PhD Defense: Zhenhua Liu The open nature of wireless communication makes it easy for adversaries to either inject random signals to wireless channels harming the network availability, or eavesdrop on the communication breaching the location privacy. Those threats are challenging to cope with, because most of them cannot be addressed by traditional cryptographic methods. One of the attacks that can easily imperil the availability of networks is jamming attacks. An adversary can launch a jamming attack either by bypassing MAC-layer protocols and keeping sending packets, or by emitting radio signals to a particular channel. To cope with jamming attacks, in this dissertation, we focus on developing mechanisms to localize jammers. We examine how jammers affect networks in terms of signal strength, nodes’ communication range, and network topologies, and present how to measure these jamming effects. To localize a jammer, we design an Adaptive Least-Squares-based (LSQ-based) algorithm which performs localization by exploiting the changes of communication range. Then, to further improve the localization accuracy, we propose an error minimizing framework that can localize not only one but also multiple jammers through utilizing the strength of jamming signals (JSS). To evaluate the effectiveness of our proposed localization schemes, we conducted real-world experiments using a testbed of MicaZ, and then carried out extensive performance studies in large-scale networks by simulation. Another problem that cannot be solved by traditional cryptographic method is the location privacy issue. We study this issue in wireless sensor network because the locations of the sink nodes are critically important to the viability of wireless networks, and such information can be easily determined by attackers. For instance, attackers can eavesdrop on the network communication at several spots and trace back to the sink nodes. Then, they can destroy the sink nodes physically to disable the data collection or dissemination. In this dissertation, we examine the sink location privacy problem from both the attack and defense sides. On the attack side, we present two types of Zeroing-In attacks which allow attackers to identify the sink location by estimating the hop count or the arrival time of a broadcast packet at a few spots in the network. To cope with the Zeroing-In attacks, we propose a directed-walk-based scheme and validate that it is effective in deceiving adversaries at modest energy costs."