37 research outputs found
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
Security and Interpretability in Automotive Systems
Controller area network (CAN) is the most commonly found bus protocol in automotive systems. The two-wire bus protocol helps accomplish sophisticated vehicle services in real-time through complex interactions between hardware components. However, the lack of any sender authentication mechanism in place makes CAN susceptible to security vulnerabilities and threats. To address the insecure nature of the system, this thesis demonstrates a sender authentication technique that uses power consumption measurements of the electronic control units (ECUs) and a classification model to determine the transmitting states of the ECUs. The method's evaluation in real-world settings shows that the technique applies in a broad range of operating conditions and achieves good accuracy.
A key challenge of machine learning-based security controls is the potential of false positives. A false-positive alert may induce panic in operators, lead to incorrect reactions, and in the long run cause alarm fatigue. For reliable decision-making in such a circumstance, knowing the cause for unusual model behavior is essential. But, the black-box nature of these models makes them uninterpretable. Therefore, another contribution of this thesis explores explanation techniques for inputs of type image and time series that (1) assign weights to individual inputs based on their sensitivity toward the target class, (2) and quantify the variations in the explanation by reconstructing the sensitive regions of the inputs using a generative model.
In summary, this thesis presents methods for addressing the security and interpretability in automotive systems, which can also be applied in other settings where safe, transparent, and reliable decision-making is crucial
Trustworthiness in Mobile Cyber Physical Systems
Computing and communication capabilities are increasingly embedded in diverse objects and structures in the physical environment. They will link the ‘cyberworld’ of computing and communications with the physical world. These applications are called cyber physical systems (CPS). Obviously, the increased involvement of real-world entities leads to a greater demand for trustworthy systems. Hence, we use "system trustworthiness" here, which can guarantee continuous service in the presence of internal errors or external attacks. Mobile CPS (MCPS) is a prominent subcategory of CPS in which the physical component has no permanent location. Mobile Internet devices already provide ubiquitous platforms for building novel MCPS applications. The objective of this Special Issue is to contribute to research in modern/future trustworthy MCPS, including design, modeling, simulation, dependability, and so on. It is imperative to address the issues which are critical to their mobility, report significant advances in the underlying science, and discuss the challenges of development and implementation in various applications of MCPS
EXT-TAURUM P2T: an Extended Secure CAN-FD Architecture for Road Vehicles
The automobile industry is no longer relying on pure mechanical systems; instead, it benefits from advanced Electronic Control Units (ECUs) in order to provide new and complex functionalities in the effort to move toward fully connected cars. However, connected cars provide a dangerous playground for hackers. Vehicles are becoming increasingly vulnerable to cyber attacks as they come equipped with more connected features and control systems. This situation may expose strategic assets in the automotive value chain. In this scenario, the Controller Area Network (CAN) is the most widely used communication protocol in the automotive domain. However, this protocol lacks encryption and authentication. Consequently, any malicious/hijacked node can cause catastrophic accidents and financial loss. Starting from the analysis of the vulnerability connected to the CAN communication protocol in the automotive domain, this paper proposes EXT-TAURUM P2T a new low-cost secure CAN-FD architecture for the automotive domain implementing secure communication among ECUs, a novel key provisioning strategy, intelligent throughput management, and hardware signature mechanisms. The proposed architecture has been implemented, resorting to a commercial Multi-Protocol Vehicle Interface module, and the obtained results experimentally demonstrate the approach’s feasibility
Energy Harvesting and Sensor Based Hardware Security Primitives for Cyber-Physical Systems
The last few decades have seen a large proliferation in the prevalence of cyber-physical systems. Although cyber-physical systems can offer numerous advantages to society, their large scale adoption does not come without risks. Internet of Things (IoT) devices can be considered a significant component within cyber-physical systems. They can provide network communication in addition to controlling the various sensors and actuators that exist within the larger cyber-physical system. The adoption of IoT features can also provide attackers with new potential avenues to access and exploit a system\u27s vulnerabilities. Previously, existing systems could more or less be considered a closed system with few potential points of access for attackers. Security was thus not typically a core consideration when these systems were originally designed. The cumulative effect is that these systems are now vulnerable to new security risks without having native security countermeasures that can easily address these vulnerabilities. Even just adding standard security features to these systems is itself not a simple task. The devices that make up these systems tend to have strict resource constraints in the form of power consumption and processing power. In this dissertation, we explore how security devices known as Physically Unclonable Functions (PUFs) could be used to address these concerns.
PUFs are a class of circuits that are unique and unclonable due to inherent variations caused by the device manufacturing process. We can take advantage of these PUF properties by using the outputs of PUFs to generate secret keys or pseudonyms that are similarly unique and unclonable. Existing PUF designs are commonly based around transistor level variations in a special purpose integrated circuit (IC). Integrating these designs within a system would still require additional hardware along with system modification to interact with the device. We address these concerns by proposing a novel PUF design methodology for the creation of PUFs whose integration within these systems would minimize the cost of redesigning the system by reducing the need to add additional hardware. This goal is achieved by creating PUF designs from components that may already exist within these systems.
A PUF designed from existing components creates the possibility of adding a PUF (and thus security features) to the system without actually adding any additional hardware. This could allow PUFs to become a more attractive security option for integration with resource constrained devices. Our proposed approach specifically targets sensors and energy harvesting devices since they can provide core functions within cyber-physical systems such as power generation and sensing capabilities. These components are known to exhibit variations due to the manufacturing process and could thus be utilized to design a PUF. Our first contribution is the proposal of a novel PUF design methodology based on using components which are already commonly found within cyber-physical systems. The proposed methodology uses eight sensors or energy harvesting devices along with a microcontroller.
