A. Fundamental Research
High level report of result or partial result that helped move security science forward-- In most cases it should point to a "hard problem". These are the most important research accomplishments of the Lablet in the previous quarter.

Uncertainty in Security Analysis

• We applied risk analysis to cyber security incident response, with a focus on understanding and quantifying (i) the impact of uncertainty on detecting and containing compromised hosts and (ii) the tradeoff between observability (being able to fully scope an attack, which takes considerable amount of time) and timeliness (being able to act quickly and effectively, despite the lack of information).
• We are developing Bayesian models to answer the two questions above. We also utilized the uncertain attack graph developed in the previous quarters as a core component of the Bayesian models for modeling multi-step attacks.

An Automated Synthesis Framework for Network Security and Resilience

• We continue to study the interdependence between the power system and the communication network to improve resilience in critical energy infrastructures, which addresses the resilient architecture hard problem. In the current quarter, we validated our simulation model. We used power grid models following the standard systems (e.g., IEEE 123-node system, Ckt-7 system) and the associated communication network model following an industry documentation. We measured the load pickup time and amount and observed that the restoration time and load of each node block is the same. Our paper "Distribution Grid Restoration with Power-Communication Interdependency" received the second-round review comments (minor revision) from IEEE Transactions on Smart Grid. Currently, we are addressing the review comments and plan to submit a revised manuscript in January 2022.
• We continue to develop a simulation-based platform for cyber-physical system resilience and security evaluation, which addresses the resilient architecture and scalability hard problem. In the current quarter, we formulated an analytical model of the virtual time advancement mechanism and proposed a time compensation mechanism to improve temporal fidelity of the testbed. We implemented the mechanism in Linux kernel to precisely control time advancement by considering the non-CPU task waiting time. We also conducted extensive experiments for error analysis and system evaluation. We are currently working on a large-scale case study on a block chain application for demonstration. We are preparing a manuscript describing this work, and plan to submit it to ACM SIGSIM-PADS in January 2022.
• We start a new project to explore methods to detect and mitigate attacks caused by IoT botnet in the context of smart grid to address the resilient architecture hard problem. In the current quarter, we propose an SDN-based IoT network architecture and a machine learning based detection model to identify the suspicious attack packets generated from the bots. We are also developing an optimization-based mitigation scheme to isolate IoT bots and to recover the power system from potential power system failures.

Resilient Control of Cyber-Physical Systems with Distributed Learning

• We have developed and implemented a nearly sample-optimal algorithm for statistical model checking of markov decision processes. This advances the state of the art in achieving resiliency (hard problem)  as optimal data usage for verification makes the algorithms effective for offline analysis of autonomous system design as well as on board monitoring.
• We have developed a collection of benchmarks for comparing our approach with existing model checking tools such as Prism, Storm, and Plasma Lab that are also used for security and resiliency analysis of autonomous and cyber-physical systems.

B. Community Engagement(s)
Research interaction in the community including workshops, seminars, competitions, etc.

• Matthew Caesar will serve on the Program Committee for USENIX NSDI 2023.
• Matthew Caesar is serving on the Program Committee for USENIX NSDI 2022.
• Matthew Caesar is serving as a co-chair for the Networking Channel (https://networkingchannel.eu/), an online talk series for computer networking, systems, and security topics that is a joint initiative between EU's Empower initiative, the National Science Foundation's PAWR office, and ACM SIGCOMM. Talks are held online and are open to all, to provide broad reach into the community.
• Kevin Jin will serve on the Program Committee for Workshop on ns-3 (WNS3) 2022.
• Matthew Caesar is serving as the Sponsor Chair for ACM SIGCOMM 2022.
• Kevin Jin is serving as a Program Co-chair for ACM SIGSIM-PADS 2022.
• Kevin Jin served as a panelist in the “Dynamic Data-Driven Application Systems” track at the 2021 INFORMS Annual Meeting, October 2021.
• Sayan Mitra is serving as the General Chair of HoTSoS 22.
• Sayan Mitra participated in virtual roundtable on “Formal methods for cyber-physical systems”, appeared in the IEEE Computer magazine, 2021.

Publications

Otto Piramuthu, Matthew Caesar, Towards a Lightweight VANET Authentication Protocol, ACM SIGAPP Symposium on Applied Computing, April 2022.

