Distributing Cyber-Physical Systems Simulation: The Satellite Constellation Case

The goal of this position paper is to contribute for the improving of Cyber-Physical System (CPS) simulations by introducing distribution. CPS use computations andcommunication tightly interacting with physical processes. So a CPS simulation needs to tackle with three kinds of simulations: the computational simulation, the physical simulation, and the communication simulation. In this paper, we will focus on the communication simulation, and its interaction with the two others simulations. We will draw a landscape of the existing concepts and technologies for distributing communication simulation, and then propose an architecture for interacting with the whole CPS simulation. We will apply this architecture to a simulation of a satellite constellation, where satellites can be simulated with different levels of precision, from the simple generic mathematical model to the heavy-featured CPS simulation

Robust and secure resource management for automotive cyber-physical systems

2022 Spring.Includes bibliographical references.Modern vehicles are examples of complex cyber-physical systems with tens to hundreds of interconnected Electronic Control Units (ECUs) that manage various vehicular subsystems. With the shift towards autonomous driving, emerging vehicles are being characterized by an increase in the number of hardware ECUs, greater complexity of applications (software), and more sophisticated in-vehicle networks. These advances have resulted in numerous challenges that impact the reliability, security, and real-time performance of these emerging automotive systems. Some of the challenges include coping with computation and communication uncertainties (e.g., jitter), developing robust control software, detecting cyber-attacks, ensuring data integrity, and enabling confidentiality during communication. However, solutions to overcome these challenges incur additional overhead, which can catastrophically delay the execution of real-time automotive tasks and message transfers. Hence, there is a need for a holistic approach to a system-level solution for resource management in automotive cyber-physical systems that enables robust and secure automotive system design while satisfying a diverse set of system-wide constraints. ECUs in vehicles today run a variety of automotive applications ranging from simple vehicle window control to highly complex Advanced Driver Assistance System (ADAS) applications. The aggressive attempts of automakers to make vehicles fully autonomous have increased the complexity and data rate requirements of applications and further led to the adoption of advanced artificial intelligence (AI) based techniques for improved perception and control. Additionally, modern vehicles are becoming increasingly connected with various external systems to realize more robust vehicle autonomy. These paradigm shifts have resulted in significant overheads in resource constrained ECUs and increased the complexity of the overall automotive system (including heterogeneous ECUs, network architectures, communication protocols, and applications), which has severe performance and safety implications on modern vehicles. The increased complexity of automotive systems introduces several computation and communication uncertainties in automotive subsystems that can cause delays in applications and messages, resulting in missed real-time deadlines. Missing deadlines for safety-critical automotive applications can be catastrophic, and this problem will be further aggravated in the case of future autonomous vehicles. Additionally, due to the harsh operating conditions (such as high temperatures, vibrations, and electromagnetic interference (EMI)) of automotive embedded systems, there is a significant risk to the integrity of the data that is exchanged between ECUs which can lead to faulty vehicle control. These challenges demand a more reliable design of automotive systems that is resilient to uncertainties and supports data integrity goals. Additionally, the increased connectivity of modern vehicles has made them highly vulnerable to various kinds of sophisticated security attacks. Hence, it is also vital to ensure the security of automotive systems, and it will become crucial as connected and autonomous vehicles become more ubiquitous. However, imposing security mechanisms on the resource constrained automotive systems can result in additional computation and communication overhead, potentially leading to further missed deadlines. Therefore, it is crucial to design techniques that incur very minimal overhead (lightweight) when trying to achieve the above-mentioned goals and ensure the real-time performance of the system. We address these issues by designing a holistic resource management framework called ROSETTA that enables robust and secure automotive cyber-physical system design while satisfying a diverse set of constraints related to reliability, security, real-time performance, and energy consumption. To achieve reliability goals, we have developed several techniques for reliability-aware scheduling and multi-level monitoring of signal integrity. To achieve security objectives, we have proposed a lightweight security framework that provides confidentiality and authenticity while meeting both security and real-time constraints. We have also introduced multiple deep learning based intrusion detection systems (IDS) to monitor and detect cyber-attacks in the in-vehicle network. Lastly, we have introduced novel techniques for jitter management and security management and deployed lightweight IDSs on resource constrained automotive ECUs while ensuring the real-time performance of the automotive systems

Machine learning and blockchain technologies for cybersecurity in connected vehicles

Future connected and autonomous vehicles (CAVs) must be secured againstcyberattacks for their everyday functions on the road so that safety of passengersand vehicles can be ensured. This article presents a holistic review of cybersecurityattacks on sensors and threats regardingmulti-modal sensor fusion. A compre-hensive review of cyberattacks on intra-vehicle and inter-vehicle communicationsis presented afterward. Besides the analysis of conventional cybersecurity threatsand countermeasures for CAV systems,a detailed review of modern machinelearning, federated learning, and blockchain approach is also conducted to safe-guard CAVs. Machine learning and data mining-aided intrusion detection systemsand other countermeasures dealing with these challenges are elaborated at theend of the related section. In the last section, research challenges and future direc-tions are identified

Cyber Threats Facing Autonomous and Connected Vehicles: Future Challenges

Vehicles are currently being developed and sold with increasing levels of connectivity and automation. As with all networked computing devices, increased connectivity often results in a heightened risk of a cyber security attack. Furthermore, increased automation exacerbates any risk by increasing the opportunities for the adversary to implement a successful attack. In this paper, a large volume of publicly accessible literature is reviewed and compartmentalised based on the vulnerabilities identified and mitigation techniques developed. This review highlighted that the majority of research is reactive and vulnerabilities are often discovered by friendly adversaries (white-hat hackers). Many gaps in the knowledge base were identified. Priority should be given to address these knowledge gaps to minimise future cyber security risks in the connected and autonomous vehicle sector

External attacks on automotive system through wireless communication channels

The reliance of today’s automotive system on electronics control system is expected to make the cars to be state-of-the-art vehicle. However, this technology dependency results in the cars to be exposed to attacks by the hacker through the manipulation of electronics system. Previously, for the attacker to compromise car’s system, he/she must access the car directly and internally. However, with the incorporation of wireless technologies such as Bluetooth and cellular into automotive system for example in its telematic units, the attacks are evolved from internal attacks into remote attack where the adversary does not have to internally access the car’s system. This paper analyses the vulnerabilities of the automotive system by the remote attacks performed through Bluetooth and cellular. Once the vulnerabilities were analyzed, the threats imposed by these vulnerabilities are accessed. Two scenarios namely theft and surveillance are used to exemplify the threats that are carried by the vulnerability of the automotive system to the remote attacks. From the vulnerability analysis and threat assessment, it can be deduced that the automotive system is vulnerable to attacks and proper countermeasure must be taken to curb the implication from the attacks.Keywords: Hardware Trojan, Insertion, Third-part IP, Trus

Recursive Set-Membership State Estimation Over a FlexRay Network

10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 61873148, 61873169, 61903253 and 61933007); Royal Society of the U.K.; Alexander von Humboldt Foundation of Germany

Ultimately Bounded PID Control For T-S Fuzzy Systems Under FlexRay Communication Protocol

This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI10.1109/TFUZZ.2023.3282044, IEEE Transactions on Fuzzy SystemsNational Natural Science Foundation of China (Grant Number: 61933007, 62273087, 62273180, U21A2019 and 62233012); Shanghai Pujiang Program of China (Grant Number: 22PJ1400400); Hainan Province Science and Technology Special Fund of China (Grant Number: ZDYF2022SHFZ105); Royal Society of the UK; Alexander von Humboldt Foundation of Germany