Emerging cyber-physical systems incorporate systems of systems that have functional interdependencies. With the increase in complexity of the cyberphysical systems, the attack surface also expands, making cyber-physical systems more vulnerable to cyber-attacks. The functional interdependencies exacerbate the security risk as a cyber-attack that compromises one constituent system of a cyber-physical system can disseminate to others. This can result in a cascade effect that can impair the operability of the whole cyber-physical system. In this article, we present a novel security architecture that localizes the cyber-attack in a timely manner, and simultaneously recovers the affected cyber-physical system functionality.We have evaluated the performance of the architecture for advanced metering infrastructure-based pricing cyber-attacks scenario. The simulation results exhibit the effectiveness of the proposed architecture in containing the attack in terms of system availability and its impact on the electric load distribution in the power grid.

Wi-Fi or wireless local area networks (WLANs) are among the most popular wireless internet access technologies used. The major challenge faced by WLANs is the provision of quality of service (QoS) for real-time applications at high congestion periods. IEEE 802.11e draft presents the only comprehensive QoS infrastructure for WLANs which proposes enhanced distributed channel access (EDCA) that propounds the prioritization of medium access for different traffic classes. EDCA while making perceptible improvements for real-time applications neglects non-real-time applications by allocating their share of the bandwidth to the former in an inefficient manner. In our study, we have found that there are considerable design improvements possible for IEEE 802.11e-based QoS propositions. This paper proposes a novel medium access and transmission mechanism for IEEE 802.11 WLANs that is specifically designed to ensure QoS for triple play services. Based on our study regarding the traffic characteristics of triple play services, we propose a mechanism that adaptively uses the medium access and transmission parameters according to the traffic characteristics of the applications, for better utilization of the available bandwidth. The mechanism also proffers higher medium access priority to the access point as compared to the stations in order to cope with the issue of uplink/downlink traffic asymmetry. Simulation-based analysis of the proposed mechanism compares its performance with EDCA. The proposed mechanism offers promising results in terms of packet loss, packet delay and throughput, and thus ensures QoS for voice, video and data transfer applications.

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The increase in scale of cyber networks and the rise in sophistication of cyber-attacks have introduced several challenges in intrusion detection. The primary challenge is the requirement to detect complex multi-stage attacks in realtime by processing the immense amount of traffic produced by present-day networks. In this paper we present PRISM, a hierarchical intrusion detection architecture that uses a novel attacker behavior model-based sampling technique to minimize the realtime traffic processing overhead. PRISM has a unique multi-layered architecture that monitors network traffic distributedly to provide efficiency in processing and modularity in design. PRISM employs a Hidden Markov Model-based prediction mechanism to identify multi-stage attacks and ascertain the attack progression for a proactive response. Furthermore, PRISM introduces a stream management procedure that rectifies the issue of alert reordering when collected from distributed alert reporting systems. To evaluate the performance of PRISM, multiple metrics has been proposed, and various experiments have been conducted on a multi-stage attack dataset. The results exhibit up to 7.5x improvement in processing overhead as compared to a standard centralized IDS without the loss of prediction accuracy while demonstrating the ability to predict different attack stages promptly.