Enhancing service quality and reliability in intelligent traffic system

Intelligent Traffic Systems (ITS) can manage on-road traffic efficiently based on real-time traffic conditions, reduce delay at the intersections, and maintain the safety of the road users. However, emergency vehicles still struggle to meet their targeted response time, and an ITS is vulnerable to various types of attacks, including cyberattacks. To address these issues, in this dissertation, we introduce three techniques that enhance the service quality and reliability of an ITS. First, an innovative Emergency Vehicle Priority System (EVPS) is presented to assist an Emergency Vehicle (EV) in attending the incident place faster. Our proposed EVPS determines the proper priority codes of EV based on the type of incidents. After priority code generation, EVPS selects the number of traffic signals needed to be turned green considering the impact on other vehicles gathered in the relevant adjacent cells. Second, for improving reliability, an Intrusion Detection System for traffic signals is proposed for the first time, which leverages traffic and signal characteristics such as the flow rate, vehicle speed, and signal phase time. Shannon’s entropy is used to calculate the uncertainty associated with the likelihood of particular evidence and Dempster-Shafer (DS) decision theory is used to fuse the evidential information. Finally, to improve the reliability of a future ITS, we introduce a model that assesses the trust level of four major On-Board Units (OBU) of a self-driving car along with Global Positioning System (GPS) data and safety messages. Both subjective logic (DS theory) and CertainLogic are used to develop the theoretical underpinning for estimating the trust value of a self-driving car by fusing the trust value of four OBU components, GPS data and safety messages. For evaluation and validation purposes, a popular and widely used traffic simulation package, namely Simulation of Urban Mobility (SUMO), is used to develop the simulation platform using a real map of Melbourne CBD. The relevant historical real data taken from the VicRoads website were used to inject the traffic flow and density in the simulation model. We evaluated the performance of our proposed techniques considering different traffic and signal characteristics such as occupancy rate, flow rate, phase time, and vehicle speed under many realistic scenarios. The simulation result shows the potential efficacy of our proposed techniques for all selected scenarios.Doctor of Philosoph

Game Theory-Based Cooperation for Underwater Acoustic Sensor Networks: Taxonomy, Review, Research Challenges and Directions.

Exploring and monitoring the underwater world using underwater sensors is drawing a lot of attention these days. In this field cooperation between acoustic sensor nodes has been a critical problem due to the challenging features such as acoustic channel failure (sound signal), long propagation delay of acoustic signal, limited bandwidth and loss of connectivity. There are several proposed methods to improve cooperation between the nodes by incorporating information/game theory in the node's cooperation. However, there is a need to classify the existing works and demonstrate their performance in addressing the cooperation issue. In this paper, we have conducted a review to investigate various factors affecting cooperation in underwater acoustic sensor networks. We study various cooperation techniques used for underwater acoustic sensor networks from different perspectives, with a concentration on communication reliability, energy consumption, and security and present a taxonomy for underwater cooperation. Moreover, we further review how the game theory can be applied to make the nodes cooperate with each other. We further analyze different cooperative game methods, where their performance on different metrics is compared. Finally, open issues and future research direction in underwater acoustic sensor networks are highlighted

On the Security of the Automatic Dependent Surveillance-Broadcast Protocol

Automatic dependent surveillance-broadcast (ADS-B) is the communications protocol currently being rolled out as part of next generation air transportation systems. As the heart of modern air traffic control, it will play an essential role in the protection of two billion passengers per year, besides being crucial to many other interest groups in aviation. The inherent lack of security measures in the ADS-B protocol has long been a topic in both the aviation circles and in the academic community. Due to recently published proof-of-concept attacks, the topic is becoming ever more pressing, especially with the deadline for mandatory implementation in most airspaces fast approaching. This survey first summarizes the attacks and problems that have been reported in relation to ADS-B security. Thereafter, it surveys both the theoretical and practical efforts which have been previously conducted concerning these issues, including possible countermeasures. In addition, the survey seeks to go beyond the current state of the art and gives a detailed assessment of security measures which have been developed more generally for related wireless networks such as sensor networks and vehicular ad hoc networks, including a taxonomy of all considered approaches.Comment: Survey, 22 Pages, 21 Figure

