National Institute of Standards and Technology (NIST)’s Post

I am thrilled to announce the publication of our latest paper, "A Survey on Cyber-Physical Security of Autonomous Vehicles Using a Context Awareness Method," now available in #IEEEAccess! In the area of autonomous vehicles, cyber-physical security remains a significant challenge. This is largely due to the dependency on machine learning-processed camera imagery, which is susceptible to anomalies, affecting recognition accuracy and raising security issues. The unpredictability in vehicular environments, especially with unforeseen objects and anomalies, poses a tough challenge for current machine learning models. Our survey paper explores the innovative concept of active inference, a technique inspired by human cognition, to enhance the adaptability of these models. We aim to integrate this approach into autonomous vehicle systems, addressing the critical security gaps identified in our research. Our findings reveal the effectiveness of these frameworks in managing unexpected vehicular anomalies. A heartfelt thank you to my advisors, Dr. Junho H. and Dr. Jaerock Kwon, for their invaluable guidance. Also, special thanks to John Moore for his insightful contributions to this work. You can access the full publication through the link provided. https://lnkd.in/gYyPydTY #AutonomousVehicles #Security #Cyberphysical #MachineLearning #ActiveInference #ContextAwareness #AbnormalScenarios #Research

📃Scientific paper: Using Knowledge Awareness to improve Safety of Autonomous Driving Abstract: We present a method, which incorporates knowledge awareness into the symbolic computation of discrete controllers for reactive cyber physical systems, to improve decision making about the unknown operating environment under uncertain/incomplete inputs. Assuming an abstract model of the system and the environment, we translate the knowledge awareness of the operating context into linear temporal logic formulas and incorporate them into the system specifications to synthesize a controller. The knowledge base is built upon an ontology model of the environment objects and behavioural rules, which includes also symbolic models of partial input features. The resulting symbolic controller support smoother, early reactions, which improves the security of the system over existing approaches based on incremental symbolic perception. A motion planning case study for an autonomous vehicle has been implemented to validate the approach, and presented results show significant improvements with respect to safety of state-of-the-art symbolic controllers for reactive systems. Continued on ES/IODE ➡️ https://etcse.fr/vkO ------- If you find this interesting, feel free to follow, comment and share. We need your help to enhance our visibility, so that our platform continues to serve you.

Greetings Connections! 👋🏻 I just finished my presentation for Seminar on Special Topics in Emerging Areas. 🎬 🚗 Revolutionizing the Road: Edge Computing in Autonomous Vehicles 🚀 Excited to share insights from my recent presentation on Edge Computing for Autonomous Vehicles! 🌐🤖 🔍 Unveiling the Power of Edge Computing: a distributed computing paradigm that brings computation and data storage closer to the location where it is needed, rather than relying on a centralized data-processing warehouse. The processing is done on or near the source of the data, reducing latency and increasing efficiency. 🚀 🔧 Tesla's Trailblazing Tech: In the automotive industry, companies like Tesla are at the forefront, integrating edge computing to enhance real-time decision-making in their autonomous vehicles. Tesla cars can accelerate, brake and adjust their driving speeds to adapt to the obstacles on the road. 🚗🔒 🛣️ Can Detect Criminal Behaviour: Dubai Police Unveils Driverless, Al-Powered Patrol Cars With its smart technology and artificial intelligence, the vehicle can detect criminal behaviour, recognize faces, and read car license plates. 🌐🔐 🧠 5G for Edge AI: The advent of 5G technology has ushered in a new era of connectivity, boasting speeds that are ten times faster than its predecessor, 4G. This enhanced speed not only accelerates data transmission but also opens up opportunities for transformative technologies like mobile edge computing. By bringing computing capacities closer to end-users, mobile edge computing effectively reduces dormancy and enhances the overall user experience. 🤖💡 🔮 Cybersecurity in Action: As we shift to edge computing, cybersecurity becomes a focal point. To include robust cybersecurity measures to safeguard autonomous vehicles from potential threats. 🚀🔮 I would like to extend my special thanks to Dr. Mohd Abuzar Sayeed, our respected Prof. (Dr. ) Abhay Bansal and School of CSET Bennett University, India for providing me with this informative and educational experience. 👏🏻 📺 I urge you to watch my engaging video on this topic: https://lnkd.in/djpMCD9w 🎡 The wheels are set in motion, and the horizon is limitless – welcome to the era where edge computing propels autonomy into the fast lane of progress. 🏎 🤝 Let's connect and delve deeper into the fascinating intersection of technology and transportation! 🌐🚗  #EdgeComputing, #AutonomousVehicles, #AIinTransportation, #InnovationInMobility, #TeslaTech, #EdgeAI, #SmartMobility

