Publications funded by the ADAPT MURI'16

João P. Hespanha
This document includes links to several papers based upon research funded by the ONR-funded MURI'16 project "ADAPT: An Analytical Framework For Actionable Defense Against Advanced Persistent Threats." The Principal Investigator (PI) for this project is João P. Hespanha.
The papers are in PDF or compressed (gzip) postscript form. In case of difficulties, please send me an email. Slides are available for many of the conference papers. Please let us know if would like us to post a specific presentation. Technical reports are available here.
This material is based upon work supported by the Army Research Office (ARO). Any opinions, findings and conclusions or recomendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the ARO.

Topics

1. Switched and Hybrid Systems
7. Network Security

8. Distributed Control and Multi-agent Systems
11. Optimization and Optimal Control
12. Game Theory

19. Other

1. Switched and Hybrid Systems

[1] G. Yang, A. James Schmidt, D. Liberzon, J. Hespanha. Topological entropy of switched linear systems: General matrices and matrices with commutation relations. Math. Contr., Signals, Syst.. To appear. [bibtex:YangSchmidtLiberzonHespanha2020] [pdf]

[13] G. Yang, J. Hespanha, D. Liberzon. On topological entropy and stability of switched linear systems. In Proc. of the 22nd ACM Int. Conf. on Hybrid Systems: Computation and Control (HSCC 2019), pages 119—127, Apr. 2019. [bibtex:YangHespanhaLiberzonApr2019] [pdf]

[15] G. Yang, J. Hespanha. On topological entropy of switched linear systems with pairwise-commuting matrices. In Proc. of the 56th Annual Allerton Conf. on Comm., Contr., and Computing, Oct. 2018. [bibtex:YangHespanhaOct18] [pdf]

7. Network Security

[2] J. Hespanha. Sensor Manipulation Games in Cyber Security. In Game Theory and Machine Learning for Cyber Security, Charles A. Kamhoua, Christopher D. Kiekintveld, Fei Fang, Quanyan Zhu (ed.), 2021. To appear. [bibtex:HespanhaDec20] [pdf]

[3] G. Yang, Radha Poovendran, J. Hespanha. Adaptive learning in two-player Stackelberg games with application to network security. Jan. 2021. Submitted to journal publication. [bibtex:YangPoovendranHespanhaJan21] [pdf]

[4] M. Chong, Henrik Sandberg, J. Hespanha. A secure state estimation algorithm for nonlinear systems under sensor attacks. In Proc. of the 59th Conf. on Decision and Contr., Dec. 2020. To appear. [bibtex:ChongHespanhaDec20] [pdf]

[6] David Grimsman, J. Hespanha, Jason R. Marden. Stackelberg Equilibria for Two-Player Network Routing Games on Parallel Networks. In Proc. of the 2020 Amer. Contr. Conf., July 2020. [bibtex:GrimsmanHespanhaMardenJul20] [pdf]

[11] M. Wakaiki, P. Tabuada, J. Hespanha. Supervisory Control of Discrete-event Systems under Attacks. Dynamic Games and Applications, Special Issue on Dynamic Games in Cyber Security, 9(4):965—983, Dec. 2019. [bibtex:WakaikiTabuadaHespanhaDec19] [pdf]

[12] J. Hespanha, S. Bopardikar. Output-feedback linear quadratic robust control under actuation and deception attacks. In Proc. of the 2019 Amer. Contr. Conf., July 2019. [bibtex:HespanhaBopardikarJul19] [pdf]

[16] Y. Wang, J. Hespanha. Distributed Estimation of Power System Oscillation Modes under Attacks on GPS Clocks. IEEE Trans. on Instr. and Measurement, 67(7):1626—1637, July 2018. [bibtex:WangHespanhaJul18] [pdf]

[18] G. Yang, Hossein Hosseini, Dinuka Sahabandu, Andrew Clark, J. Hespanha, Radha Poovendran. Modeling and Mitigating the Coremelt Attack. In Proc. of the 2018 Amer. Contr. Conf., June 2018. [bibtex:YangHosseiniSahabanduHespanhaPoovendranClarkJun18] [pdf]

