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Cybersecurity Modeling of Autonomous Systems: a Game-based Approach

Jahan, Farha
http://orcid.org/0000-0001-7599-3295
http://rave.ohiolink.edu/etdc/view?acc_num=toledo1651881092817159

Abstract Details

2022, Doctor of Philosophy, University of Toledo, Engineering.
Autonomous Systems are soon expected to integrate into our lives as home assistants, delivery drones, and driverless cars. The level of automation in these systems, from being manually controlled to fully autonomous, would depend upon the autonomy approach chosen to design these systems. This selection would also affect other operational as well as essential aspects such as cybersecurity and trust. Consequently, the dawn of the areas of human-machine teams (HMT) and cyber-physical human systems (CPHS) have attempted to address the human trust in autonomy while traditional domains of security, along with these new domains, continue to attempt to address the security concerns. This dissertation revolves around these general ideas and attempts to answer many open questions. How did we get here? Where is the future? How do we ensure that the autonomous systems are secure enough so that we may trust their autonomous operation? Can we model the attacker and defender behavior based on the strategies for defense or attack? Given the importance of cybersecurity of these systems, we propose that simulation and modeling of these interactions to predict or select appropriate behavior is expected to lead to a greater trust in autonomous systems through explainable cause and action sequences. This first phase of this research reviews the historical evolution of autonomy, its approaches, and the current trends in related fields to build robust autonomous systems. Towards such a goal and with the increased number of cyberattacks, the security of these systems needs special attention from the research community. To gauge the extent of stat-of-the-art in this area, we study the works that attempt to improve the cybersecurity of these systems. We also found that it is essential to model the system architecture from a security perspective, identify the threats and vulnerabilities and then model the cyberattacks. A survey in this direction explores the various attack models that have been proposed over the years and identifies the research gap that needs to be addressed by the research community. The second phase of this work focuses on developing generic autonomous system architecture, both theoretical and analytical, on enabling the next step of security modeling. It was construed that any autonomous system can be represented using three major modules - perception, cognition, and control. Further, the proposed autonomous system model performed detailed threat, vulnerability, and attack modeling. The next step involved exploring various theories and methods to gauge the appropriateness of its application to security modeling. It was found that economic theories such as game theory work best for profit/loss-oriented cybersecurity problems. We modeled the attack and defense mechanisms applied to the above-mentioned autonomous system modules using a non-cooperative non-zero-sum game. We developed the strategic game formulation and established the method to calculate the decision payoff and associated Nash equilibrium. Twenty-one different scenarios were identified using combinations of 3 attacker and 2 defender strategies. Finally, we simulate the game using an OMNeT++ based simulator known as VEINS to obtain the optimal strategy to maintain a secure system state. Distributed Denial of Service attack was chosen as the attack as there have been many real-world instances of this attack, simply by using a bunch of phones or IoT devices. The simulation results also give a perspective on the attacker's strategies that could have maximum impact of DDoS attack in the Vehicular AdHoc Network. Another tool called Gambit was utilized to calculate the Nash equilibrium for each scenario. After a detailed discussion of the results and their analysis, the work is concluded, summarizing the various actions that attacker and defender can independently take. Each party's best and worst scenarios were identified among the different scenarios. In essence, this work provides a predictive all-scenario evaluation for a network of autonomous systems to allow system designers to be prepared to take action in real-time in case of a cyber attack. Knowing or estimating attacker capability is critical to the success of this model. Underestimating attacker capabilities may lead to the unpreparedness of the system and result in catastrophic damages in case of a cyber attack. Therefore, vulnerability analysis and modeling of the target system serve as a prerequisite for applying this game theory-based security modeling.
Weiqing Sun (Advisor)
Devinder Kaur (Committee Member)
Junghwan Kim (Committee Member)
Quamar Niyaz (Committee Member)
Mohammed Niamat (Committee Member)
149 p.
Computer Engineering
Cybersecurity, Autonomous Systems, Driverless Cars, Mathematical Modeling, Game Theory, Non-Cooperative non-zero-sum game

Recommended Citations

Citations

  • Jahan, F. (2022). Cybersecurity Modeling of Autonomous Systems: a Game-based Approach [Doctoral dissertation, University of Toledo]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1651881092817159

    APA Style (7th edition)

  • Jahan, Farha. Cybersecurity Modeling of Autonomous Systems: a Game-based Approach . 2022. University of Toledo, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=toledo1651881092817159.

    MLA Style (8th edition)

  • Jahan, Farha. "Cybersecurity Modeling of Autonomous Systems: a Game-based Approach ." Doctoral dissertation, University of Toledo, 2022. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1651881092817159

    Chicago Manual of Style (17th edition)

toledo1651881092817159
422
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This open access ETD is published by University of Toledo and OhioLINK.