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2024 | Buch

Introduction Kapitel lesen Erstes Kapitel lesen

Deception in Autonomous Transport Systems

Threats, Impacts and Mitigation Policies

herausgegeben von: Simon Parkinson, Alexandros Nikitas, Mauro Vallati

Verlag: Springer International Publishing

Buchreihe : Wireless Networks

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

This book provides a comprehensive overview of deception in autonomous transport systems. This involves investigating the threats facing autonomous transport systems and how they can contribute towards a deceptive attack, followed by their potential impact if successful, and finally, how they can be mitigated. The work in this book is grouped into three parts. This first part focuses on the area of smart cities, policies, and ethics. This includes critically appraising the trade-off between functionality and security with connected and autonomous vehicles. The second discusses a range of AI applications in the wider field of smart transport and mobility, such as detecting anomalies in vehicle behaviour to investigating detecting disobedient vehicles. Finally, the third part presents and discusses cybersecurity-related aspects to consider when dealing with Connected and Autonomous Vehicles (CAVs) and smart urban infrastructure. This includes analysing different attacks to investigating secure communication technologies.

CAVs are a game-changing technology with the potential to transform the way transport is perceived, mobility is serviced, travel ecosystems ‘behave’, and cities and societies as a whole function. There are many foreseen safety, accessibility and sustainability benefits resulting from the adoption of CAVs because of their ability, in theory, to operate error-free and collaboratively, ranging from accident prevention, congestion reduction and decreased carbon emissions to time savings, increased social inclusion, optimised routing, and better traffic control. However, no matter what the expected benefits are, CAVs are at the same time susceptible to an unprecedented number of new digital and physical threats. The severity of these threats has resulted in an increased effort to deepen our understanding of CAVs when it comes to their safety and resilience. In this complex and multi-faceted scenario, this book aims to provide an extensive overview of the risks related to the malicious exploitation of CAVs and beyond, the potential ways in which vulnerabilities can be exploited, prevention and mitigation policies and techniques, and the impact that the non-acceptance of Connected and Autonomous Mobility can have on the Smart City agenda.

This book targets researchers, practitioners, and advanced-level students in computer science and transport engineering.

Inhaltsverzeichnis

Frontmatter
Introduction
Abstract
Over half of the world’s 7.7 billion population now reside in urban environments and require good transport options so that they can reach those destinations, people and resources they need for enjoying an adequate standard of living and productivity. Efficient, safe, inclusive and sustainable mobility services and infrastructure have emerged therefore as a prerequisite (and possibly a benchmark) for city prosperity and societal well-being. Reaching this goal, however, is not easy. In the United Kingdom alone, 32.5 million vehicles are resulting in increasing congestion, with the average citizen losing 115 h to road traffic every year at a cost of £8 billion to the economy. In an era where artificial intelligence (AI) is revolutionizing technology and reshaping the world, smart traffic investments and intelligent transport systems (ITS) can be critical for reducing road traffic congestion and all its adverse impacts (i.e. environmental degradation, noise pollution, traffic accidents, unhealthy lifestyles, productivity losses).
Alexandros Nikitas, Simon Parkinson, Mauro Vallati

