Vehicular Internet: Security & Privacy Challenges and Opportunities

The vehicular internet will drive the future of vehicular technology and intelligent transportation systems (ITS). Whether it is road safety, infotainment, or driver-less cars, the vehicular internet will lay the foundation for the future of road travel. Governments and companies are pursuing driver-less vehicles as they are considered to be more reliable than humans and, therefore, safer. The vehicles today are not just a means of transportation but are also equipped with a wide range of sensors that provide valuable data. If vehicles are enabled to share data that they collect with other vehicles or authorities for decision-making and safer driving, they thereby form a vehicular network. However, there is a lot at stake in vehicular networks if they are compromised. With the stakes so high, it is imperative that the vehicular networks are secured and made resilient to any attack or attempt that may have serious consequences. The vehicular internet can also be the target of a cyber attack, which can be devastating. In this paper, the opportunities that the vehicular internet offers are presented and then various security and privacy aspects are discussed and some solutions are presented

State of the Art and Future Perspectives in Smart and Sustainable Urban Development

This book contributes to the conceptual and practical knowledge pools in order to improve the research and practice on smart and sustainable urban development by presenting an informed understanding of the subject to scholars, policymakers, and practitioners. This book presents contributions—in the form of research articles, literature reviews, case reports, and short communications—offering insights into the smart and sustainable urban development by conducting in-depth conceptual debates, detailed case study descriptions, thorough empirical investigations, systematic literature reviews, or forecasting analyses. This way, the book forms a repository of relevant information, material, and knowledge to support research, policymaking, practice, and the transferability of experiences to address urbanization and other planetary challenges

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

Data-centric trust in ephemeral networks

New network types require new security concepts. Surprisingly, trust – the ultimate goal of security – has not evolved as much as other concepts. In particular, the traditional notion of building trust in entities seems inadequate in an ephemeral environment where contacts among nodes are often short-lived and non-recurrent. It is actually the trustworthiness of the data that entities generate that matters most in these ephemeral networks. And what makes things more interesting is the continuous "humanization" of devices, by making them reflect more closely their owners' preferences, including the human sense of costs. Hence, in this thesis we study the notion of data-centric trust in an ephemeral network of rational nodes. The definition of a new notion requires specifying the corresponding basis, measures, and raison d'être. In the following chapters, we address these issues. We begin by defining the system and security models of an example ephemeral network, namely a vehicular network. Next, we delve into the subject of revocation in vehicular networks, before creating and analyzing a game-theoretic model of revocation, where the notion of cost-aware devices makes its first appearance in this thesis. This model not only makes possible the comparison of different revocation mechanisms in the literature, but also leads to the design of an optimal solution, the RevoGame protocol. With the security architecture in place, we formally define data-centric trust and compare several mechanisms for evaluating it. Notably, we apply the Dempster-Shafer Theory to cases of high uncertainty. Last but not least, we show that data-centric trust can reduce the privacy loss resulting from the need to establish trust. We first create a model of the trust-privacy tradeoff and then analyze it with game theory, in an environment of privacy-preserving entities. Our analysis shows that proper incentives can achieve this elusive tradeoff

Towards reliable geographic broadcasting in vehicular networks

In Vehicular ad hoc Networks (VANETs), safety-related messages are broadcasted amongst cars, helping to improve drivers' awareness of the road situation. VANETs’ reliability are highly affected by channel contention. This thesis first addresses the issue of channel use efficiency in geographical broadcasts (geocasts). Constant connectivity changes inside a VANET make the existing routing algorithms unsuitable. This thesis presents a geocast algorithm that uses a metric to estimate the ratio of useful to useless packet received. Simulations showed that this algorithm is more channel-efficient than the farthest-first strategy. It also exposes a parameter, allowing it to adapt to channel load. Second, this thesis presents a method of estimating channel load for providing feedback to moderate the offered load. A theoretical model showing the relationship between channel load and the idle time between transmissions is presented and used to estimate channel contention. Unsaturated stations on the network were shown to have small but observable effects on this relationship. In simulations, channel estimators based on this model show higher accuracy and faster convergence time than by observing packet collisions. These estimators are also less affected by unsaturated stations than by observing packet collisions. Third, this thesis couples the channel estimator to the geocast algorithm, producing a closed-loop load-reactive system that allows geocasts to adapt to instantaneous channel conditions. Simulations showed that this system is not only shown to be more efficient in channel use and be able to adapt to channel contention, but is also able to self-correct suboptimal retransmission decisions. Finally, this thesis demonstrates that all tested network simulators exhibit unexpected behaviours when simulating broadcasts. This thesis describes in depth the error in ns-3, leading to a set of workarounds that allows results from most versions of ns-3 to be interpreted correctly

Authentication enhancement in command and control networks: (a study in Vehicular Ad-Hoc Networks)

