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Conference Paper
Abbas, Waseem, Perelman, Lina Sela, Amin, Saurabh, Koutsoukos, Xenofon.  2015.  An Efficient Approach to Fault Identification in Urban Water Networks Using Multi-Level Sensing. Proceedings of the 2Nd ACM International Conference on Embedded Systems for Energy-Efficient Built Environments. :147–156.

The objective of this work is to develop an efficient and practical sensor placement method for the failure detection and localization in water networks. We formulate the problem as the minimum test cover problem (MTC) with the objective of selecting the minimum number of sensors required to uniquely identify and localize pipe failure events. First, we summarize a single-level sensing model and discuss an efficient fast greedy approach for solving the MTC problem. Simulation results on benchmark test networks demonstrate the efficacy of the fast greedy algorithm. Second, we develop a multi-level sensing model that captures additional physical features of the disturbance event, such as the time lapsed between the occurrence of disturbance and its detection by the sensor. Our sensor placement approach using MTC extends to the multi-level sensing model and an improved identification performance is obtained via reduced number of sensors (in comparison to single-level sensing model). In particular, we investigate the bi-level sensing model to illustrate the efficacy of employing multi-level sensors for the identification of failure events. Finally, we suggest extensions of our approach for the deployment of heterogeneous sensors in water networks by exploring the trade-off between cost and performance (measured in terms of the identification score of pipe/link failures).

Mitra, Aritra, Abbas, Waseem, Sundaram, Shreyas.  2018.  On the Impact of Trusted Nodes in Resilient Distributed State Estimation of LTI Systems. 2018 IEEE Conference on Decision and Control (CDC). :4547—4552.

We address the problem of distributed state estimation of a linear dynamical process in an attack-prone environment. A network of sensors, some of which can be compromised by adversaries, aim to estimate the state of the process. In this context, we investigate the impact of making a small subset of the nodes immune to attacks, or “trusted”. Given a set of trusted nodes, we identify separate necessary and sufficient conditions for resilient distributed state estimation. We use such conditions to illustrate how even a small trusted set can achieve a desired degree of robustness (where the robustness metric is specific to the problem under consideration) that could otherwise only be achieved via additional measurement and communication-link augmentation. We then establish that, unfortunately, the problem of selecting trusted nodes is NP-hard. Finally, we develop an attack-resilient, provably-correct distributed state estimation algorithm that appropriately leverages the presence of the trusted nodes.

Laszka, Aron, Abbas, Waseem, Sastry, S. Shankar, Vorobeychik, Yevgeniy, Koutsoukos, Xenofon.  2016.  Optimal Thresholds for Intrusion Detection Systems. Proceedings of the Symposium and Bootcamp on the Science of Security. :72–81.

In recent years, we have seen a number of successful attacks against high-profile targets, some of which have even caused severe physical damage. These examples have shown us that resourceful and determined attackers can penetrate virtually any system, even those that are secured by the "air-gap." Consequently, in order to minimize the impact of stealthy attacks, defenders have to focus not only on strengthening the first lines of defense but also on deploying effective intrusion-detection systems. Intrusion-detection systems can play a key role in protecting sensitive computer systems since they give defenders a chance to detect and mitigate attacks before they could cause substantial losses. However, an over-sensitive intrusion-detection system, which produces a large number of false alarms, imposes prohibitively high operational costs on a defender since alarms need to be manually investigated. Thus, defenders have to strike the right balance between maximizing security and minimizing costs. Optimizing the sensitivity of intrusion detection systems is especially challenging in the case when multiple inter-dependent computer systems have to be defended against a strategic attacker, who can target computer systems in order to maximize losses and minimize the probability of detection. We model this scenario as an attacker-defender security game and study the problem of finding optimal intrusion detection thresholds.

Abbas, Waseem, Perelman, Lina Sela, Amin, Saurabh, Koutsoukos, Xenofon.  2017.  Resilient Sensor Placement for Fault Localization in Water Distribution Networks. Proceedings of the 8th International Conference on Cyber-Physical Systems. :165–174.

In this paper, we study the sensor placement problem in urban water networks that maximizes the localization of pipe failures given that some sensors give incorrect outputs. False output of a sensor might be the result of degradation in sensor's hardware, software fault, or might be due to a cyber attack on the sensor. Incorrect outputs from such sensors can have any possible values which could lead to an inaccurate localization of a failure event. We formulate the optimal sensor placement problem with erroneous sensors as a set multicover problem, which is NP-hard, and then discuss a polynomial time heuristic to obtain efficient solutions. In this direction, we first examine the physical model of the disturbance propagating in the network as a result of a failure event, and outline the multi-level sensing model that captures several event features. Second, using a combinatorial approach, we solve the problem of sensor placement that maximizes the localization of pipe failures by selecting m sensors out of which at most e give incorrect outputs. We propose various localization performance metrics, and numerically evaluate our approach on a benchmark and a real water distribution network. Finally, using computational experiments, we study relationships between design parameters such as the total number of sensors, the number of sensors with errors, and extracted signal features.

Abbas, Waseem, Laszka, Aron, Vorobeychik, Yevgeniy, Koutsoukos, Xenofon.  2015.  Scheduling Intrusion Detection Systems in Resource-Bounded Cyber-Physical Systems. Proceedings of the First ACM Workshop on Cyber-Physical Systems-Security and/or PrivaCy. :55–66.

In order to be resilient to attacks, a cyber-physical system (CPS) must be able to detect attacks before they can cause significant damage. To achieve this, \emph{intrusion detection systems} (IDS) may be deployed, which can detect attacks and alert human operators, who can then intervene. However, the resource-constrained nature of many CPS poses a challenge, since reliable IDS can be computationally expensive. Consequently, computational nodes may not be able to perform intrusion detection continuously, which means that we have to devise a schedule for performing intrusion detection. While a uniformly random schedule may be optimal in a purely cyber system, an optimal schedule for protecting CPS must also take into account the physical properties of the system, since the set of adversarial actions and their consequences depend on the physical systems. Here, in the context of water distribution networks, we study IDS scheduling problems in two settings and under the constraints on the available battery supplies. In the first problem, the objective is to design, for a given duration of time $T$, scheduling schemes for IDS so that the probability of detecting an attack is maximized within that duration. We propose efficient heuristic algorithms for this general problem and evaluate them on various networks. In the second problem, our objective is to design scheduling schemes for IDS so that the overall lifetime of the network is maximized while ensuring that an intruder attack is always detected. Various strategies to deal with this problem are presented and evaluated for various networks.

Laszka, Aron, Abbas, Waseem, Vorobeychik, Yevgeniy, Koutsoukos, Xenofon.  2017.  Synergic Security for Smart Water Networks: Redundancy, Diversity, and Hardening. Proceedings of the 3rd International Workshop on Cyber-Physical Systems for Smart Water Networks. :21–24.

Smart water networks can provide great benefits to our society in terms of efficiency and sustainability. However, smart capabilities and connectivity also expose these systems to a wide range of cyber attacks, which enable cyber-terrorists and hostile nation states to mount cyber-physical attacks. Cyber-physical attacks against critical infrastructure, such as water treatment and distribution systems, pose a serious threat to public safety and health. Consequently, it is imperative that we improve the resilience of smart water networks. We consider three approaches for improving resilience: redundancy, diversity, and hardening. Even though each one of these "canonical" approaches has been throughly studied in prior work, a unified theory on how to combine them in the most efficient way has not yet been established. In this paper, we address this problem by studying the synergy of these approaches in the context of protecting smart water networks from cyber-physical contamination attacks.