Smart Cities, Policies, and Ethics

Frontmatter
Ethical Dilemmas in Autonomous Driving: Philosophical, Social, and Public Policy Implications
Abstract
As autonomous driving technology continues to advance, ethical dilemmas are emerging that raise complex philosophical, social, and public policy questions. In this paper, we explore the ethical dilemmas that arise when programming autonomous vehicles to make life-and-death decisions in situations where accidents are unavoidable. We begin by examining the trolley problem, a classic ethical thought experiment that has become a popular framework for discussing ethical dilemmas in autonomous driving. We argue that while the trolley problem can be a useful starting point for thinking about ethical dilemmas, it is ultimately limited in its ability to capture the complexity and nuance of real-world situations. There are also social and public policy implications of autonomous driving technology. For instance, the widespread adoption of autonomous vehicles could lead to significant job loss in the transportation industry. Additionally, there are concerns about the impact of autonomous vehicles on urban planning, such as increased traffic congestion and the need for additional infrastructure. In conclusion, ethical dilemmas in autonomous driving pose significant challenges for society and require careful consideration of philosophical, social, and public policy implications. By engaging in ongoing ethical reflection and dialogue, we can ensure that the development and implementation of autonomous driving technology is guided by principles of justice, fairness, and respect for human dignity.
Emilios M. Saber, Stavros-Charalampos Kostidis, Ioannis Politis
Smart Cities: Concept, Pillars, and Challenges
Abstract
The concept of a smart city is synonymous with the enhancement and enrichment of quality of life. Smart city holds the promise of digitization of a city’s systems and processes, revolutionizes the green city concept, and has the potential to revert the global warming phenomenon. It ensures democratizing the data securely. Although smart city projects vary in their scopes and scales across the globe, in general, the fundamental building blocks of a smart city are consistent. In this chapter we review the common blocks and discuss challenges to be addressed in the future.
Saumya Bhatnagar
The Connected and Autonomous Vehicle Trade-Off: Functional Benefits versus Security Risks
Abstract
Connected and autonomous vehicles (CAVs) are becoming increasingly commonplace. Vehicles are equipped with a range of communication mechanisms, and progress is being made toward automation. These advancements are largely driven by functional benefits that enhance the driver’s experience or quality of service. These advancements are often the priority of vehicle manufacturers. There are many well-known security risks associated with CAV technology, which have resulted in a shift toward a secure-by-design paradigm. However, it is not always possible to mitigate all risks, and there is a need to understand the relationship between functional benefit and risk to determine the most appropriate mitigation technique. In this article, both functional benefits and security risks are discussed, laying the foundation for future research exploring this important intersection.
Na Liu, Alexandros Nikitas, Simon Parkinson
Connected and Autonomous Vehicles and Infrastructure Needs: Exploring Road Network Changes and Policy Interventions
Abstract
Connected and autonomous vehicles. (CAVs) are a paradigm-changing transport technology that has the potential to revolutionize road ecosystems, build environments and cities as a whole, by reshaping their very form. This is a transformation with critical space and culture dimensions that may be complicated and could be responsible for a plethora of unprecedented opportunities and challenges. Physical and digital infrastructure enhancement packages and reclassification of road networks will be necessary and should be proactively identified, designed, regulated, and delivered for CAVs to be effectively utilized going forward. Risks from handling mixed traffic situations to technology shortcomings and from lack of legislative frameworks and CAV-specific education to combating CAV deception are all points of reference for this chapter. Through a narrative literature review study, we offer suggestions for a new road classification framework that welcomes CAVs and then policy recommendations for improving CAV pro-people character.
Ioannis Chatziioannou, Stefanos Tsigdinos, Panagiotis G. Tzouras, Alexandros Nikitas, Efthimios Bakogiannis

AI Applications for Smart Transport and Mobility

Frontmatter
Centralized Intelligent Traffic Routing in the Light of Disobedience of Drivers
Abstract
In urban traffic control, centralised intelligent traffic routing techniques aim to plan routes for vehicles from the global point of view, that is, assigning routes to all vehicles not having their routes yet at once while considering some global objective function such as average travel time. Consequently, it might happen that different vehicles might get assigned different routes despite having the same origin and destination. Different routes might, however, entail different costs such as travel time and/or expected fuel consumption. Such differences might, however, motivate drivers to disobey their assigned routes if such routes are more expensive (e.g. take more time and/or more fuel). Disobedient drivers might then negatively affect costs of drivers who obeyed their routes. This chapter will elaborate on how disobedient drivers can affect the quality of the routes and what remedies might be taken to mitigate the problem.
Lukáš Chrpa
Detecting Abnormal Vehicle Behavior: A Clustering-Based Approach
Abstract
The increase in connected and autonomous functionality is increasing the potential for cyberattacks. However, the amount of data generated, processed, and stored by the modern vehicle is increasing, and this is creating the potential to detect and prevent abnormal and potentially dangerous situations from occurring. The purpose of this paper is to investigate the area of intrusion detection using automotive data and to lay the foundations of research in intrusion detection using unsupervised machine learning. As vehicles continue to become more connected, there is an increased possibility of them being exploited through a successful cyberattack. An example of a hacked Jeep Cherokee (Amruthnath and Gupta, A research study on unsupervised machine learning algorithms for early fault detection in predictive maintenance. In: 2018 5th International Conference on Industrial Engineering and Applications (ICIEA). IEEE, pp 355–361, 2018) and a remote exploitation strategy using multiple attack vectors (Checkoway et al., Comprehensive experimental analyses of automotive attack surfaces. In: USENIX security symposium, vol 4, no. 447–462, p 2021, 2011) demonstrated that vehicles can be remotely compromised. These examples demonstrate the potential to exploit aspects of the vehicle’s communication and control systems, resulting in unexpected behavior. There is therefore a strong need to detect unusual behavior. This paper is focused on detecting attacks targeting a vehicle by identifying abnormal vehicle behavior, exhibited through vehicle control data. To achieve this, synthetic vehicle data containing detectable abnormalities is generated and used for analysis and detection to help detect cyberattacks. Unsupervised machine learning techniques are used to detect abnormal entries in-vehicle data. The synthetic data is generated based on datasets comparable with those generated during normal vehicle operations, before being used to manually insert skewness to generate abnormalities, before using and evaluating various unsupervised learning algorithms.
Shrey Verma, Simon Parkinson, Saad Khan
AI Approaches on Urban Public Transport Routing
Abstract
Artificial intelligence (AI) is an innovative concept that can provide potentials to overcome the challenges of operation in public transport (PT) systems. The AI applications in the PT operation offer the opportunities to alleviate traffic congestion and enhance the accessibility, mobility, and reliability of services with a more efficient and effective PT system. One of the key areas that AI is beneficial is in optimization of network route design. Examples of AI approaches that are finding their way under fuel and electric vehicle conditions include genetic algorithm (GA), simulated annealing (SA), etc. The more promising application of AI techniques requires a well-understood knowledge of multiple data sets and features of different PT services, including conventional buses and demand-responsive transit systems, especially when dealing with travel demands fluctuating in time and space. Moreover, the emerging development in connected and autonomous vehicles (CAVs) is leading a rapid improvement in flexibility, punctuality, vehicle safety, and transit priority. The purpose of this chapter is to review AI approaches applied on public transport operation, especially on routing. The overview concludes by addressing the issues and challenges of AI applications in PT operation.
Rongge Guo

