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Businessman on blurred background using antivirus to block a cyber attack 3D rendering

System Security

System Security is a research theme within the Centre for Future Transport and Cities. 

Focus of our research

The Systems Security Group (SSG) is concerned with cyber-physical systems security with a strong focus on automotive and transport systems. Of particular interest to the group is answering the questions to how we build secure systems. These include:

  • What are the methods for rigorous design and qualified tools to deliver on such design?
  • Once deployed, how do we analyse such systems to detect and monitor for stealthy threats?
  • What are the effective means to inform secure engineering practices and standards for industry?
  • What national policy instruments are needed to ensure safe and secure operation of such systems?
  • SSG’s vision is to carry out novel, relevant and high impact security/safety research that meets the needs of and benefits society.

  • SSG’s core mission is to research and engineer secure and resilient cyber-physical systems for automotive and transport industry, working in collaboration with partners in industry, academia, and government.

Key researchers

Name Title Email
Soufiene Djahel Professor

ae3095@coventry.ac.uk

Rakib Abdur Associate Professor ad9812@coventry.ac.uk
Jeremy Bryans Assistant Professor ac1126@coventry.ac.uk
Hesamaldin Jadidbonab Assistant Professor ad4953@coventry.ac.uk

Project spotlight

Secure-CAV: Advanced Cybersecurity for Connected and Autonomous Vehicles - Secure-CAV is an ambitious collaborative project that aims to improve the safety and security of tomorrow’s connected and autonomous vehicles (CAVs): and in doing so, ultimately advance the wellbeing of our citizens and infrastructure.

The project addresses one of the most pressing “pain points” in the transportation industry: cybersecurity. Today, we are moving progressively through increased levels of driver assistance, with the eventual aim of deploying full autonomy. The electronic content of vehicles is therefore growing rapidly. Vehicles are also increasingly connected, becoming effectively IoT-style devices.

The result of all this is that the opportunities for malicious actors to hack into vehicles’ systems are becoming greater. And at the same time, the potential consequences of failing to detect and mitigate such attacks are skyrocketing: a compromised autonomous vehicle is no mere inconvenience, it is a potential threat to life.

The Secure-CAV project seeks to answer these challenges by developing cybersecurity solutions that can be embedded deep in the underlying electronic hardware within a CAV. To do so, it brings together a multidisciplinary team: Cybersecurity specialist consultancy Copper Horse, leading hardware-based cybersecurity provider Siemens EDA, Machine Learning (ML) experts from the University of Southampton and the Institute of Future Transport at Coventry University. The socio-economic impacts of cybersecurity attacks are tremendous, with the automotive industry estimated to lose £20 billion annually by 2023 [Upstream Security]. Co-funded by the UK’s innovation agency Innovate UK, the Secure-CAV project is tackling a very real market and societal need with new thinking and technology.

TOMSAC: Trade-off Management between Safety and Cybersecurity - The TOMSAC project aims to propose novel and effective solutions for managing trade-offs between cybersecurity and safety in converging Cyber Physical (CPS) and Internet of Things (IoT) systems.

The convergence of IoT and CPS systems means there is a need for effective methods to manage trade-offs between cybersecurity and safety measures that are interdependent and often complementing or conflicting. Assuring cybersecurity can introduce unintended safety consequences and vice versa. Early analysis of existing work in this area indicates an urgent need of methods for managing trade-off between safety and cybersecurity. TOMSAC will achieve its aims through a comprehensive literature review, consultations with user partners and an industry survey.

The project will reflect the findings of the available research, complemented by the recommendations of relevant international standards and guidelines (such as ISA 84, ISA 99, ISO 26262, ISO/SAE 21434), and practices used by industry. TOMSAC will develop a novel method which is inspired by the principles of Quality Function Deployment (QFD) – a method created in Japan in 1960s and widely used in industry for improving product quality and customer satisfaction.

ENCODE: Ensuring Cybersecure Deployments of Driverless Teleoperated Vehicles - ENCODE will further the integration of enabling Connected and Automated Vehicle (CAV) technology, namely teleoperation - remotely operating a vehicle, and assessing its safe and secure integration with an automated driving system.

ENCODE believes that "multi-driver" vehicles (manually driven, automated software-driven or teleoperated) will accelerate CAV technology to commercially viable deployment, enabling the removal of the safety driver within certain ODDs. This supports the DfT's mission to benefit the UK supply chain, and support government assurance processes in this area.

This six-month project, concluding in March 2022, will research and assess the security and safety considerations for implementing a remote driving system into a multi-driver vehicle removing barriers to CAV deployment.

SAVOR: Safely Advancing Vehicle Automation on Roads - SAVOR explores the key requirements to apply remote monitoring and teleoperation (RMTO) to automated vehicles (AVs) as an essential safety measure in achieving L4 operation on public roads.

These requirements apply both to the vehicle automation stack, the communications and the remote monitoring and control interface. The project includes essential human factors and technology assessments to provide recommendations that may be used by DfT, CCAV, and other industry stakeholders when deploying their solutions.

 Queen’s Award for Enterprise Logo
University of the year shortlisted
QS Five Star Rating 2023