Dynamic hashing technique for bandwidth reduction in image transmission

Hash functions are widely used in secure communication systems by generating the message digests for detection of unauthorized changes in the files. Encrypted hashed message or digital signature is used in many applications like authentication to ensure data integrity. It is almost impossible to ensure authentic messages when sending over large bandwidth in highly accessible network especially on insecure channels. Two issues that required to be addressed are the large size of hashed message and high bandwidth. A collaborative approach between encoded hash message and steganography provides a highly secure hidden data. The aim of the research is to propose a new method for producing a dynamic and smaller encoded hash message with reduced bandwidth. The encoded hash message is embedded into an image as a stego-image to avoid additional file and consequently the bandwidth is reduced. The receiver extracts the encoded hash and dynamic hashed message from the received file at the same time. If decoding encrypted hash by public key and hashed message from the original file matches the received file, it is considered as authentic. In enhancing the robustness of the hashed message, we compressed or encoded it or performed both operations before embedding the hashed data into the image. The proposed algorithm had achieved the lowest dynamic size (1 KB) with no fix length of the original file compared to MD5, SHA-1 and SHA-2 hash algorithms. The robustness of hashed message was tested against the substitution, replacement and collision attacks to check whether or not there is any detection of the same message in the output. The results show that the probability of the existence of the same hashed message in the output is closed to 0% compared to the MD5 and SHA algorithms. Amongst the benefits of this proposed algorithm is computational efficiency, and for messages with the sizes less than 1600 bytes, the hashed file reduced the original file up to 8.51%

Secure Authentication and Privacy-Preserving Techniques in Vehicular Ad-hoc NETworks (VANETs)

In the last decade, there has been growing interest in Vehicular Ad Hoc NETworks (VANETs). Today car manufacturers have already started to equip vehicles with sophisticated sensors that can provide many assistive features such as front collision avoidance, automatic lane tracking, partial autonomous driving, suggestive lane changing, and so on. Such technological advancements are enabling the adoption of VANETs not only to provide safer and more comfortable driving experience but also provide many other useful services to the driver as well as passengers of a vehicle. However, privacy, authentication and secure message dissemination are some of the main issues that need to be thoroughly addressed and solved for the widespread adoption/deployment of VANETs. Given the importance of these issues, researchers have spent a lot of effort in these areas over the last decade. We present an overview of the following issues that arise in VANETs: privacy, authentication, and secure message dissemination. Then we present a comprehensive review of various solutions proposed in the last 10 years which address these issues. Our survey sheds light on some open issues that need to be addressed in the future

Detecting Rogue Nodes In Vehicular Ad-hoc Networks (DETER)

Vehicular ad hoc Networks (VANETs) are self-organizing networks of vehicles equipped with radios and processors. VANETs are very promising as they can make driving safer by improving road awareness through sharing of information from sensors. Vehicles communicate with each other wirelessly to exchange information and this exchange of information is susceptible to attacks of different kinds. There are some very important issues that need to be resolved before VANETs can be deployed on large scale. Security and privacy issues are undoubtedly the most important factors that need to be resolved. Amongst various problems to be solved in VANETs is the issue of rogue nodes and their impact on the network. This thesis discusses the problems associated with the security and privacy of vehicular networks in the presence of rogue nodes. The rogue nodes can share / inject false data in the network which can cause serious harm. The techniques proposed make VANETs secure and prevent them from the harmful impact of rogue nodes. The proposed work makes the network safer by making it fault tolerant and resilient in the presence of rogue nodes that can be detected and reported. As VANETs are highly dynamic and fast moving so, a data centric scheme is proposed that can determine if a node is rogue or not just by analysing its data. The work then enhances the developed mechanism by applying hypothesis testing and other statistical techniques to detect intrusions in the network by rogue nodes. The technique is simulated using OMNET++, SUMO and VACAMobil and the results obtained have been presented, discussed and compared to previous works. In order to prevent rogue nodes from becoming part of the VANETs this thesis also presents a novel framework for managing the digital identity in the vehicular networks. This framework authenticates the user and the vehicle separately from two authorities and allows him to communicate securely with the infrastructure using IBE (Identity Based Encryption). The proposed technique also preserves the privacy of the user. The proposed scheme allows traceability and revocation so that users can be held accountable and penalised. The results have been compared to previous works of similar nature. The thesis also discusses the Sybil attack and how to detect them using game theory in a VANET environment

An intelligent intrusion detection system for external communications in autonomous vehicles

Advancements in computing, electronics and mechanical systems have resulted in the creation of a new class of vehicles called autonomous vehicles. These vehicles function using sensory input with an on-board computation system. Self-driving vehicles use an ad hoc vehicular network called VANET. The network has ad hoc infrastructure with mobile vehicles that communicate through open wireless channels. This thesis studies the design and implementation of a novel intelligent intrusion detection system which secures the external communication of self-driving vehicles. This thesis makes the following four contributions: It proposes a hybrid intrusion detection system to protect the external communication in self-driving vehicles from potential attacks. This has been achieved using fuzzification and artificial intelligence. The second contribution is the incorporation of the Integrated Circuit Metrics (ICMetrics) for improved security and privacy. By using the ICMetrics, specific device features have been used to create a unique identity for vehicles. Our work is based on using the bias in on board sensory systems to create ICMetrics for self-driving vehicles. The incorporation of fuzzy petri net in autonomous vehicles is the third contribution of the thesis. Simulation results show that the scheme can successfully detect denial-of-service attacks. The design of a clustering based hierarchical detection system has also been presented to detect worm hole and Sybil attacks. The final contribution of this research is an integrated intrusion detection system which detects various attacks by using a central database in BusNet. The proposed schemes have been simulated using the data extracted from trace files. Simulation results have been compared and studied for high levels of detection capability and performance. Analysis shows that the proposed schemes provide high detection rate with a low rate of false alarm. The system can detect various attacks in an optimised way owing to a reduction in the number of features, fuzzification