Vehicular ad hoc networks (VANETs) are a subclass of mobile ad hoc networks (MANETs) in which the mobile nodes are vehicles; these vehicles are autonomous systems connected by wireless communication on a peer-to-peer basis. They are self-organized, self-configured and self-controlled infrastructure-less networks. This kind of network has the advantage of being able to be set-up and deployed anywhere and anytime because it has no infrastructure set-up and no central administration. Distributing information between these vehicles over long ranges in such networks, however, is a very challenging task, since sharing information always has a risk attached to it especially when the information is confidential. The disclosure of such information to anyone else other than the intended parties could be extremely damaging, particularly in military applications where controlling the dissemination of messages is essential. This thesis therefore provides a review of the issue of security in VANET and MANET; it also surveys existing solutions for dissemination control. It highlights a particular area not adequately addressed until now: controlling information flow in VANETs. This thesis contributes a policy-based framework to control the dissemination of messages communicated between nodes in order to ensure that message remains confidential not only during transmission, but also after it has been communicated to another peer, and to keep the message contents private to an originator-defined subset of nodes in the VANET. This thesis presents a novel framework to control data dissemination in vehicle ad hoc networks in which policies are attached to messages as they are sent between peers. This is done by automatically attaching policies along with messages to specify how the information can be used by the receiver, so as to prevent disclosure of the messages other than consistent with the requirements of the originator. These requirements are represented as a set of policy rules that explicitly instructs recipients how the information contained in messages can be disseminated to other nodes in order to avoid unintended disclosure. This thesis describes the data dissemination policy language used in this work; and further describes the policy rules in order to be a suitable and understandable language for the framework to ensure the confidentiality requirement of the originator. This thesis also contributes a policy conflict resolution that allows the originator to be asked for up-to-date policies and preferences. The framework was evaluated using the Network Simulator (NS-2) to provide and check whether the privacy and confidentiality of the originators’ messages were met. A policy-based agent protocol and a new packet structure were implemented in this work to manage and enforce the policies attached to packets at every node in the VANET. Some case studies are presented in this thesis to show how data dissemination can be controlled based on the policy of the originator. The results of these case studies show the feasibility of our research to control the data dissemination between nodes in VANETs. NS-2 is also used to test the performance of the proposed policy-based agent protocol and demonstrate its effectiveness using various network performance metrics (average delay and overhead).

<p>The rapid expansion of consumer Internet-of-Things (IoT) technology across various application domains has made it one of the most sought-after and swiftly evolving technologies. IoT devices offer numerous benefits, such as enhanced security, convenience, and cost reduction. However, as these devices need access to sensitive aspects of human life to function effectively, their abuse can lead to significant financial, psychological, and physical harm. While previous studies have examined the vulnerabilities of IoT devices, insufficient research has delved into the impact and mitigation of threats to users' privacy and safety. This dissertation addresses the challenge of protecting user safety and privacy against threats posed by IoT device vulnerabilities. We first introduce a novel IWMD architecture, which serves as the last line of defense against unsafe operations of Implantable and Wearable Medical Devices (IWMDs). We demonstrate the architecture's effectiveness through a prototype artificial pancreas. Subsequent chapters emphasize the safety and privacy of smart home device users. First, we propose a unique device activity-based categorization and learning approach for network traffic analysis. Utilizing this technology, we present a new smart home security framework and a device type identification mechanism to enhance transparency and access control in smart home device communication. Lastly, we propose a novel traffic shaping technique that hinders adversaries from discerning user activities through traffic analysis. Experiments conducted on commercially available IoT devices confirm that our solutions effectively address these issues with minimal overhead.</p>