The list below contains 8 journal publications, 29 international conference contributions, 3 master theses, 2 licentiate theses, and 9 submitted papers.
[1] Yassir Jedra, Alexandre Proutiere. “Finite-time Identification of Stable Linear Systems
Optimality of the Least-Squares Estimator”, Proc. of CDC 2020.
[2] Yassir Jedra, Alexandre Proutiere, “Sample Complexity Lower Bounds for Linear System Identification”, Proc. of CDC 2019.
[3] Ingvar Ziemann and Yishao Zhou, “Model Reduction of Semi-stable Distributed Parameter Systems,” Proc. of ECC 2019.
[4] Ingvar Ziemann, Henrik Sandberg: “On a Phase Transition of Regret in Linear Quadratic Control: The Memoryless Case”, IEEE Control Systems Letters, 5:2, pp. 695–700, April 2021.
[5] Ingvar Ziemann, Henrik Sandberg: “On Uninformative Optimal Policies in Adaptive LQR with Unknown B-Matrix”, Proceedings of Machine Learning Research vol 144:1–36, 2021.
[6] Rijad Alisic, Henrik Sandberg: “Data-Injection Attacks Using Historical Inputs and Outputs”, Proc. of European Control Conference, 2021.
[7] Ingvar Ziemann: “Applications of Information Inequalities to Linear Systems: Adaptive Control and Security”, Licentiate thesis, KTH, 2021.
[8] Hanxiao Liu, Yuqing Ni, Lihua Xie, Karl H. Johansson, “An Optimal Linear Attack Strategy on Remote State Estimation”, Proc. of IFAC World Congress, Berlin, Germany, 2020.
[9] Alessio Russo and Alexandre Proutiere , “Towards Optimal Attacks in Reinforcement Learning Policies”, Proc. of American Control Conference 2021.
[10] Ezgi Korkmaz, György Dán, Henrik Sandberg, “Bounded Myopic Adversaries for Deep Reinforcement Learning Agents”, submitted 2021.
[11] Alessio Russo and Alexandre Proutiere, “Data poisoning of data-driven controllers”, Proc. of American Control Conference 2021.
[12] Zijian Fan, “Applying Generative Adversarial Networks for the Generation of Adversarial Attacks against Continuous Authentication”, MSc thesis supervised by G. Dan, KTH, 2020.
[13] Maciej Kufel, “Adversarial Attacks against Behavioral-based Continuous Authentication”, MSc thesis supervised by G. Dan, KTH, 2020.
[14] Martin Lindström, Hampei Sasahara, Xingkang He, Henrik Sandberg, Karl H. Johansson, “Power Injection Attacks in Smart Distribution Grids with Photovoltaics,” Proc. of European Control Conference, 2021.
[15] Xiaoqiang Ren, Yilin Mo and Karl H. Johansson, “Secure Static State Estimation: A Large Deviation Approach”, Proc. of 7th IFAC Workshop on Distributed Estimation and Control in Networked Systems (NecSys), Groningen, Netherlands, August 2018.
[16] Xiaoqiang Ren, Yilin Mo, Jie Chen, and Karl H. Johansson, “Secure State Estimation with Byzantine Sensors: A Probabilistic Approach”, IEEE Transactions on Automatic Control, Submitted. Available on arxiv.org.
[17] Xingkang He, Xiaoqiang Ren, Henrik Sandberg, Karl H. Johansson, “Secured filters based on saturated innovations,” a chapter of the book “Security and Resilience of Control Systems: Theory and Applications,” under editing in Springer.
[18] Xingkang He, Xiaoqiang Ren, Henrik Sandberg, Karl H. Johansson, “How to secure distributed filters under sensor attacks,” submitted to IEEE Transactions on Automatic Control.
[19] Hanxiao Liu, Yuqing Ni, Lihua Xie, Karl H. Johansson, “How Vulnerable is Innovation-based Remote State Estimation: Fundamental Limits under Linear Attacks”, Automatica, provisionally accepted as Regular Paper.
