Security Of Intelligent Transportation Systems Research Articles

A Formal Approach to Design and Security Verification of Operating Systems for Intelligent Transportation Systems Based on Object Model

Operating system in intelligent transportation systems (ITSs) is a complex software system whose correctness and security are not obvious. There are advances in formal description and verification of operating systems in ITSs recently and they mainly focus on bottom-up proofs in which the source codes satisfy certain expected properties expressed by logic formulae. In this paper, we propose a layered object model for operating systems in ITSs. This model includes functionality layer, refinement layer and concrete layer. We consider the operating system object model as a logic system ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L)$</tex-math> </inline-formula> with variables representing the objects of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L$</tex-math> </inline-formula> , and a series of logic formulae for security and functional configurations in security of ITSs. We establish a mathematical structure as a domain of discourse for operating system in ITSs and accordingly, construct a mapping from operating system objects to the domain. In this way, we propose a formal method to verify the operating system security properties and configurations in ITSs. We use the virtual memory management part of our self-designed operating system VSOS as an example to illustrate the model and show that the claimed security properties can be rigorously proven for ITSs. The evaluation and verification of VSOS indicate that the proposed model implementation is feasible and achieves the security goals.

Adversarial Deep Learning based Dampster–Shafer data fusion model for intelligent transportation system

Intelligent Transportation Systems (ITS) have revolutionized transportation by incorporating advanced technologies for efficient and safe mobility. However, these systems face challenges ensuring security and resilience against adversarial attacks. This research addresses these challenges and introduces a novel Dampster–Shafer data fusion-based Adversarial Deep Learning (DS-ADL) Model for ITS in fog cloud environments. Our proposed model focuses on three levels of adversarial attacks: original image level, feature level, and decision level. Adversarial examples are generated at each level to evaluate the system’s vulnerability comprehensively. To enhance the system’s capabilities, we leverage the power of several vital components. Firstly, we employ Dempster–Shafer-based Multimodal Sensor Fusion, enabling the fusion of information from multiple sensors for improved scene understanding. This fusion approach enhances the system’s perception and decision-making abilities. For feature extraction and classification, we utilize ResNet 101, a deep learning architecture known for its effectiveness in computer vision tasks. We introduced a novel Monomodal Multidimensional Gaussian Model (MMGM-DD) based Adversarial Detection approach to detect adversarial examples. This detection mechanism enhances the system’s ability to identify and mitigate adversarial attacks in real-time. Additionally, we incorporate the Defensive Distillation method for adversarial training, which trains the model to be robust against attacks by exposing it to adversarial examples during the training process. To evaluate the performance of our proposed model, we utilize two datasets: Google Speech Command version 0.01 and the German Traffic Sign Recognition Benchmark (GTSRB). Evaluation metrics include latency delay and computation time (fog–cloud), accuracy, MSE, loss, and F-score for attack detection and defense. The results and discussions demonstrate the effectiveness of our Dampster–Shafer data fusion-based Adversarial Deep Learning Model in enhancing the robustness and security of ITS in fog–cloud environments. The model’s ability to detect and defend against adversarial attacks while maintaining low-latency fog–cloud operations highlights its potential for real-world deployment in ITS.

Attack Modeling Methodology and Taxonomy for Intelligent Transportation Systems

With newer technologies, the embedded hardware and software in traditional vehicles and traffic control infrastructure continue to become more interconnected and more vulnerable. To assist in dealing with existing and potential vulnerabilities, we present a novel attack modeling methodology, taxonomy, and metrics (relative average waiting time, average network flow, impacts and rate of changes) to model, simulate, and meaningfully evaluate the security of Intelligent Transportation Systems. We implement our work in two different architectures: 1) Newell’s Car-Following Model with Bounded Acceleration (the BA-Newell Model) in Matlab and 2) Intelligent Driver Model in Veins. Our code is entirely open-sourced and will be maintained so that the ITS community may use it as a tool. We observe that the architectural-related metric values for sample attack simulation results are similar and transferable; where, for example, the rate of change values have range of average distances 1.8-3.5% for network flow impact and 3.3-9.6% for wait time impact.

Detection and Isolation of False Data Injection Attack in Intelligent Transportation System via Robust State Observer

As the future of transportation systems, the intelligent transportation system is a promising technology to improve the increasingly serious traffic problems. However, the integration of cyber-physical systems makes them vulnerable to new cyber–physical attacks. To ensure the security of intelligent transportation systems, a novel robust state observer-based detection and isolation method against false data injection attacks is developed. Based on the constructed dynamic model of intelligent vehicle networking, the covert characteristic of a false data injection attack is analyzed. Then, a novel state residuals-based detection criterion is developed by using a real-time observed state. To shorten the detection time, an adaptive detection threshold is designed to replace the existing computed threshold. In addition, robust state observer banks are established to isolate multiple injected attacks. Finally, simulation results on the vehicle networking system demonstrate the effectiveness of the developed detection and isolation method against false data injection attacks.

Threshold Key Management Scheme for Blockchain-Based Intelligent Transportation Systems

Intelligent transportation systems (ITS) have always been an important application of Internet of Things (IoT). Today, big data and cloud computing have further promoted the construction and development of ITS. At the same time, the development of blockchain has also brought new features and convenience to ITS. However, due to the endless emergence of increasingly advanced types of attacks, the security of blockchain-based ITS needs more attention from industry and academia. In this paper, we focus on exploring the primitives in cryptography to guarantee the security of blockchain-based ITS. In particular, the authentication, encryption, and key management schemes in cryptography are discussed. Furthermore, we propose two methods for achieving the threshold key management in blockchain-based ITS. The proposed threshold key management scheme (with threshold t ) enables various stakeholders to recover a secret if the number of participated stakeholders is at least t . It should be noted that the proposed threshold key management scheme is efficient and secure for multiple users in blockchain-based ITS, especially for the data-sharing scenario.