[20] K. Vamvoudakis, J. Hespanha. Game-Theory-Based Consensus Learning of Double-Integrator Agents in the Presence of Worst-Case Adversaries. J. Opt. Theory and Applications, 177(1):222—253, Apr. 2018. [bibtex:VamvoudakisHespanhaApr18a] [pdf]

[25] J. Hespanha, S. Bopardikar. Output-Feedback linear quadratic robust control under actuation and deception attacks. Technical Report, University of California, Santa Barbara, Sep. 2018. Available at http://www.ece.ucsb.edu/~hespanha/techrep.html [bibtex:HespanhaBopardikarSep18] [pdf]

[26] M. Wakaiki, P. Tabuada, J. Hespanha. Supervisory Control of Discrete-event Systems under Attacks. Technical Report, University of California, Santa Barbara, Aug. 2016. [bibtex:WakaikiTabuadaHespanhaAug2016b] [pdf]

See also [7], [9].

8. Distributed Control and Multi-agent Systems

[8] David Grimsman, Mohd. Shabbir Ali, J. Hespanha, Jason R. Marden. The Impact of Information in Distributed Submodular Maximization. IEEE Trans. on Contr. of Network Syst., Dec. 2019. [bibtex:GrimsmanAliHespanhaardenDec19] [pdf]

[14] David Grimsman, Jason R. Marden, J. Hespanha. Strategic Information Sharing in Greedy Submodular Maximization. In Proc. of the 57th Conf. on Decision and Contr., Dec. 2018. [bibtex:GrimsmanMardenHespanhaDec18] [pdf]

[17] D. Silvestre, J. Hespanha, C. Silvestre. A PageRank Algorithm based on Asynchronous Gauss-Seidel Iterations. In Proc. of the 2018 Amer. Contr. Conf., June 2018. [bibtex:SilvestreHespanhaSilvestreJun18] [pdf]

[22] David Grimsman, Mohd. Shabbir Ali, J. Hespanha Jason R. Marden. Impact of information in greedy submodular maximization. In Proc. of the 56th Conf. on Decision and Contr., Dec. 2017. [bibtex:GrimsmanAliHespanhaMardenDec17] [pdf]

See also [17], [19].

11. Optimization and Optimal Control

[5] J. Hespanha, Denis Garagic. Optimal Sensor Selection for Binary Detection based on Stochastic Submodular Optimization. In Proc. of the 59th Conf. on Decision and Contr., Dec. 2020. To appear. [bibtex:HespanhaGaragicDec20] [pdf]

[24] J. Hespanha, Denis Garagic. Optimal Sensor Selection for Binary Detection based on Stochastic Submodular Optimization: Technical Report. Technical Report, University of California, Santa Barbara, Dec. 2020. [bibtex:HespanhaGaragicDec20] [pdf]

See also [8], [14], [19], [22].

12. Game Theory

[7] G. Yang, J. Hespanha. Modeling and mitigating link-flooding distributed denial-of-service attacks via learning in Stackelberg games. In Handbook of Reinforcement Learning, Vamvoudakis, Kyriakos G., Wan, Yan, Lewis, Frank L., Cansever, Derya (ed.). To appear [bibtex:YangHespanhaMay2020] [pdf]

[9] G. Yang, Radha Poovendran, J. Hespanha. Adaptive learning in two-player Stackelberg games with continuous action sets. In Proc. of the 58th Conf. on Decision and Contr., Dec. 2019. [bibtex:YangPoovendranHespanhaDec2019] [pdf]

[10] J. Hespanha, Denis Garagic. Sensor-Reveal Games. In Proc. of the 58th Conf. on Decision and Contr., Dec. 2019. [bibtex:HespanhaGaragicDec2019] [pdf]

[19] K. Vamvoudakis, J. Hespanha. Cooperative Q-learning for Rejection of Persistent Adversarial Inputs in Networked Linear Quadratic Systems. IEEE Trans. on Automat. Contr., 63(4):1018—1031, Apr. 2018. [bibtex:VamvoudakisHespanhaApr18b] [pdf]

[23] J. Hespanha. Noncooperative Game Theory: An Introduction for Engineers and Computer Scientists. Princeton Press, June 2017. [bibtex:Hespanha17]

See also [2], [3], [4], [6], [8], [11], [12], [14], [20], [22], [25], [26].

