in both the radio and visible light ranges. Furthermore, SA-SM is capable of reducing the peak-to-average-power-ratio (PAPR) by 26.2%.

Safety and security of complex critical infrastructures are very important for economic, environmental and social reasons. The complexity of these systems introduces difficulties in the identification of safety and security risks that emerge from interdisciplinary interactions and dependencies. The discovery of safety and security design weaknesses late in the design process and during system operation can lead to increased costs, additional system complexity, delays and possibly undesirable compromises to address safety and security weaknesses.

Information and communication technologies have augmented interoperability and rapidly advanced varying industries, with vast complex interconnected networks being formed in areas such as safety-critical systems, which can be further categorised as critical infrastructures. What also must be considered is the paradigm of the Internet of Things which is rapidly gaining prevalence within the field of wireless communications, being incorporated into areas such as e-health and automation for industrial manufacturing. As critical infrastructures and the Internet of Things begin to integrate into much wider networks, their reliance upon communication assets by third parties to ensure collaboration and control of their systems will significantly increase, along with system complexity and the requirement for improved security metrics. We present a critical analysis of the risk assessment methods developed for generating attack graphs. The failings of these existing schemas include the inability to accurately identify the relationships and interdependencies between the risks and the reduction of attack graph size and generation complexity. Many existing methods also fail due to the heavy reliance upon the input, identification of vulnerabilities, and analysis of results by human intervention. Conveying our work, we outline our approach to modelling interdependencies within large heterogeneous collaborative infrastructures, proposing a distributed schema which utilises network modelling and attack graph generation methods, to provide a means for vulnerabilities, exploits and conditions to be represented within a unified model.