It is unlikely that single type of sensor or energy harvester will exist in all possible cyber-physical systems. Therefore, it is important to create a range of designs in order to reach a greater portion of cyber-physical systems. The second contribution of this work is the design of a PUF based on piezo sensors. Our third contribution is the design of a PUF that utilizes thermistor temperature sensors. The fourth contribution of this work is a proposed solar cell based PUF design. Furthermore, as a fifth contribution of this dissertation we evaluate a selection of common solar cell materials to establish which type of solar cell would be best suited to the creation of a PUF based on the operating conditions. The viability of the proposed designs is evaluated through testing in terms of reliability and uniformity. In addition, Monte Carlo simulations are performed to evaluate the uniqueness property of the designs.
For our final contribution we illustrate the security benefits that can be achieved through the adoption of PUFs by cyber-physical systems. For this purpose we chose to highlight vehicles since they are a very popular example of a cyber-physical system and they face unique security challenges which are not readily solvable by standard solutions. Our contribution is the proposal of a novel controller area network (CAN) security framework that is based on PUFs. The framework does not require any changes to the underlying CAN protocol and also minimizes the amount of additional message passing overhead needed for its operation. The proposed framework is a good example of how the cost associated with implementing such a framework could be further reduced through the adoption of our proposed PUF designs. The end result is a method which could introduce security to an inherently insecure system while also making its integration as seamless as possible by attempting to minimize the need for additional hardware
TAURUM P2T: Advanced secure CAN-FD architecture for road vehicle
Interconnected devices are growing very fast in today's automotive market, providing new and complex features that cover very different domains. This vast and continuous requirement for new features brings to impact areas categorized as real-time safety-critical devices, opening the possibility to add potential vulnerabilities. By analyzing the security vulnerabilities within vehicle networks, this paper aims at proposing a new generation of a secure architecture based on Controller Area Network (CAN) called TAURUM P2T. This new architecture looks at mitigating the vulnerabilities found in the current network systems of road vehicles by introducing a low-cost and efficient solution based on the introduction of a Secure CAN network able to implement a novel key provisioning strategy. The proposed architecture has been implemented, resorting to a commercial Multi-Protocol Vehicle Interface module, and the obtained results experimentally demonstrate the approach's feasibility
Process-Aware Defenses for Cyber-Physical Systems
The increasing connectivity is exposing safety-critical systems to cyberattacks that can cause real physical damage and jeopardize human lives. With billions of IoT devices added to the Internet every year, the cybersecurity landscape is drastically shifting from IT systems and networks to systems that comprise both cyber and physical components, commonly referred to as cyber-physical systems (CPS). The difficulty of applying classical IT security solutions in CPS environments has given rise to new security techniques known as process-aware defense mechanisms, which are designed to monitor and protect industrial processes supervised and controlled by cyber elements from sabotage attempts via cyberattacks. In this thesis, we critically examine the emerging CPS-driven cybersecurity landscape and investigate how process-aware defenses can contribute to the sustainability of highly connected cyber-physical systems by making them less susceptible to crippling cyberattacks. We introduce a novel data-driven model-free methodology for real-time monitoring of physical processes to detect and report suspicious behaviour before damage occurs. We show how our model-free approach is very lightweight, does not require detailed specifications, and is applicable in various CPS environments including IoT systems and networks. We further design, implement, evaluate, and deploy process-aware techniques, study their efficacy and applicability in real-world settings, and address their deployment challenges
Automotive firmware extraction and analysis techniques
An intricate network of embedded devices, called Electronic Control Units (ECUs), is responsible for the functionality of a modern vehicle. Every module processes a myriad of information and forwards it on to other nodes on the network, typically an automotive bus such as the Controller Area Network (CAN). Analysing embedded device software, and automotive in particular, brings many challenges.
The analyst must, especially in the notoriously secretive automotive industry, first lift the ECU firmware from the hardware, which typically prevents unauthorised access. In this thesis, we address this problem in two ways:
- We detail and bypass the access control mechanism used in diagnostic protocols in ECU firmware. Using existing diagnostic functionality, we present a generic technique to download code to RAM and execute it, without requiring physical access to the ECU. We propose a generic firmware readout framework on top of this, which only requires access to the CAN bus.
- We analyse various embedded bootloaders and combine dynamic analysis with low-level hardware fault attacks, resulting in several fault-injection attacks which bypass on-chip readout protection.
We then apply these firmware extraction techniques to acquire immobiliser firmware by two different manufacturers, from which we reverse engineer the DST80 cipher and present it in full detail here. Furthermore, we point out flaws in the key generation procedure, also recovered from the ECU firmware, leading to a full key recovery based on publicly readable transponder pages
Spectra: Detecting Attacks on In-Vehicle Networks through Spectral Analysis of CAN-Message Payloads
Nowadays, vehicles have complex in-vehicle networks that have recently been shown to be increasingly vulnerable to cyber-attacks capable of taking control of the vehicles, thereby threatening the safety of the passengers. Several countermeasures have been proposed in the literature in response to the arising threats, however, hurdle requirements imposed by the industry is hindering their adoption in practice. In this paper, we propose SPECTRA, a data-driven anomaly-detection mechanism that is based on spectral analysis of CAN-message payloads. SPECTRA does not abide by the strict specifications predefined for every vehicle model and addresses key real-world deployability challenges