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A water treatment center (WTC) removes contaminants and unwanted components from the water and makes the water more acceptable to the end-users. A modern WTC is equipped with different water sensors and uses a combination of wired/wireless communication network. During the water treatment process, controllers periodically collect sensor measurements and make important operational decisions. Since accuracy is vital, a WTC also uses different data validation mechanisms to validate the incoming sensor measurements. However, like any other cyber-physical system, water treatment facilities are prone to cyberattacks and an intelligent adversary can alter the sensors measurements stealthily, and corrupt the water treatment process. In this work, we propose WTC Checker (WTC2), an impact-aware formal analysis framework that demonstrates the impact of stealthy false data injection attacks on the water treatment sensors. Through our work, we demonstrate that if an adversary has sufficient access to sensor measurements and can evade the data validation process, he/she can compromise the sensors measurements, change the water disinfectant contact time, and inflict damage to the clean water production process. We model this attack as a constraint satisfaction problem (CSP) and encode it using Satisfiability Modulo Theories (SMT). We evaluate the proposed framework for its threat analysis capability as well as its scalability by executing experiments on different synthetic test cases.
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Sensor Selection for Detecting Deviations from a Planned Itinerary
Suppose an agent asserts that it will move through an environment in some way. When the agent executes its motion, how does one verify the claim? The problem arises in a range of contexts including validating safety claims about robot behavior, applications in security and surveillance, and for both the conception and the (physical) design and logistics of scientific experiments. Given a set of feasible sensors to select from, we ask how to choose sensors optimally in order to ensure that the agent's execution does indeed fit its pre-disclosed itinerary. Our treatment is distinguished from prior work in sensor selection by two aspects: the form the itinerary takes (a regular language of transitions) and that families of sensor choices can be grouped as a single choice. Both are intimately tied together, permitting construction of a product automaton because the same physical sensors (i.e., the same choice) can appear multiple times. This paper establishes the hardness of sensor selection for itinerary validation within this treatment, and proposes an exact algorithm based on an integer linear programming (ILP) formulation that is capable of solving problem instances of moderate size. We demonstrate its efficacy on small-scale case studies, including one motivated by wildlife tracking.
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- Award ID(s):
- 1849291
- PAR ID:
- 10333050
- Date Published:
- Journal Name:
- IEEE/RSJ International Conference on Intelligent Robots and Systems
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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