[20] Deming Yuan, Alexandre Proutiere, Guodong Shi, “Distributed online linear regressions”, IEEE Trans. on Information Theory, 67 (1), 616—639, 2020.
[21] Deming Yuan, Alexandre Proutiere, Guodong Shi, “Distributed online optimization with long-term constraints”, IEEE Trans. on Automatic Control, 2021.
[22] Xinlei Yi, Xiuxian Li, Lihua Xie, and Karl H. Johansson, “Distributed online convex optimization with time-varying coupled inequality constraints,” IEEE Transactions on Signal Processing 68 (2020): 731-746.
[23] Xinlei Yi, Xiuxian Li, Tao Yang, Lihua Xie, Tianyou Chai, and Karl H. Johansson, “Distributed Bandit Online Convex Optimization with Time-Varying Coupled Inequality Constraints,” submitted to IEEE Transactions on Automatic Control. Available on arxiv.org.
[24] Xinlei Yi, Xiuxian Li, Tao Yang, Lihua Xie, Tianyou Chai, and Karl H. Johansson, “Distributed Bandit Online Convex Optimization with Time-Varying Coupled Inequality Constraints,” IEEE Transactions on Automatic Control, to appear. Available on arxiv.org.
[25] Xinlei Yi, Shengjun Zhang, Tao Yang, Tianyou Chai, and Karl H. Johansson, “A Primal–Dual SGD Algorithm for Distributed Nonconvex Optimization,” submitted to SIAM Journal on Optimization.
[26] Xinlei Yi, Shengjun Zhang, Tao Yang, Tianyou Chai, and Karl H. Johansson, “Linear Convergence of First- and Zeroth-Order Primal–Dual Algorithms for Distributed Nonconvex Optimization,” submitted to IEEE Transactions on Automatic Control.
[27] Xinlei Yi, Shengjun Zhang, Tao Yang, Tianyou Chai, and Karl H. Johansson, “Sublinear and Linear Convergence of ADMM for Distributed Nonconvex Optimization,” submitted to IEEE Transactions on Control of Network Systems.
[28] Alessio Russo, Alexandre Proutiere, “Balancing detectability and performance of attacks on the action channel of Markov Decision Processes”, submitted to NeurIPS 2021.
[29] Hanxiao Liu, Yuchao Li, Jonas Mårtensson, Lihua Xie, and Karl Henrik Johansson, “Reinforcement Learning Based Approach for Flip Attack Detection”, Proc. of 59th Conference on Decision and Control, 2020.
[30] Hanxiao Liu, Yuchao Li, Jonas Mårtensson, Lihua Xie, Karl H. Johansson, “Reinforcement learning-based approach for flip attack detection”, Proc. of the 59th IEEE Conference on Decision and Control (CDC), Jeju, Republic of Korea, December 2020.
[31] Zuxing Li, György Dán, ”Dynamic Cheap Talk for Robust Adversarial Learning,” in Proc. of Intl. Conf. on Decision and Game Theory for Security (GameSec), Oct. 2019.
[32] Xingkang He, Xiaoqiang Ren, Henrik Sandberg, and Karl H. Johansson, “Secure Distributed Filtering for Unstable Dynamics Under Compromised Observations”, Proc. of IEEE Conference on Decision and Control, 2019.
[33] Xingkang He, Ehsan Hashemi, and Karl H. Johansson, “Secure Platooning of Autonomous Vehicles Under Attacked GPS Data”, Proc. of IEEE Conference on Decision and Control, 2020.
[34] Elis Stefansson, Jaime F. Fisac, Dorsa Sadigh, S. Shankar Sastry, Karl H. Johansson, “Human-robot interaction for truck platooning using hierarchical dynamic games”, Proc. of ECC 2019.
[35] Jaime F. Fisac, Eli Bronstein, Elis Stefansson, Dorsa Sadigh, S. Shankar Sastry, Anca D. Dragan, “Hierarchical Game-Theoretic Planning for Autonomous Vehicles”, Proc. of ICRA 2019.
