A Cyber Physical System (CPS) consists of cyber components for computation and communication, and physical components such as sensors and actuators for process control. These components are networked and interact in a feedback loop. CPS are found in critical infrastructure such as water distribution, power grid, and mass transportation. Often these systems are vulnerable to attacks as the cyber components such as Supervisory Control and Data Acquisition workstations, Human Machine Interface and Programmable Logic Controllers are potential targets for attackers. In this work, we report a study to investigate the impact of cyber attacks on a water distribution (WADI) system. Attacks were designed to meet attacker objectives and launched on WADI using a specially designed tool. This tool enables the launch of single and multi-point attacks where the latter are designed to specifically hide one or more attacks. The outcome of the experiments led to a better understanding of attack propagation and behavior of WADI in response to the attacks as well as to the design of an attack detection mechanism for water distribution system.
Attacks have been modeled as noise in sensor data , @cite_49 . Attack models designed specifically for CPS include a variety of deception attacks including surge, bias, and geometric , @cite_3 . Such models have been used in experiments to understand the effectiveness of statistical techniques in detecting cyber attacks. The attacks designed in this work are based on a cyber-physical attacker model , @cite_21 . @cite_43 proposed a detailed procedure for modeling cyber systems using attack graphs. Such graphs model practical vulnerabilities in distributed networked systems. , @cite_24 have proposed argument graphs as a means to capture the workflow in a CPS. The graphs are intended to assess a system in the presence of an attacker. The graphs are formed based on information in the workflow such as use case or state, physical system topology such as network type, and an attacker model such as an order to interrupt, power supply, physical tampering, network connection, denial of service, etc. Typed graphs , @cite_35 and Bayesian defense graphs , @cite_30 are a few other important contributions to the modeling of cyber attacks.
@cite_30 @cite_35 @cite_21 @cite_3 @cite_24 @cite_43 @cite_49
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An attacker model is proposed for Cyber Physical Systems (CPS). The attack models derived from the attacker model are used to generate parameterized attack procedures and functions that target a specific CPS. The proposed models capture both physical and cyber attacks and unify a number of existing attack models into a common framework useful for researchers in the experimental assessment of attack detection techniques. The generality of the models is shown by mapping a broad variety of existing attack models to the models proposed here, as well as generating attacks that are not found in the CPS design literature. The models have been used extensively in understanding the impact of cyber attacks on a water treatment system and in the design and assessment of detection mechanisms. In this paper we advocate the use of workflow---describing how a system provides its intended functionality---as a pillar of cybersecurity analysis and propose a holistic workflow-oriented assessment framework. While workflow models are currently used in the area of performance and reliability assessment, these approaches are designed neither to assess a system in the presence of an active attacker, nor to assess security aspects such as confidentiality. On the other hand, existing security assessment methods typically focus on modeling the active attacker (e.g., attack graphs), but many rely on restrictive models that are not readily applicable to complex (e.g., cyber-physical or cyber-human) systems. By "going with the flow," our assessment framework can naturally adopt a holistic view of such systems, unifying information about system components, their properties, and possible attacks to argue about a security goal. The argument is expressed in a graph structure, based on inputs from several distinct classes that are integrated in a systematic manner. That rigorous structure allows our approach to provide quantitative assessment in an automated fashion (like reliability assessment tools and attack graphs), while maintaining a broad assessment scope. We demonstrate our security assessment process using the case of Advanced Metering Infrastructure in a smart power grid and obtain quantitative results for system availability and confidentiality. Security of Cyber-Physical Systems (CPS) against cyber attacks is an important yet challenging problem. Since most cyber attacks happen in erratic ways, it is difficult to describe them systematically. In this paper, instead of identifying a specific cyber attack model, we are focused on analyzing the system's response during cyber attacks. Deception attacks (or false data injection attacks), which are performed by tampering with system components or data, are not of particular concern if they can be easily detected by the system's monitoring system. However, intelligent cyber attackers can avoid being detected by the monitoring system by carefully design cyber attacks. Our main objective is to investigate the performance of such stealthy deception attacks from the system's perspective. We investigate three kinds of stealthy deception attacks according to the attacker's ability to compromise the system. Based on the information about the dynamics of the system and existing hypothesis testing algorithms, we derive the necessary and sufficient conditions under which the attacker could perform each kind of attack without being detected. In the end, we illustrate the threat of these cyber attacks using an Unmanned Aerial Vehicle (UAV) navigation example. A distributed detection method is proposed to detect single stage multi-point (SSMP) attacks on a Cyber Physical System (CPS). Such attacks aim at compromising two or more sensors or actuators at any one stage of a CPS and could totally compromise a controller and prevent it from detecting the attack. However, as demonstrated in this work, using the flow properties of water from one stage to the other, a neighboring controller was found effective in detecting such attacks. The method is based on physical invariants derived for each stage of the CPS from its design. The attack detection effectiveness of the method was evaluated experimentally against an operational water treatment testbed containing 42 sensors and actuators. Results from the experiments point to high effectiveness of the method in detecting a variety of SSMP attacks but also point to its limitations. Distributing the attack detection code among various controllers adds to the scalability of the proposed method.