Foundations of a CPS Resilience - July 2019

PI: Xenofon Koutsoukos

HARD PROBLEM(S) ADDRESSED

The goals of this project are to develop the principles and methods for designing and analyzing resilient CPS architectures that deliver required service in the face of compromised components. A fundamental challenge is to understand the basic tenets of CPS resilience and how they can be used in developing resilient architectures. The primary hard problem addressed is resilient architectures. In addition, the work addresses scalability and composability as well as metrics and evaluation.

PUBLICATIONS

[1]  Bradley Potteiger, Zhenkai Zhang, and Xenofon Koutsoukos. Integrated Data Space Randomization and Control Reconfiguration for Securing Cyber-Physical Systems. Symposium and Bootcamp on the Science of Security (HotSoS 2019), Nashville, TN, April 2-3, 2019. 
[2]  Himanshu Neema, Harsh Vardhan, Carlos Barreto, and Xenofon Koutsoukos. Web-based Platform for Evaluation of Resilient and Transactive Smart-Grids. 7th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems. Montreal, Canada, 15 April 2019. 
[3]  Amin Ghafouri, Aron Laszka, Waseem Abbas, Yevgeniy Vorobeychik, and Xenofon Koutsoukos. A Game-Theoretic Approach for Selecting Optimal Time-Dependent Thresholds for Anomaly Detection. Autonomous Agents and Multi-Agent Systems, 33:430-456, 2019.

KEY HIGHLIGHTS

This quarterly report presents two key highlights that demonstrate (1) a game theoretic approach for attack detection in dynamic environments and (2) teaching cybersecurity using networked robots.

Highlight 1: A Game-Theoretic Approach for Selecting Optimal Time-Dependent Thresholds for Anomaly Detection

Adversaries may cause significant damage to smart infrastructure using malicious attacks.
To detect and mitigate these attacks before they can cause physical damage, operators can
deploy anomaly detection systems (ADS), which can alarm operators to suspicious activities. However, detection thresholds of ADS need to be configured properly, as an oversensitive detector raises a prohibitively large number of false alarms, while an undersensitive detector may miss actual attacks. This is an especially challenging problem in dynamical environments, where the impact of attacks may significantly vary over time. Using a game-theoretic approach, we formulate the problem of computing optimal detection thresholds which minimize both the number of false alarms and the probability of missing actual attacks as a two-player Stackelberg security game. We provide an efficient dynamic programming-based algorithm for solving the game, thereby finding optimal detection thresholds. We analyze the performance of the proposed algorithm and show that its running time scales polynomially as the length of the time horizon of interest increases. In addition, we study the problem of finding optimal thresholds in the presence of both random faults and attacks. Finally, we evaluate our result using a case study of contamination attacks in water networks, and show that our optimal thresholds significantly outperform fixed thresholds that do not consider that the environment is dynamical.

[1]  Amin Ghafouri, Aron Laszka, Waseem Abbas, Yevgeniy Vorobeychik, and Xenofon Koutsoukos. A Game-Theoretic Approach for Selecting Optimal Time-Dependent Thresholds for Anomaly Detection. Autonomous Agents and Multi-Agent Systems, 33:430-456, 2019. 
 

Highlight 2: Teaching Cybersecurity with Networked Robots

We have developed RoboScape, a collaborative, networked robotics environment that makes key ideas in computer science accessible to groups of learners in informal learning spaces and K-12 classrooms. RoboScape is built on top of NetsBlox, an open-source, networked, visual programming environment based on Snap! that is specifically designed to introduce students to distributed computation and computer networking. RoboScape provides a twist on the state of the art of robotics learning platforms. First, a user’s program controlling the robot runs in the browser and not on the robot. There is no need to download the program to the robot and hence, development and debugging become much easier. Second, the wireless communication between a student’s program and the robot can be overheard by the programs of the other students. This makes cybersecurity an immediate need that students realize and can work to address. We have designed and delivered a cybersecurity summer camp to 24 students in grades between 7 and 12. The following paper summarizes the technology behind RoboScape, the hands-on curriculum of the camp and the lessons learned.

[2]  Akos Ledeczi, Miklos Maroti, Hamid Zare, Bernard Yett, Nicole Hutchins, Brian Broll, Peter Vogyesi, Michael B. Smith, Timothy Darrah, Mary Metelko, Xenofon Koutsoukos and Gautam Biswas. "Teaching Cybersecurity with Networked Robots". SIGCSE 2019. Minneapolis, MN, Feb. 27 - March 2, 2019.
 

COMMUNITY ENGAGEMENTS

Our research was presented in the HotSoS 2019 and also in CPSWeek 2019.

EDUCATIONAL ADVANCES

RoboScape

We offered two summer camps for high-school students and one summer camp for teachers on CPS security based on Roboscape, a collaborative, networked robotics environment that makes key ideas in computer science accessible to groups of learners in informal learning spaces and K12 classrooms.