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CARAMEL: results on a secure architecture for connected and autonomous vehicles detecting GPS spoofing attacks

Christian Vitale, Nikos Piperigkos, Christos Laoudias, Georgios Ellinas, Jordi Casademont, Josep Escrig, Andreas Kloukiniotis, Aris S. Lalos, Konstantinos Moustakas, Rodrigo Diaz Rodriguez, Daniel Baños, Gemma Roqueta Crusats (+3 others)
2021 EURASIP Journal on Wireless Communications and Networking  
for connected and autonomous driving.  ...  among others, algorithms for detecting attacks are implemented; (3) an intelligent On-Board Unit with anti-hacking features inside the vehicle; (4) a Public Key Infrastructure that validates in real-time  ...  attacks GNSS interface tamper attacks Eavesdropping data signals Clock fault injection Temperature fault injection Voltage fault injection Environmental sensors • • • Opening  ... 
doi:10.1186/s13638-021-01971-x fatcat:es7gzcufzvhozhxuh3q6h5j7sq

A Systematic Literature Review about the impact of Artificial Intelligence on Autonomous Vehicle Safety [article]

A. M. Nascimento, L. F. Vismari, C. B. S. T. Molina, P.S. Cugnasca, J.B. Camargo Jr., J.R. de Almeida Jr., R. Inam, E. Fersman, M. V. Marquezini, A. Y. Hata
2019 arXiv   pre-print
As a main result, we have reinforced our preliminary observation about the necessity of considering a serious safety agenda for the future studies on AI-based AV systems.  ...  Autonomous Vehicles (AV) are expected to bring considerable benefits to society, such as traffic optimization and accidents reduction.  ...  [66] proposed an approach to describe test-cases for validating autonomous vehicles using recordings of traffic situations for creating a minimal test-suit that could help in the certification process  ... 
arXiv:1904.02697v1 fatcat:jsruqsy3kvcyvdyfhzo4ojfaqi

Intrusion Detection Systems for Intra-vehicle Networks: A Review

Omar Y. Al-Jarrah, Carsten Maple, Mehrdad Dianati, David Oxtoby, Alex Mouzakitis
2019 IEEE Access  
This paper provides a structured and comprehensive review of the state of the art of the intra-vehicle intrusion detection systems (IDSs) for passenger vehicles.  ...  A modern vehicle is a complex system of sensors, electronic control units, and actuators connected through different types of intra-vehicle networks to control and monitor the state of the vehicle.  ...  [5] proposed a ML-based IDS for robot vehicle.  ... 
doi:10.1109/access.2019.2894183 fatcat:w2vnreq2n5gsthqusue47zubk4

Exploring Fault Parameter Space Using Reinforcement Learning-based Fault Injection

Mehrdad Moradi, Bentley James Oakes, Mustafa Saraoglu, Andrey Morozov, Klaus Janschek, Joachim Denil
2020 Figshare  
Fault Injection (FI) is a proven technique for safety analysis and is recommended by the automotive safety standard ISO 26262.  ...  In this paper, we apply our technique on an Adaptive Cruise Controller with sensor fusion and compare the proposed method with Monte Carlo-based fault injection.  ...  The authors thank Moharram Challenger for his useful suggestions.  ... 
doi:10.6084/m9.figshare.12479888.v1 fatcat:nitj5bmsmngydml343lqhbawjq

Cyberattacks and Countermeasures For In-Vehicle Networks [article]

Emad Aliwa, Omer Rana, Charith Perera, Peter Burnap
2020 arXiv   pre-print
With the rise of connected cars, more entry points and interfaces have been introduced on board vehicles, thereby also leading to a wider potential attack surface.  ...  We conclude with potential mitigation strategies and research challenges for the future.  ...  data from autonomous vehicle.  ... 
arXiv:2004.10781v1 fatcat:bbcyqiwskfbjtkp2a2wpvkqbny

STC-IDS: Spatial-Temporal Correlation Feature Analyzing based Intrusion Detection System for Intelligent Connected Vehicles [article]

Mu Han, Pengzhou Cheng, Fengwei Zhang
2022 arXiv   pre-print
To address these limitations, we present a novel model for automotive intrusion detection by spatial-temporal correlation features of in-vehicle communication traffic (STC-IDS).  ...  Extensive empirical studies based on a real-world vehicle attack dataset demonstrate that STC-IDS has outperformed baseline methods and cables fewer false-positive rates while maintaining efficiency.  ...  It is worth noting that the time-cost detection of proposed methods is based on in-vehicle edge computing and autonomous driving platform from our research group.  ... 
arXiv:2204.10990v1 fatcat:zrdma3ghjbcyvhnrctzcldko2m

Software Verification and Validation of Safe Autonomous Cars: A Systematic Literature Review

Nijat Rajabli, Francesco Flammini, Roberto Nardone, Valeria Vittorini
2020 IEEE Access  
The second part investigates more specific approaches, including simulation environments and mutation testing, corner cases and adversarial examples, fault injection, software safety cages, techniques  ...  By appropriate criteria, a subset of primary studies has been selected for more in-depth analysis.  ...  The framework called DriveFI is able to modify the state of software and hardware components to demonstrate the effects of faults in a simulation environment, and use ML-based Bayesian FI to find faults  ... 
doi:10.1109/access.2020.3048047 fatcat:7mgx34zscvfavenyznqmbul7cm

