VU SoS Lablet Quarterly Executive Summary - July 2020

A. Fundamental Research

The Science of Security for Cyber-Physical Systems (CPS) Lablet focuses on (1) Foundations of CPS Resilience, (2) Analytics for CPS Cybersecurity, (3) Development of a Multi-model Testbed for Simulation–based Evaluation of Resilience, and (4) Mixed Initiative and Collaborative Learning in Adversarial Environments. 

• We study resilient distributed diffusion for multi-task estimation in the presence of adversaries where networked agents must estimate distinct but correlated states of interest by processing streaming data. We show that in general diffusion strategies are not resilient to malicious agents that do not adhere to the diffusion-based information processing rules. In particular, by exploiting the adaptive weights used for diffusing information, we develop time-dependent attack models that drive normal agents to converge to states selected by the attacker. We show that an attacker that has complete knowledge of the system can always drive its targeted agents to its desired estimates. Moreover, an attacker that does not have complete knowledge of the system including streaming data of targeted agents or the parameters they use in diffusion algorithms, can still be successful in deploying an attack by approximating the needed information. The attack models can be used for both stationary and non-stationary state estimation. In addition, we present and analyze a resilient distributed diffusion algorithm that is resilient to any data falsification attack in which the number of compromised agents in the local neighborhood of a normal agent is bounded. The proposed algorithm guarantees that all normal agents converge to their true target states if appropriate parameters are selected. We also analyze trade-off between the resilience of distributed diffusion and its performance in terms of steady-state mean-square-deviation (MSD) from the correct estimates. Finally, we evaluate the proposed attack models and resilient distributed diffusion algorithm using stationary and non-stationary multi-target localization. Our results are reported in [1]. 
• As outlined in our research plan, we refined the foundations for cybersecurity analytics to better: (a) Identify the policy relevant ecosystem; (b) Formalize rules for extracting data from text; and (c) Identify missing pieces for implementation of cybersecurity measures. Our recent work focused on data organization and metrics to: (1) Construct internally consistent structure and framework for organizing, metricizing, and managing critical information and (2) Create an initial base-line design structure matrix of the cyber-physical system.
• Experimentation with Blockchain-based Transactive Energy Systems (TES) has been an ongoing research effort, involving the design and modeling of such systems, developing a novel class of attacks against TES, analyzing the system-level effects and potential mitigation strategies. To support this work, an experimentation platform has been built by integrating GridLAB-D - which simulates the power generation, distribution, and consumption aspects of the smart-grid - with TRANSAX, an in-house developed open-source framework for solving and executing market bids and contracts in a Blockchain-based decentralized energy exchange.

B. Community Engagement(s)

• Our research was presented in the following conferences: ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS 2020), 8th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (held in conjunction with CPS IoT Week 2020), IEEE International Symposium On Real-Time Distributed Computing 2020 (ISORC 2020), IEEE Symposium on Security and Privacy (S&P’20), Workshop on Assured Autonomous Systems (Held in conjunction with IEEE S&P 2020), and 3rd IEEE International Conference on Industrial Cyber-Physical Systems (ICPS 2020). 

C. Educational Advances

• At MIT, we began to explore logistics of organizing a summer program for senior SoS leadership on the topic of Cybersecurity in collaboration with MIT Professional Education. Due to nCOVID-19, we are working on a special online class on Cybersecurity. The class will be offered first to MIT students, and if requested, SoS team members will be invited to audit the class.