Byzantine Attack and Defense in Cognitive Radio Networks: A Survey

The Byzantine attack in cooperative spectrum sensing (CSS), also known as the spectrum sensing data falsification (SSDF) attack in the literature, is one of the key adversaries to the success of cognitive radio networks (CRNs). In the past couple of years, the research on the Byzantine attack and defense strategies has gained worldwide increasing attention. In this paper, we provide a comprehensive survey and tutorial on the recent advances in the Byzantine attack and defense for CSS in CRNs. Specifically, we first briefly present the preliminaries of CSS for general readers, including signal detection techniques, hypothesis testing, and data fusion. Second, we analyze the spear and shield relation between Byzantine attack and defense from three aspects: the vulnerability of CSS to attack, the obstacles in CSS to defense, and the games between attack and defense. Then, we propose a taxonomy of the existing Byzantine attack behaviors and elaborate on the corresponding attack parameters, which determine where, who, how, and when to launch attacks. Next, from the perspectives of homogeneous or heterogeneous scenarios, we classify the existing defense algorithms, and provide an in-depth tutorial on the state-of-the-art Byzantine defense schemes, commonly known as robust or secure CSS in the literature. Furthermore, we highlight the unsolved research challenges and depict the future research directions.Comment: Accepted by IEEE Communications Surveys and Tutoiral

Trust-based energy efficient routing protocol for wireless sensor networks

Wireless Sensor Networks (WSNs) consist of a number of distributed sensor nodes that are connected within a specified area. Generally, WSN is used for monitoring purposes and can be applied in many fields including health, environmental and habitat monitoring, weather forecasting, home automation, and in the military. Similar, to traditional wired networks, WSNs require security measures to ensure a trustworthy environment for communication. However, due to deployment scenarios nodes are exposed to physical capture and inclusion of malicious node led to internal network attacks hence providing the reliable delivery of data and trustworthy communication environment is a real challenge. Also, malicious nodes intentionally dropping data packets, spreading false reporting, and degrading the network performance. Trust based security solutions are regarded as a significant measure to improve the sensor network security, integrity, and identification of malicious nodes. Another extremely important issue for WSNs is energy conversation and efficiency, as energy sources and battery capacity are often limited, meaning that the implementation of efficient, reliable data delivery is an equally important consideration that is made more challenging due to the unpredictable behaviour of sensor nodes. Thus, this research aims to develop a trust and energy efficient routing protocol that ensures a trustworthy environment for communication and reliable delivery of data. Firstly, a Belief based Trust Evaluation Scheme (BTES) is proposed that identifies malicious nodes and maintains a trustworthy environment among sensor nodes while reducing the impact of false reporting. Secondly, a State based Energy Calculation Scheme (SECS) is proposed which periodically evaluates node energy levels, leading to increased network lifetime. Finally, as an integrated outcome of these two schemes, a Trust and Energy Efficient Path Selection (TEEPS) protocol has been proposed. The proposed protocol is benchmarked with A Trust-based Neighbour selection system using activation function (AF-TNS), and with A Novel Trust of dynamic optimization (Trust-Doe). The experimental results show that the proposed protocol performs better as compared to existing schemes in terms of throughput (by 40.14%), packet delivery ratio (by 28.91%), and end-to-end delay (by 41.86%). In conclusion, the proposed routing protocol able to identify malicious nodes provides a trustworthy environment and improves network energy efficiency and lifetime

A comprehensive survey of V2X cybersecurity mechanisms and future research paths

Recent advancements in vehicle-to-everything (V2X) communication have notably improved existing transport systems by enabling increased connectivity and driving autonomy levels. The remarkable benefits of V2X connectivity come inadvertently with challenges which involve security vulnerabilities and breaches. Addressing security concerns is essential for seamless and safe operation of mission-critical V2X use cases. This paper surveys current literature on V2X security and provides a systematic and comprehensive review of the most relevant security enhancements to date. An in-depth classification of V2X attacks is first performed according to key security and privacy requirements. Our methodology resumes with a taxonomy of security mechanisms based on their proactive/reactive defensive approach, which helps identify strengths and limitations of state-of-the-art countermeasures for V2X attacks. In addition, this paper delves into the potential of emerging security approaches leveraging artificial intelligence tools to meet security objectives. Promising data-driven solutions tailored to tackle security, privacy and trust issues are thoroughly discussed along with new threat vectors introduced inevitably by these enablers. The lessons learned from the detailed review of existing works are also compiled and highlighted. We conclude this survey with a structured synthesis of open challenges and future research directions to foster contributions in this prominent field.This work is supported by the H2020-INSPIRE-5Gplus project (under Grant agreement No. 871808), the ”Ministerio de Asuntos Económicos y Transformacion Digital” and the European Union-NextGenerationEU in the frameworks of the ”Plan de Recuperación, Transformación y Resiliencia” and of the ”Mecanismo de Recuperación y Resiliencia” under references TSI-063000-2021-39/40/41, and the CHIST-ERA-17-BDSI-003 FIREMAN project funded by the Spanish National Foundation (Grant PCI2019-103780).Peer ReviewedPostprint (published version