Otto Piramuthu, Matthew Caesar, Ling Ren, UAV/VANET Authentication for Real Time Highway Surveillance, ACM SIGAPP Symposium on Applied Computing, April 2022.

Otto Piramuthu, Matthew Caesar, How Effective are Identification Technologies in Autonomous Self-Driving Vehicles?, IEEE CommNet, December 2021.

NeuReach: Learning Reachability Functions from Simulations.
Dawei Sun and Sayan Mitra, To appear in the proceedings of Int. Conf. on Tools and Algorithms for Construction and Analysis of Systems (TACAS), 2022.

Multi-agent Motion Planning from Signal Temporal Logic Specifications.
Dawei Sun, Jingkai Chen, Sayan Mitra, Chuchu Fan to appear in the proceedings of IEEE Robotics and Automation
Letters (RA-L), 2022.

Verification and Parameter Synthesis for Stochastic Systems using  Optimistic Optimization, Negin Musavi, Dawei Sun, Sayan Mitra, Sanjay Shakkottai, and Geir Dullerud, to appear in Proceedings of IEEE Conference on Control Technology and Applications (CCTA), September 2021.

Policy Optimization for Markovian Jump Linear Quadratic Control: Gradient-Based Methods and Global Convergence and Parameter Synthesis for Stochastic Systems using  Optimistic Optimization, Joao Jansch-Porto, Bin Hu, and Geir Dullerud, submitted for review, January 2021.

MLEFlow: Learning from His- tory to Improve Load Balancing in Tor, H. Darir, H. Sibai, C.-Y. Cheng, N. Borisov, G.E. Dullerud, and S. Mitra, accepted to Privacy Enhancing Technologies Symposium(PETS), 2022.

Linear Bandit Algorithms with Sublinear Time Complexity, Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit Dhillon and Sujay Sanghavi, submitted for review, 2021.

Multi-Agent Low-Dimensional Linear Bandits, Ronshee Chawla, Abishek Sankararaman, and Sanjay Shakkottai. Submitted for review, 2021.

A Model-free Adversarial Reinforcement Learning Approach for mu Synthesis, by Darioush Keivan, Aaron Havens, Peter Seiler, Geir E. Dullerud, Bin Hu, Submitted for Review.

Revisiting PGD Attack for Stability Analysis of Large-Scale Nonlinear Systems and Perception-Based Control, by Aaron Havens, Darioush Keivan, Peter Seiler, Geir E. Dullerud, Bin Hu, Submitted for Review.

GRILC: Gradient-based Reprogrammable Iterative Learning Control for Autonomous Systems, Kuan-Yu Tseng, Jeff S. Shamma, Geir E. Dullerud, Appeared at NeurIPS Workshop on Deployable Decision Making in Embodied Systems, 2021.

Low-fidelity Gradient Updates for High-fidelity Reprogrammable Iterative Learning Control,  by Kuan-Yu Tseng,  Jeff S. Shamma, Geir E. Dullerud, Submitted for Review.

C. Educational Advances
Impact to courses or curriculum at your school or elsewhere that indicates an increased training or rigor in security research.

• Kevin Jin has developed a new graduate-level class, CSCE5655 Network Security, for the University of Arkansas Global Campus. The class is being offered in Spring 2022.
• Xiaoliang Wu, a Ph.D. student of Kevin Jin, graduated in December 2021, and will join Facebook, working on data center network design and performance evaluation.
• Xiaoliang Wu and Kevin Jin is organizing a Ph.D. colloquium as part of the ACM SIGSIM-PADS conference in June 2022. The Ph.D. colloquium will include a keynote speech, multiple student presentations and a poster session.
• Matthew Caesar has undertaken substantial work to update his Internet of Things MOOC, which reaches over 17,000 students, including development of two new laboratory assignments allowing students to explore cybersecurity of Cisco IOS and core networks, as well as AWS IoT and cloud IoT platforms.
• Matthew Caesar is teaching CS 437: Internet of Things at the University of Illinois, which covers advanced concepts and security practices in IoT, and which will be taught to about 150 on-campus graduates/undergraduates, as well as about 150 graduate students who are part of the Illinois Masters in Computer Science program, many of whom are software development professionals working in companies across many sectors.