[36] Ingvar Ziemann, Henrik Sandberg, ”Parameter Privacy versus Control Performance: Fisher Information Regularized Control”, Proc. of American Control Conference, 2020.
[37] Elis Stefansson and Karl H. Johansson, “Computing Complexity-aware Plans Using Kolmogorov Complexity”, Proc. of Conference on Decision and Control (CDC) 2021.
[38] Serkan Saritas, Ezzeldidn Shereen, Henrik Sandberg, György Dán, ”Adversarial Attacks on Continuous Authentication Security: A Dynamic Game Approach,” Proc. of Intl. Conf. on Decision and Game Theory for Security (GameSec), Oct. 2019.
[39] Ingvar Ziemann, Henrik Sandberg: “Resource Constrained Sensor Attacks by Minimizing Fisher Information”, Proc. of American Control Conference, 2021.
[40] Zuxing Li, György Dán, Dong Liu, “A Game Theoretic Analysis of LQG Control under Adversarial Attack”, in Proc. of IEEE CDC, 2020.
[41] Elis Stefansson, Frank J. Jiang, Ehsan Nekouei, Håkan Nilsson, and Karl H. Johansson, “Modeling the decision-making in human driver overtaking”, Proc. of IFAC World Congress, Berlin, Germany, 2020.
[42] Marco Molinari, Davide Rolando, “Digital twin of the Live-In LabTestbed KTH: development and calibration”, selected for publication in the proceedings of International Conference Organised by IBPSA-Nordic, October 13 – October 14, 2020, OsloMet ISSN 2387-4295 (online) url:https://www.sintefbok.no/book/index/1264/buildsim-nordic_2020_selected_papers.
[43] Davide Rolando, Marco Molinari, “Development of a comfort platform for user feedback: the experience of the KTH Live-In Lab” – 12th International Conference on Applied Energy Dec. 1- Dec.10, 2020, Bangkok/Virtual (ICAE2020).
[44] Marco Molinari, Jonas Anund Vogel and Davide Rolando, “Using Living Labs to tackle innovation bottlenecks: the KTH Live-In Lab case study”, International Conference on Applied Energy, Applied Energy Symposium, MIT A+B, August 11-13, 2021, MIT Boston, USA.
[45] Rijad Alisic, Marco Molinari, Philip E. Pare, and Henrik Sandberg, “Bounding Privacy Leakage in Smart Buildings”, Proc. of IEEE Conference on Control Technology and Applications (CCTA), 2020.
[46] Rijad Alisic, Marco Molinari, Philip E. Pare, and Henrik Sandberg, “Maximizing Privacy in MIMO Cyber-Physical Systems Using the Chapman-Robbins Bound”, Proc. of IEEE Conference on Decision and Control, 2020.
[47] Alessio Russo, Marco Molinari and Alexandre Proutiere, “Data poisoning of data-driven controllers: the KTH Live-in Lab use-case”, Proc. of Mediterranean Control Conference 2021.
[48] Kevin Ammouri, “Deep Reinforcement Learning for Temperature Control in Buildings and Adversarial Attacks”, MSc supervised by Alessio Russo, KTH, 2021.
[49] Alanwar, Amr, Anne Koch, Frank Allgöwer, and Karl Henrik Johansson. “Data-Driven Reachability Analysis from Noisy Data”. arXiv preprint arXiv:2105.07229 (2021).Submitted to Transaction of Automatic control.
[50] Junsoo Kim, Hyungbo Shim, Henrik Sandberg, and Karl H. Johansson, “Method for Running Dynamic Systems over Encrypted Data for Infinite Time Horizon without Bootstrapping and Re-encryption”, Proc. of CDC 2021.
[51] Rijad Alisic: “Privacy of Sudden Events in Cyber-Physical Systems”, Licentiate thesis, 2021