A Comprehensive Analysis of Cybersecurity Challenges in Self-Adaptive Avionics: A Plug&Fly Avionics Platform Case Study
SHORT
This program is tentative and subject to change.
Increasing complexity and availability demands of traditional software systems have derived the need for self-adaptive systems. Self-adaptive systems automatically adjust their behavior at runtime to meet objectives. However, these systems accompany additional challenges specially in terms of security. These challenges include interaction with non-trusted entities, widening of attack surface due to multichannel communication, risk of unauthorized and malicious access to operating environment, and potential exploitation of adaptive mechanisms by attackers. Despite the growing adoption of these systems in avionics, comprehensive study on their cybersecurity assessment is missing. To fill the gap, this study discusses various security vulnerabilities introduced with self-adaptivity in avionics. The aim of the study is to use the Plug&Fly Avionics Platform (PAFA) as a case study, and analyze the impact of self-adaptivity in exposing the system to a wide range of cyber threats such as, faulty decision making, compromised reconfigurations, and so on. Besides detailed analysis of security vulnerabilities introduced with self-adaptivity, the paper also proposes some novel mitigation strategies and demonstrate their effectiveness in achieving a cybersecure adaptive system in the context of PAFA. These findings aim to provide solid basis in future research and development towards securing self-adaptive systems, ensuring both their reliability and safety in complex operational environments.
This program is tentative and subject to change.
Tue 29 AprDisplayed time zone: Eastern Time (US & Canada) change
11:00 - 12:30 | |||
11:00 25mTalk | Self-Adaptive Dual-Layer DDoS Mitigation using Autoencoder and Reinforcement LearningFULL Research Track Qi Duan Carnegie Mellon University, Ehab Al-Shaer Carnegie Mellon University, USA, David Garlan Carnegie Mellon University | ||
11:25 25mTalk | Analysis of Autonomous Driving Software to Low-Level Sensor Cyber AttacksFULL Research Track Andrew Roberts Tallinn University of Technology, Mohsen Malayjerdi Tallinn University of Technology, Mauro Bellone FinEst Smart City Centre, Raivo Sell Tallinn University of Technology, Olaf Maennel University of Adelaide, Mohammad Hamad Technical University of Munich, Sebastian Steinhorst Technical University of Munich | ||
11:50 15mTalk | A Comprehensive Analysis of Cybersecurity Challenges in Self-Adaptive Avionics: A Plug&Fly Avionics Platform Case StudySHORT Research Track Aisha Zahid Junejo Universitat Stuttgart, Mario Werthwein Universitat Stuttgart, Bjoern Annighoefer University of Stuttgart | ||
12:05 15mTalk | Towards Using Inductive Learning to Adapt Security Controls in Smart HomesSHORT Research Track Kushal Ramkumar Lero@University College Dublin, Wanling Cai Lero@Trinity College Dublin, John McCarthy Lero@University College Cork, Gavin Doherty Lero@Trinity College Dublin, Bashar Nuseibeh The Open University, UK; Lero, University of Limerick, Ireland, Liliana Pasquale University College Dublin & Lero File Attached | ||
12:20 10mOther | Discussion Session 6 Research Track |