19. Other

[21] J. Hespanha. Linear Systems Theory. Princeton Press, Feb. 2018. [bibtex:HespanhaFeb18] [pdf] [pdf] [pdf]

See also [23].

This file was generated on 3/31/2021 using the perl script "bib2web" (version 1.4, dated 29/03/2016) written by João Pedro Hespanha

[1]	G. Yang, A. James Schmidt, D. Liberzon, J. Hespanha. Topological entropy of switched linear systems: General matrices and matrices with commutation relations. Math. Contr., Signals, Syst.. To appear. [bibtex:YangSchmidtLiberzonHespanha2020] [pdf]
[13]	G. Yang, J. Hespanha, D. Liberzon. On topological entropy and stability of switched linear systems. In Proc. of the 22nd ACM Int. Conf. on Hybrid Systems: Computation and Control (HSCC 2019), pages 119—127, Apr. 2019. [bibtex:YangHespanhaLiberzonApr2019] [pdf]
[15]	G. Yang, J. Hespanha. On topological entropy of switched linear systems with pairwise-commuting matrices. In Proc. of the 56th Annual Allerton Conf. on Comm., Contr., and Computing, Oct. 2018. [bibtex:YangHespanhaOct18] [pdf]

[2]	J. Hespanha. Sensor Manipulation Games in Cyber Security. In Game Theory and Machine Learning for Cyber Security, Charles A. Kamhoua, Christopher D. Kiekintveld, Fei Fang, Quanyan Zhu (ed.), 2021. To appear. [bibtex:HespanhaDec20] [pdf]
[3]	G. Yang, Radha Poovendran, J. Hespanha. Adaptive learning in two-player Stackelberg games with application to network security. Jan. 2021. Submitted to journal publication. [bibtex:YangPoovendranHespanhaJan21] [pdf]
[4]	M. Chong, Henrik Sandberg, J. Hespanha. A secure state estimation algorithm for nonlinear systems under sensor attacks. In Proc. of the 59th Conf. on Decision and Contr., Dec. 2020. To appear. [bibtex:ChongHespanhaDec20] [pdf]
[6]	David Grimsman, J. Hespanha, Jason R. Marden. Stackelberg Equilibria for Two-Player Network Routing Games on Parallel Networks. In Proc. of the 2020 Amer. Contr. Conf., July 2020. [bibtex:GrimsmanHespanhaMardenJul20] [pdf]
[11]	M. Wakaiki, P. Tabuada, J. Hespanha. Supervisory Control of Discrete-event Systems under Attacks. Dynamic Games and Applications, Special Issue on Dynamic Games in Cyber Security, 9(4):965—983, Dec. 2019. [bibtex:WakaikiTabuadaHespanhaDec19] [pdf]
[12]	J. Hespanha, S. Bopardikar. Output-feedback linear quadratic robust control under actuation and deception attacks. In Proc. of the 2019 Amer. Contr. Conf., July 2019. [bibtex:HespanhaBopardikarJul19] [pdf]
[16]	Y. Wang, J. Hespanha. Distributed Estimation of Power System Oscillation Modes under Attacks on GPS Clocks. IEEE Trans. on Instr. and Measurement, 67(7):1626—1637, July 2018. [bibtex:WangHespanhaJul18] [pdf]
[18]	G. Yang, Hossein Hosseini, Dinuka Sahabandu, Andrew Clark, J. Hespanha, Radha Poovendran. Modeling and Mitigating the Coremelt Attack. In Proc. of the 2018 Amer. Contr. Conf., June 2018. [bibtex:YangHosseiniSahabanduHespanhaPoovendranClarkJun18] [pdf]
[20]	K. Vamvoudakis, J. Hespanha. Game-Theory-Based Consensus Learning of Double-Integrator Agents in the Presence of Worst-Case Adversaries. J. Opt. Theory and Applications, 177(1):222—253, Apr. 2018. [bibtex:VamvoudakisHespanhaApr18a] [pdf]
[25]	J. Hespanha, S. Bopardikar. Output-Feedback linear quadratic robust control under actuation and deception attacks. Technical Report, University of California, Santa Barbara, Sep. 2018. Available at http://www.ece.ucsb.edu/~hespanha/techrep.html [bibtex:HespanhaBopardikarSep18] [pdf]
[26]	M. Wakaiki, P. Tabuada, J. Hespanha. Supervisory Control of Discrete-event Systems under Attacks. Technical Report, University of California, Santa Barbara, Aug. 2016. [bibtex:WakaikiTabuadaHespanhaAug2016b] [pdf]