Cyber Security for Deceitful Connected and Autonomous Vehicles

Frontmatter
Cyber Threat Intelligence Analysis for Situational Understanding in Autonomous Transport Systems
Abstract
Autonomous transport systems promise to change how mobility is serviced, with potential ramifications in how cities and societies function. Among others, benefits include accident prevention and decreased carbon emissions. Like any other computer system, they face a plethora of security threats, both traditional and novel. In this work, we show how cyber threat intelligence analysis techniques can help understand and investigate—and potentially mitigate—security threats to autonomous transport systems. We exemplify the adoption of cyber threat intelligence analysis techniques and threat modelling in a concrete—albeit simple—case study. We finally discuss some implications involving cyber threat intelligence analysis techniques in autonomous transport systems and how proper uncertainty management is a powerful tool for preventing and mitigating many cyber threats affecting autonomous transport systems.
Federico Cerutti
Interaction Attacks as Deceitful Connected and Automated Vehicle Behavior
Abstract
The present chapter aims at exploring the idea of interaction attacks as a form of deceitful connected and automated vehicle (CAV) behavior that requires to be counteracted both on the technical and social levels. After some introductory remarks on cyberattacks, deception, and driving automation, we argue that interaction attacks and related risks still require to be adequately conceptualized. To this aim, we draw on Norbert Wiener’s notes on animals and cybernetic systems to show that the possibility of interaction attacks based on deceptive behavior stems from the very nature of control in machines. Using Wiener’s insights and recent literature as a blueprint, we then provide a conceptual description of interaction attacks involving CAVs. In addition, we discuss a case study aimed at further clarifying the phenomenon. Finally, we advance some remarks on interaction attacks as a form of deceitful CAV behavior according to the framework elaborated by (Nikitas et al., Transp Policy 122: 1–10, 2022) and call for further research on such a critical issue.
Fabio Fossa, Luca Paparusso, Francesco Braghin
Securing Vehicle-to-Drone (V2D) Communications: Challenges and Solutions
Abstract
This chapter provides an overview of vehicle-to-drone (V2D) communications, highlighting its fundamentals, applications, and key components. It explores how V2D communication enhances perception capabilities and facilitates advanced functionalities. The chapter investigates into the critical security and privacy issues specific to V2D, including the threat landscape and challenges related to authentication and authorization. Several real-world scenarios illustrating compromised security in V2D are discussed, emphasizing the need for robust security solutions. Finally, key security solutions for V2D communication are presented, offering insights into mitigating risks and ensuring the integrity and reliability of V2D interactions.
S.  M. Riazul Islam, Mohammad Aminul Hoque, Mahmud Hossain
The Use of GPS Spoofing Attacks in Location Deception
Abstract
Global positioning systems (GPS) play an integral role in location-based systems. These systems are pervasive throughout the use of connected and autonomous vehicles (CAVs), as being able to accurately determine location is essential to provide CAV functionality. This integral use of GPS has created the potential for CAV functionality dependent on knowing the location to be attacked, compromising the vehicle and instigating widespread impacts throughout the traffic infrastructure. The technical means as to how GPS systems can be spoofed are well known; however, less well-known and considered in literature is how GPS spoofing might be targeted to acquire preferential and deceitful behaviours. In this work, the necessary background into GPS workings is provided, before analysing how spoofing could be specifically used to gain preferential behaviour. This article serves as an introduction to this important and significant topic.
Saad Khan, Simon Parkinson
Metadaten
Titel
Deception in Autonomous Transport Systems
herausgegeben von
Simon Parkinson
Alexandros Nikitas
Mauro Vallati
Copyright-Jahr
2024
Electronic ISBN
978-3-031-55044-7
Print ISBN
978-3-031-55043-0
DOI
https://doi.org/10.1007/978-3-031-55044-7

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