A Survey on the Current Security Landscape of Intelligent Transportation Systems

With the proliferation of embedded technologies and wireless capabilities, today’s vehicles are no longer isolated mechanical machines. They become part of a hyper-connected system -Intelligent Transportation Systems (ITS)- that has the potential to support multiple levels of autonomy and intelligence improving considerably the safety, efficiency, and sustainability of transportation networks. However, this raises new security issues that make the whole system prone to cybersecurity attacks that threaten both the safety and privacy of all road-users. This article gives a short background tutorial on the main security issues and the different attacks that hinder Intelligent Transport Systems. To enable secure and safe ITS applications, this article provides a comprehensive analysis of existing solutions and highlights their strengths and limitations. Finally, this survey presents key challenges in the field, and discusses recent trends that must be factored in by researchers, implementers, and car manufactures to improve the security of ITS.

Intelligent Transportation System Security: Impact-Oriented Risk Assessment of in-Vehicle Networks

The concept of Intelligent Transportation Systems (ITS) was developed in the 1980s when then upcoming technologies and cognitive information were incorporated into the road infrastructures and vehicles. The ITS infrastructure is critical yet not immune to both physical and cyber threats. Vehicles are cyber-physical systems which are a core component of ITS, can be either a target or a launching point for an attack on the ITS network. Unknown vehicle security vulnerabilities trigger a race among adversaries to exploit the weaknesses and security experts to mitigate the vulnerability. In this study, we identified opportunities for adversaries to take control of the in-vehicle network, which can compromise the safety, privacy, reliability, efficiency, and security of the transportation system. This study contributes in three ways to the literature of ITS security and resiliency. First, we aggregate individual risks that are associated with hacking the in-vehicle network to determine system-level risk. Second, we employ a risk-based model to conduct a qualitative vulnerability-oriented risk assessment. Third, we identify the consequences of hacking the in-vehicle network through a risk-based approach, using an impact-likelihood matrix. The qualitative assessment communicates risk outcomes for policy analysis. The outcome of this study would be of interest and usefulness to policymakers and engineers concerned with the potential vulnerabilities of such critical infrastructures.

Cybersecurity in Intelligent Transportation Systems

Intelligent Transportation Systems (ITS) are emerging field characterized by complex data model, dynamics and strict time requirements. Ensuring cybersecurity in ITS is a complex task on which the safety and efficiency of transportation depends. The imposition of standards for a comprehensive architecture, as well as specific security standards, is one of the key steps in the evolution of ITS. The article examines the general outlines of the ITS architecture and security issues. The main focus of security approaches is: configuration and initialization of the devices during manufacturing at perception layer; anonymous authentication of nodes in VANET at network layer; defense of fog-based structures at support layer and description and standardization of the complex model of data and metadata and defense of systems, based on AI at application layer. The article oversees some conventional methods as network segmentation and cryptography that should be adapted in order to be applied in ITS cybersecurity. The focus is on innovative approaches that have recently been trying to find their place in ITS security strategies. These approaches includes blockchain, bloom filter, fog computing, artificial intelligence, game theory and ontologies. In conclusion, a correlation is made between the commented methods, the problems they solve and the architectural layers in which they are applied.

Virus-traffic coupled dynamic model for virus propagation in vehicle-to-vehicle communication networks

With the development of connected vehicle technology, virus propagation that exists in a traditional network environment will gradually penetrate vehicle-to-vehicle (V2V) communication networks, thus posing a serious threat to the security of intelligent transportation systems (ITS). Understanding the characteristics of virus propagation through space and time is the key to ensuring the safety of ITS. However, most existing studies on virus propagation have ignored the dynamic relationship between virus transmission and traffic flow based on the assumption that the probability of virus infection is a constant. In light of this, this study proposes a two-layer model, called the virus-traffic coupled dynamic model, to investigate virus propagation in V2V communication networks. First, the dynamics of traffic flow and vehicular mobility are formulated as many update rules between cellular automata in the lower layer; then, due to the similarity between biological epidemic dissemination and virus propagation, an epidemic model called the susceptible-infected-recovered (SIR) was built to model the virus propagation process in the upper layer; finally, the lower and upper layer are connected by the probability of virus infection. Numerical experiments show that the model can accurately reproduce the process of virus transmission over space and time. The experiments also prove that reducing the probability of virus infection can constrain the spread of the virus effectively for both different communication range limits and various traffic densities.

The UMTS-AKA Protocols for Intelligent Transportation Systems

The integration of communication protocols into transport systems is a much adored research area today. Much of seminal work has been reported on the topic of intelligent transportation systems (ITS) in the recent years.Many advanced techniques have been garnered to improve online communication and to promote the security, comfort, and efficiency of ITS. Of primary importance to the effective application of ITS is the communication protocol used. A fascinating development is that the yesterday's Global System for Mobile Communication protocol is being replaced by the Universal Mobile Telecommunication System protocol, which is the third-generation mobile technology. This article attempts to identify a suitable communication system for ITS applications. It is impracticable to substantially modify the original UMTS-IMS-AKA protocol which is in practice because it can disturb the operation of the current system, and thus we explore other possibilities through this research. We investigate a novel protocol to make the original UMTS-IMS-AKA protocol compliant with ITS as well as adaptable into the current UMTS protocol.