[8]	David Grimsman, Mohd. Shabbir Ali, J. Hespanha, Jason R. Marden. The Impact of Information in Distributed Submodular Maximization. IEEE Trans. on Contr. of Network Syst., Dec. 2019. [bibtex:GrimsmanAliHespanhaardenDec19] [pdf]
[14]	David Grimsman, Jason R. Marden, J. Hespanha. Strategic Information Sharing in Greedy Submodular Maximization. In Proc. of the 57th Conf. on Decision and Contr., Dec. 2018. [bibtex:GrimsmanMardenHespanhaDec18] [pdf]
[17]	D. Silvestre, J. Hespanha, C. Silvestre. A PageRank Algorithm based on Asynchronous Gauss-Seidel Iterations. In Proc. of the 2018 Amer. Contr. Conf., June 2018. [bibtex:SilvestreHespanhaSilvestreJun18] [pdf]
[22]	David Grimsman, Mohd. Shabbir Ali, J. Hespanha Jason R. Marden. Impact of information in greedy submodular maximization. In Proc. of the 56th Conf. on Decision and Contr., Dec. 2017. [bibtex:GrimsmanAliHespanhaMardenDec17] [pdf]

[5]	J. Hespanha, Denis Garagic. Optimal Sensor Selection for Binary Detection based on Stochastic Submodular Optimization. In Proc. of the 59th Conf. on Decision and Contr., Dec. 2020. To appear. [bibtex:HespanhaGaragicDec20] [pdf]
[24]	J. Hespanha, Denis Garagic. Optimal Sensor Selection for Binary Detection based on Stochastic Submodular Optimization: Technical Report. Technical Report, University of California, Santa Barbara, Dec. 2020. [bibtex:HespanhaGaragicDec20] [pdf]

[7]	G. Yang, J. Hespanha. Modeling and mitigating link-flooding distributed denial-of-service attacks via learning in Stackelberg games. In Handbook of Reinforcement Learning, Vamvoudakis, Kyriakos G., Wan, Yan, Lewis, Frank L., Cansever, Derya (ed.). To appear [bibtex:YangHespanhaMay2020] [pdf]
[9]	G. Yang, Radha Poovendran, J. Hespanha. Adaptive learning in two-player Stackelberg games with continuous action sets. In Proc. of the 58th Conf. on Decision and Contr., Dec. 2019. [bibtex:YangPoovendranHespanhaDec2019] [pdf]
[10]	J. Hespanha, Denis Garagic. Sensor-Reveal Games. In Proc. of the 58th Conf. on Decision and Contr., Dec. 2019. [bibtex:HespanhaGaragicDec2019] [pdf]
[19]	K. Vamvoudakis, J. Hespanha. Cooperative Q-learning for Rejection of Persistent Adversarial Inputs in Networked Linear Quadratic Systems. IEEE Trans. on Automat. Contr., 63(4):1018—1031, Apr. 2018. [bibtex:VamvoudakisHespanhaApr18b] [pdf]
[23]	J. Hespanha. Noncooperative Game Theory: An Introduction for Engineers and Computer Scientists. Princeton Press, June 2017. [bibtex:Hespanha17]