A Comprehensive Review on Blockchains for Internet of Vehicles: Challenges and Directions [article]

Brian Hildebrand, Mohamed Baza, Tara Salman, Fathi Amsaad, Abdul Razaqu, Abdullah Alourani
2022 arXiv   pre-print
Internet of Vehicles (IoVs) consist of smart vehicles, Autonomous Vehicles (AVs) as well as roadside units (RSUs) that communicate wirelessly to provide enhanced transportation services such as improved  ...  In this work, we present the state-of-the-art of Blockchain-enabled IoVs (BIoV) with a particular focus on their applications such as crowdsourcing-based applications, energy trading, traffic congestion  ...  Blockchain-Based FL for Autonomous Vehicles In [152] , authors propose a Blockchain-based FL system for autonomous vehicles (AVs). The framework is composed of miners and AVs.  ... 
arXiv:2203.10708v1 fatcat:sozptzz5l5a27oh5rukujcg32a

Blockchain and Autonomous Vehicles: Recent Advances and Future Directions

Saurabh Jain, Neelu Jyothi Ahuja, P. Srikanth, Kishor V. Bhadane, Bharathram Nagaiah, Adarsh Kumar, Charalambos Konstantinou
2021 IEEE Access  
Alexey Shumsky [80] presented a method based on AQLPR for fault detection in sensors of AUVs.  ...  This work can be extended to design blockchain and smart contract-based use-cases for autonomous driving, vehicles and systems.  ... 
doi:10.1109/access.2021.3113649 fatcat:js3fseq3d5g7zbjkaop2tl3t7m

Hierarchical Fault Diagnosis and Health Monitoring in Satellites Formation Flight

Amitabh Barua, Khashayar Khorasani
2011 IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)  
In this paper, we develop a systematic and transparent fault diagnosis methodology within a hierarchical fault diagnosis framework for a satellites formation flight.  ...  We have developed a methodology for specifying the network parameters that utilizes both node fault diagnosis performance data and domain experts' beliefs.  ...  The work in [6] does not propose any Bayesian network-based model for hierarchical fault diagnosis.  ... 
doi:10.1109/tsmcc.2010.2049994 fatcat:a2zm3x73tjbftdvf66naoihq3q

A Survey on Machine-Learning Based Security Design for Cyber-Physical Systems

Sangjun Kim, Kyung-Joon Park
2021 Applied Sciences  
In this survey, we provide an extensive review of the threats and ML-based security designs for CPSs.  ...  Furthermore, we discuss future research directions for ML-based cyber-physical security research in the context of real-time constraints, resiliency, and dataset generation to learn about the possible  ...  emergency stop for an autonomous vehicle [81] .  ... 
doi:10.3390/app11125458 fatcat:c6kjiidpv5dt7iiyxxhtoi5ura

An Analysis of ISO 26262: Using Machine Learning Safely in Automotive Software [article]

Rick Salay, Rodrigo Queiroz, Krzysztof Czarnecki
2017 arXiv   pre-print
Machine learning (ML) plays an ever-increasing role in advanced automotive functionality for driver assistance and autonomous operation; however, its adequacy from the perspective of safety certification  ...  We then provide a set of recommendations on how to adapt the standard to accommodate ML.  ...  ACKNOWLEDGMENT The authors would like to thank Atri Sarkar, Michael Smart, Michal Antkiewicz, Marsha Chechik, Sahar Kokaly and Ramy Shahin for their insightful comments.  ... 
arXiv:1709.02435v1 fatcat:ci747pyhbbb25b6o25rl3v4asi

Automotive Parts Assessment: Applying Real-time Instance-Segmentation Models to Identify Vehicle Parts [article]

Syed Adnan Yusuf, Abdulmalik Ali Aldawsari, Riad Souissi
2022 arXiv   pre-print
The Yolact-based part localization and segmentation method performed well when compared to other real-time instance mechanisms with a mAP of 66.5.  ...  the task even more challenging for a machine-learning model to perform well.  ...  combined classification and regression outputs for parts localization, damage localization and segmentation as well as parts and labour cost regression.  ... 
arXiv:2202.00884v1 fatcat:hf6txbmcv5dadc4zuoovmbxtsa

A Deep Learning Perspective on Connected Automated Vehicle (CAV) Cybersecurity and Threat Intelligence [article]

Manoj Basnet, Mohd. Hasan Ali
2021 arXiv   pre-print
threat intelligence for attack detection.  ...  The automation and connectivity of CAV inherit most of the cyber-physical vulnerabilities of incumbent technologies such as evolving network architectures, wireless communications, and AI-based automation  ...  [30] proposed the dynamic federated proximal (DFP) based FL framework for designing the autonomous controller of the CAV.  ... 
arXiv:2109.10763v1 fatcat:tigj5x6pnrbmrbf3my46ynr4we

Machine Learning Testing: Survey, Landscapes and Horizons [article]

Jie M. Zhang University College London, Nanyang Technological University)
2019 arXiv   pre-print
This paper provides a comprehensive survey of Machine Learning Testing (ML testing) research.  ...  ., autonomous driving, machine translation).  ...  This also provided one final stage in the systematic trawling of the literature for relevant work.  ... 
arXiv:1906.10742v2 fatcat:p5c54cy4pjc5flzm7shybk3qxe
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