Biblio

The assurance of the operability of surface water treatment facilities lies in many factors, but the factor with the largest impact on said assurance is the availability of the necessary chemicals. Facilities across the country vary in their processes and sources, but all require chemicals to produce potable water. The purpose of this project was to develop a risk assessment tool to determine the shortfalls and risks in the water treatment industry's chemical supply chain, which was used to produce a risk mitigation plan ensuring plant operability. To achieve this, a Fault Tree was built to address four main areas of concern: (i) market supply and demand, (ii) chemical substitutability, (iii) chemical transportation, and (iv) chemical storage process. Expert elicitation was then conducted to formulate a Failure Modes and Effects Analysis (FMEA) and develop Radar Charts, regarding the operations and management of specific plants. These tools were then employed to develop a final risk mitigation plan comprising two parts: (i) a quantitative analysis comparing and contrasting the risks of the water treatment plants under study and (ii) a qualitative recommendation for each of the plants-both culminating in a mitigation model on how to control and monitor chemical-related risks.

SCADA/ICS (Supervisory Control and Data Acqui-sition/Industrial Control Systems) networks are becoming targets of advanced multi-faceted attacks, and use of attack-graphs has been proposed to model complex attacks scenarios that exploit interdependence among existing atomic vulnerabilities to stitch together the attack-paths that might compromise a system-level security property. While such analysis of attack scenarios enables security administrators to establish appropriate security measurements to secure the system, practical considerations on time and cost limit their ability to address all system vulnerabilities at once. In this paper, we propose an approach that identifies label-cuts to automatically identify a set of critical-attacks that, when blocked, guarantee system security. We utilize the Strongly-Connected-Components (SCCs) of the given attack graph to generate an abstracted version of the attack-graph, a tree over the SCCs, and next use an iterative backward search over this tree to identify set of backward reachable SCCs, along with their outgoing edges and their labels, to identify a cut with a minimum number of labels that forms a critical-attacks set. We also report the implementation and validation of the proposed algorithm to a real-world case study, a SCADA network for a water treatment cyber-physical system.

This paper provides an approach to the detection of information security breaches in automated process control systems (APCS), which consists in forecasting multivariate time series formed from the values of the operating parameters of the end system devices. Using an experimental model of water treatment, a comparison was made of the forecasting results for the parameters characterizing the operation of the entire model, and for the parameters characterizing the flow of individual subprocesses implemented by the model. For forecasting, GRU-neural network training was performed.

Industrial Control Systems (ICS) are found in critical infrastructure such as for power generation and water treatment. When security requirements are incorporated into an ICS, one needs to test the additional code and devices added do improve the prevention and detection of cyber attacks. Conducting such tests in legacy systems is a challenge due to the high availability requirement. An approach using Timed Automata (TA) is proposed to overcome this challenge. This approach enables assessment of the effectiveness of an attack detection method based on process invariants. The approach has been demonstrated in a case study on one stage of a 6- stage operational water treatment plant. The model constructed captured the interactions among components in the selected stage. In addition, a set of attacks, attack detection mechanisms, and security specifications were also modeled using TA. These TA models were conjoined into a network and implemented in UPPAAL. The models so implemented were found effective in detecting the attacks considered. The study suggests the use of TA as an effective tool to model an ICS and study its attack detection mechanisms as a complement to doing so in a real plant-operational or under design.

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.

Drinking water availability is a crucial problem that must be addressed in order to improve the quality of life of individuals living developing nations. Improving water supply availability is important for public health, as it is the third highest risk factor for poor health in developing nations with high mortality rates. This project researched drinking water filtration for areas of Sub-Saharan Africa near existing bodies of water, where the populations are completely reliant on collecting from surface water sources: the most contaminated water source type. Water filtration methods that can be completely created by the consumer would alleviate aid organization dependence in developing nations, put the consumers in control, and improve public health. Filtration processes pass water through a medium that will catch contaminants through physical entrapment or absorption and thus yield a cleaner effluent. When exploring different materials for filtration, removal of contaminants and hydraulic conductivity are the two most important components. Not only does the method have to treat the water, but also it has to do so in a timeframe that is quick enough to produce potable water at a rate that keeps up with everyday needs. Cement is easily accessible in Sub- Saharan regions. Most concrete mixtures are not meant to be pervious, as it is a construction material used for its compressive strength, however, reduced water content in a cement mixture gives it higher permeability. Several different concrete samples of varying thicknesses and water concentrations were created. Bacterial count tests were performed on both pre-filtered and filtered water samples. Concrete filtration does remove bacteria from drinking water, however, the method can still be improved upon.