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Game Theory and Algorithm Design in Network Security and Smart Grid

Zhang, Ming
http://orcid.org/0000-0001-6412-8730
http://rave.ohiolink.edu/etdc/view?acc_num=osu1534690108502024

Abstract Details

2018, Doctor of Philosophy, Ohio State University, Computer Science and Engineering.
New cyber-security threats and the emergence of the smart grid bring to the fore numerous performance and security challenges that need to be carefully addressed. In this dissertation, we use game theory to investigate the difficulties involved in network security issues with stealthy attacks as well as the problem of dynamic economic dispatch in smart grid, designing efficient algorithm to overcome the new challenges. From a network security perspective, we focus on stealthy attacks and the corresponding defense on a network of multiple independent components. Stealthy attacks are now a major cyber-security threat. In practice, both attackers and defenders have resource constraints that could limit their capabilities. To develop robust defense strategies, game theory is utilized to understand the fundamental trade-offs involved. Previous works in this direction, however, mainly focus on the single-node case without considering strict resource constraints. In this dissertation, a game-theoretic model for protecting a system of multiple nodes against stealthy attacks is developed. We consider the practical setting where the frequencies of both attack and defense are constrained by limited resources, and an asymmetric feedback structure where the attacker can fully observe the states of nodes while entirely hiding its actions from the defender. We characterize the best response strategies for both attacker and defender in the space of both non-adaptive and adaptive strategies, and study the Nash Equilibria of the game. We further study a sequential game where the defender first announces its strategy and the attacker then responds accordingly, and design an algorithm that finds a nearly optimal strategy for the defender to commit to. For the smart grid, we investigate the mechanism design problem in dynamic economic dispatch involving an Independent System Operator (ISO) and multiple electricity generators. The objective of the ISO is to minimize the total cost of power generation for serving a time-variant demand profile based on the set of bids from each generator which has generation cost, ramping cost and ramping capacity. Due to the selfishness, generators may not reveal their true information to the ISO. We design a mechanism with a VCG-type payment function, which guarantees that a profile of truthful bids from all the generators form a Nash equilibrium and at the same time, the ISO minimizes the actual total cost based on the bids. We further extend our mechanism to an online setting. We first show that no online algorithm can achieve sublinear bound and then prove that, if certain assumption holds, the RHC algorithm can achieve the same performance as in our offline setting . We next shift our focus on a similar scenario where power-proportional data centers can save energy cost by dynamically ``right-sizing'' the data centers based on real-time workload. Servers are activated when the workload increases while some servers can be put into the sleep mode during periods of low load. However, the activation and deactivation of servers incur an extra switching cost. In this part, we revisit the dynamic right-sizing problem for heterogeneous data centers with various operational cost and switching cost. We propose a new online algorithm based on a regularization technique, which achieves a better competitive ratio compared to the state-of-the-art greedy algorithm. We further introduce a switching cost offset into the model and extend our algorithm to this new setting. Simulations based on real workload and renewable energy traces show that our algorithms outperform the greedy algorithm in both settings.
Ness Shroff (Advisor)
Atilla Eryilmaz (Committee Member)
Abhishek Gupta (Committee Member)
150 p.
Computer Science
Game theory; Algorithm Design; Network Security; Smart Grid

Recommended Citations

Citations

  • Zhang, M. (2018). Game Theory and Algorithm Design in Network Security and Smart Grid [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1534690108502024

    APA Style (7th edition)

  • Zhang, Ming. Game Theory and Algorithm Design in Network Security and Smart Grid. 2018. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1534690108502024.

    MLA Style (8th edition)

  • Zhang, Ming. "Game Theory and Algorithm Design in Network Security and Smart Grid." Doctoral dissertation, Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1534690108502024

    Chicago Manual of Style (17th edition)

osu1534690108502024
256
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This open access ETD is published by The Ohio State University and OhioLINK.