Thesis--Western Reserve University. / eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis--Western Reserve University. / Includes bibliographical references.

Thesis (M.S. in entomology)--Washington State University, May 2010. / Title from PDF title page (viewed on July 12, 2010). "Department of Entomology." Includes bibliographical references.

Thesis (M.S.)--Brigham Young University. Dept. of Physics and Astronomy, 2005. / Includes bibliographical references (p. 93-96).

Thesis (M.S.)--Baylor University, 2006. / Includes bibliographical references (p. 74-76).

Complex networks appear in almost every aspect of our daily life and are widely studied in the fields of physics, mathematics, finance, biology and computer science. This work utilizes percolation theory in statistical physics to explore the percolation properties of complex networks and develops a reinforcement scheme on improving network resilience. This dissertation covers two major parts of my Ph.D. research on complex networks: i) probe—in the context of both traditional percolation and k-core percolation—the resilience of complex networks with tunable degree distributions or directed dependency links under random, localized or targeted attacks; ii) develop and propose a reinforcement scheme to eradicate catastrophic collapses that occur very often in interdependent networks. We first use generating function and probabilistic methods to obtain analytical solutions to percolation properties of interest, such as the giant component size and the critical occupation probability. We study uncorrelated random networks with Poisson, bi-Poisson, power-law, and Kronecker-delta degree distributions and construct those networks which are based on the configuration model. The computer simulation results show remarkable agreement with theoretical predictions. We discover an increase of network robustness as the degree distribution broadens and a decrease of network robustness as directed dependency links come into play under random attacks. We also find that targeted attacks exert the biggest damage to the structure of both single and interdependent networks in k-core percolation. To strengthen the resilience of interdependent networks, we develop and propose a reinforcement strategy and obtain the critical amount of reinforced nodes analytically for interdependent Erdős-Rényi networks and numerically for scale-free and for random regular networks. Our mechanism leads to improvement of network stability of the West U.S. power grid. This dissertation provides us with a deeper understanding of the effects of structural features on network stability and fresher insights into designing resilient interdependent infrastructure networks.

Wi-Fi (IEEE 802.11) is currently one of the primary media to access the Internet. Guaranteeing the availability of Wi-Fi networks is essential to numerous online activities, such as e-commerce, video streaming, and IoT services. Attacks on availability are generally referred to as Denial-of-Service (DoS) attacks. While there exists signif- icant literature on DoS attacks against Wi-Fi networks, most of the existing attacks are localized in nature, i.e., the attacker must be in the vicinity of the victim. The purpose of this dissertation is to investigate the feasibility of mounting global DoS attacks on Wi-Fi networks and develop effective counter-measures. First, the dissertation unveils the existence of a vulnerability at the MAC layer of Wi-Fi, which allows an adversary to remotely launch a Denial-of-Service (DoS) attack that propagates both in time and space. This vulnerability stems from a coupling effect induced by hidden nodes. Cascading DoS attacks can congest an entire network and do not require the adversary to violate any protocol. The dissertation demonstrates the feasibility of such attacks through experiments with real Wi-Fi cards, extensive ns-3 simulations, and theoretical analysis. The simulations show the attack is effective both in networks operating under fixed and varying bit rates, as well as ad hoc and infrastructure modes. To gain insight into the root-causes of the attack, the network is modeled as a dynamical system and its limiting behavior is analyzed. The model predicts that a phase transition (and hence a cascading attack) is possible when the retry limit parameter of Wi-Fi is greater or equal to 7. Next, the dissertation identifies a vulnerability at the physical layer of Wi-Fi that allows an adversary to launch cascading attacks with weak interferers. This vulnerability is induced by the state machine’s logic used for processing incoming packets. In contrast to the previous attack, this attack is effective even when interference caused by hidden nodes do not corrupt every packet transmission. The attack forces Wi-Fi rate adaptation algorithms to operate at a low bit rate and significantly degrades network performance, such as communication reliability and throughput. Finally, the dissertation proposes, analyzes, and simulates a method to prevent such attacks from occurring. The key idea is to optimize the duration of packet transmissions. To achieve this goal, it is essential to properly model the impact of MAC overhead, and in particular MAC timing parameters. A new theoretical model is thus proposed, which relates the utilization of neighboring pairs of nodes using a sequence of iterative equations and uses fixed point techniques to study the limiting behavior of the sequence. The analysis shows how to optimally set the packet duration so that, on the one hand, cascading DoS attacks are avoided and, on the other hand, throughput is maximized. The analytical results are validated by extensive ns-3 simulations. A key insight obtained from the analysis and simulations is that IEEE 802.11 networks with relatively large MAC overhead are less susceptible to cascading DoS attacks than networks with smaller MAC overhead.

No description available.

No

No / Accepted for conference.