As the demand for cheaper electronic devices has increased, the location of manufacturing foundries has changed to untrusted places outside of the United States. Some of these locations have limited oversight of the manufacturing of complicated and sensitive electronic components including integrated circuits (IC). IC, a key component in all current electronic devices, can be modified to be malicious or to monitor the functions of their applications. These malicious modifications are called Hardware Trojans. Hardware Trojans can be de- signed to quietly monitor, to actively send out unencrypted sensitive information, or to actively destroy their host device. Our research demonstrates the ability of Hardware Trojans to infiltrate a sensor network that could be remotely deployed for various applications. This research is important due to the dearth of knowledge on the subject. Currently, software security is given great importance. Our research shows that the same level of importance must be given to hardware to ensure a trusted and secure environment.

Thesis (M. Phil.)--University of Hong Kong, 2010. / Includes bibliographical references (leaves 85-88). Also available in print.

Thesis (Ph.D.)--University of Texas at Dallas, 2009. / Includes vita. Includes bibliographical references (leaves 61-64)

Thesis (M.S.)--Rochester Institute of Technology, 2009. / Typescript. Includes bibliographical references (leaves 39-40).

Thesis supervisor: Ted Herman. Includes bibliographic references (p. 126-130).

Thesis (Ph. D.)--Oregon State University, 2010. / Printout. Includes bibliographical references (leaves 90-97). Also available on the World Wide Web.

University of Macau / Faculty of Science and Technology / Department of Electrical and Computer Engineering

In this thesis, we propose a suite of Evolutionary Algorithms (EA)-based protocols to solve the problems of clustering and routing in Wireless Sensor Networks (WSNs). At the beginning, the problem of the Cluster Heads (CHs) selection in WSNs is formulated as a single-objective optimization problem. A centralized weighted-sum multi-objective optimization protocol is proposed to find the optimal set of CHs. The proposed protocol finds a predetermined number of CHs in such way that they form one-hop clusters. The goal of the proposed protocol is to enhance the network's energy efficiency, data delivery reliability and the protocol's scalability. The formulated problem has been solved using three evolutionary approaches: Genetic Algorithms (GA), Differential Evolution (DE) and Particle Swarm Optimization (PSO) and we assessed each of their performance. Then, a PSO-based hierarchical clustering protocol that forms two-hop clusters is proposed to investigate the effect of the number of CHs on network's energy efficiency. This protocol enhances the WSN's energy efficiency by setting an upper bound on the number of CHs and trying to minimize the number of CHs compared to that upper bound. It also maximizes the protocol's scalability by using two-hop communication between the sensor nodes and their respective CHs. Then, a centralized weighted-sum PSO-based protocol is proposed for finding the optimal inter-cluster routing tree that connects the CHs to the Base Station (BS). This protocol is appropriate when the CHs are predetermined in advance. The proposed protocol uses a particle encoding scheme and defines an objective function to find the optimal routing tree. The objective function is used to build the trade-off between the energy-efficiency and data delivery reliability of the constructed tree. Finally, a centralized multi-objective Pareto-optimization approach is adapted to find the optimal network configuration that includes both the optimal set of CHs and the optimal routing tree. A new individual encoding scheme that represents a joint solution for both the clustering and routing problems in WSNs is proposed. The proposed protocol uses a variable number of CHs, and its objective is to assign each network node to its respective CH and each CH to its respective next hop. The joint problem of clustering and routing in WSNs is formulated as a multi-objective minimization problem with a variable number of CHs, aiming at determining an energy efficient, reliable ( in terms of data delivery) and scalable clustering and routing scheme. The formulated problem has been solved using two state-of-the-art Multi-Objective Evolutionary Algorithms (MOEA), and their performance has been compared. The proposed protocols were developed under realistic network settings. No assumptions were made about the nodes' location awareness or transmission range capabilities. The proposed protocols were tested using a realistic energy consumption model that is based on the characteristics of the Chipcon CC2420 radio transceiver data sheet. Extensive simulations on 50 homogeneous and heterogeneous WSN models were evaluated and compared against well-known cluster-based sensor network protocols.

Wireless Sensor Networks (WSNs) have been applied to a wide range of application areas, including battle fields, transportation systems, and hospitals. The security issues in WSNs are still hot research topics. The constrained capabilities of sensors and the environments in which sensors are deployed, such as hostile and non-reachable areas, make the security more complicated. This dissertation describes the development and testing of a novel two-phase security mechanism for hierarchical WSNs that is capable of defending both outside and inside attacks. For the outside attacks, the attackers are usually malicious intruders that entered the network. The computation and communication capabilities of the sensors restrict them from directly defending the harmful intruders by performing traditionally encryption, authentication, or other cryptographic operations. However, the sensors can assist the more powerful nodes in a hierarchical structured WSN to track down these intruders and thereby prevent further damage. To fundamentally improve the security of a WSN, a multi-target tracking algorithm is developed to track the intruders. For the inside attacks, the attackers are compromised insiders. The intruders manipulate these insiders to indirectly attack other sensors. Therefore, detecting these malicious insiders in a timely manner is important to improve the security of a network. In this dissertation, we mainly focus on detecting the malicious insiders that try to break the normal communication among sensors, which creates holes in the WSN. As the malicious insiders attempt to break the communication by actively using HELLO flooding attack, we apply an immune-inspired algorithm called Dendritic Cell Algorithm (DCA) to detect this type of attack. If the malicious insiders adopt a subtle way to break the communication by dropping received packets, we implement another proposed technique, a short-and-safe routing (SSR) protocol to prevent this type of attack. The designed security mechanism can be applied to different sizes of both static and dynamic WSNs. We adopt a popular simulation tool, ns-2, and a numerical computing environment, MATLAB, to analyze and compare the computational complexities of the proposed security mechanism. Simulation results demonstrate effective performance of the developed corrective and preventive security mechanisms on detecting malicious nodes and tracking the intruders.

No / Wireless sensor networks are an emerging technology for low-cost, unattended monitoring of a wide range of environments. Their importance has been enforced by the recent delivery of the IEEE 802.15.4 standard for the physical and MAC layers and the forthcoming ZigBee standard for the network and application layers. The fast progress of research on energy efficiency, networking, data management and security in wireless sensor networks, and the need to compare with the solutions adopted in the standards motivates the need for a survey on this field.