Intelligent transportation systems contribute to improved traffic safety by facilitating real time communication between vehicles. By using wireless channels for communication, vehicular networks are susceptible to a wide range of attacks, such as impersonation, modification, and replay. In this context, securing data exchange between intercommunicating terminals, e.g., vehicle-to-everything (V2X) communication, constitutes a technological challenge that needs to be addressed. Hence, message authentication is crucial to safeguard vehicular ad-hoc networks (VANETs) from malicious attacks. The current state-of-the-art for authentication in VANETs relies on conventional cryptographic primitives, introducing significant computation and communication overheads. In this challenging scenario, physical (PHY)-layer authentication has gained popularity, which involves leveraging the inherent characteristics of wireless channels and the hardware imperfections to discriminate between wireless devices. However, PHY-layerbased authentication cannot be an alternative to crypto-based methods as the initial legitimacy detection must be conducted using cryptographic methods to extract the communicating terminal secret features. Nevertheless, it can be a promising complementary solution for the reauthentication problem in VANETs, introducing what is known as “cross-layer authentication.” This thesis focuses on designing efficient cross-layer authentication schemes for VANETs, reducing the communication and computation overheads associated with transmitting and verifying a crypto-based signature for each transmission. The following provides an overview of the proposed methodologies employed in various contributions presented in this thesis. 1. The first cross-layer authentication scheme: A four-step process represents this approach: initial crypto-based authentication, shared key extraction, re-authentication via a PHY challenge-response algorithm, and adaptive adjustments based on channel conditions. Simulation results validate its efficacy, especially in low signal-to-noise ratio (SNR) scenarios while proving its resilience against active and passive attacks. 2. The second cross-layer authentication scheme: Leveraging the spatially and temporally correlated wireless channel features, this scheme extracts high entropy shared keys that can be used to create dynamic PHY-layer signatures for authentication. A 3-Dimensional (3D) scattering Doppler emulator is designed to investigate the scheme’s performance at different speeds of a moving vehicle and SNRs. Theoretical and hardware implementation analyses prove the scheme’s capability to support high detection probability for an acceptable false alarm value ≤ 0.1 at SNR ≥ 0 dB and speed ≤ 45 m/s. 3. The third proposal: Reconfigurable intelligent surfaces (RIS) integration for improved authentication: Focusing on enhancing PHY-layer re-authentication, this proposal explores integrating RIS technology to improve SNR directed at designated vehicles. Theoretical analysis and practical implementation of the proposed scheme are conducted using a 1-bit RIS, consisting of 64 × 64 reflective units. Experimental results show a significant improvement in the Pd, increasing from 0.82 to 0.96 at SNR = − 6 dB for multicarrier communications. 4. The fourth proposal: RIS-enhanced vehicular communication security: Tailored for challenging SNR in non-line-of-sight (NLoS) scenarios, this proposal optimises key extraction and defends against denial-of-service (DoS) attacks through selective signal strengthening. Hardware implementation studies prove its effectiveness, showcasing improved key extraction performance and resilience against potential threats. 5. The fifth cross-layer authentication scheme: Integrating PKI-based initial legitimacy detection and blockchain-based reconciliation techniques, this scheme ensures secure data exchange. Rigorous security analyses and performance evaluations using network simulators and computation metrics showcase its effectiveness, ensuring its resistance against common attacks and time efficiency in message verification. 6. The final proposal: Group key distribution: Employing smart contract-based blockchain technology alongside PKI-based authentication, this proposal distributes group session keys securely. Its lightweight symmetric key cryptography-based method maintains privacy in VANETs, validated via Ethereum’s main network (MainNet) and comprehensive computation and communication evaluations. The analysis shows that the proposed methods yield a noteworthy reduction, approximately ranging from 70% to 99%, in both computation and communication overheads, as compared to the conventional approaches. This reduction pertains to the verification and transmission of 1000 messages in total

Data Substantiation in Mobility

The world is embracing the presence of connected autonomous vehicles which are expected to play a major role in the future of intelligent transport systems. Given such connectivity, vehicles in the networks are vulnerable to making incorrect decisions due to anomalous data. No sophisticated attacks are required; just a vehicle reporting anomalous speeds would be enough to disrupt the entire traffic flow. Detection of such anomalies is vital to ensure the security of a vehicular network. This thesis proposes the use of traffic flow theory for anomalous data detection in vehicular networks, by evaluating the consistency of microscopic parameters which are derived by traffic flow theory with macroscopic views of traffic under different traffic conditions. Though little attention has been given to using traffic flow properties to determine anomalous basic safety message data, the fundamental nature of traffic flow properties makes it a robust assessment tool. The aim of this thesis is to develop a robust data substantiation framework for vehicular networks using traffic flow fundamentals. The aim is fulfilled in three objectives; (1) to provide an overview of the context in terms of existing data substantiation methods, vehicular communication, and traffic flow theory, (2) to develop data substantiation models to detect anomalies irrespective of the cause of the anomality, and (3) to assess the applicability of traffic flow theory for data substantiation in vehicular networks. Chapters 1 and 2 are introductions and literature reviews respectively. The first main chapter describes the context of vehicular networks, traffic flow theory, and the intuition of applying traffic flow theory for substantiation in vehicular networks. The next three chapters elaborate, formulate, demonstrate, and evaluate the use of macroscopic views of traffic to substantiate microscopic data in vehicular networks. The first of these discusses the use of steady state conditions in traffic flow theory to substantiate data in vehicular networks, and the second describes the use of shockwave theory in traffic to substantiate data in vehicular networks. The third chapter develops a data substantiation model utilising localised views of traffic to provide an additional resolution to the previous models