#NewResearch I am glad to announce the publication of our (myself, Peter Lee & Prof Alison Wakefield PhD CSyP FSyI ) research on the threats, risks, and opportunities of autonomous vehicles. We navigate the technical, ethical, and legal challenges posed by autonomous vehicles on land, sea, and air domains. We show how disparate the laws on AVs are across domains and call for a more harmonised regulatory regime, with a great emphasis on addressing the challenges posed by AVs for security. The research was funded by the ASIS International and can benefit security practitioners and scholars in the areas of autonomous cars, autonomous maritime vehicles, uncrewed air vehicles, autonomous weapons systems, AI regulations and others. Find the report here https://lnkd.in/eqH8RPg4.. For those who would like a free copy, get in touch

🚗 Autonomous vehicles heavily rely on artificial intelligence to perceive their surroundings, making them vulnerable to #cyberattacks. Just imagine, a manipulated stop sign 🛑 fooling an object detector in a self-driving car. But there are ways to evaluate how well #AI performs when faced with such adversarial attacks. A team from Fraunhofer AISEC, Fraunhofer Singapore and Continental Automotive has developed CARLA-A3 (CARLA-based Adversarial Attack Assessment). The tool allows for the assessment of object detectors' robustness against #AdversarialAttacks in CARLA simulator, taking into account various attack methods 💥 and environmental conditions ❄️ where benign and malicious traffic signs might be encountered. ⛔⚠️ Our researchers are all set to present their framework at the #VehicleSec 2024 (Symposium on Vehicle Security and Privacy) in San Diego on February 26. 📺 https://lnkd.in/epZtnDGe #AIsecurity #autonomousdriving #VehicleSec24 Ray Zirui Lan; Wei Herng C., Chingyu Kao, Dr. Mathias Dehm, Philip Sperl, Konstantin Böttinger, Michael Kasper

Autonomous electric vehicles (AEVs) are revolutionizing transportation by merging the benefits of AI-driven autonomy with the eco-friendly advantages of electrification. Imagine a world where your car drives you, optimizing routes, reducing accidents, and eliminating emissions. Companies like Tesla and Waymo are pioneering this technology, promising a future where transportation is not only safer but also more efficient and sustainable. 🚗⚡️ However, the journey to widespread adoption is complex. Regulatory frameworks are still evolving, with each region taking different approaches to ensure safety and accountability. Moreover, the cybersecurity of these highly connected vehicles is a critical concern, as a breach could have catastrophic consequences. 🔐🌐 The ethical programming of AEVs, especially in unavoidable accident scenarios, also poses significant challenges. Despite these hurdles, the potential benefits of AEVs are immense, making this an exciting field to watch. 🚘🛤️ Dive deeper into this transformative technology and discover how it will shape our future. 🌍✨ #AutonomousVehicles #ElectricVehicles #FutureOfTransportation #SustainableMobility #AI #Innovation #SmartCities #CleanEnergy #CyberSecurity #TechRevolution

ARTICLE: COMPUTER VISION The internet is full of images! This is the selfie age, where taking an image and sharing it has never been easier. In fact, millions of images are uploaded and viewed every day on the internet. To make the most use of this huge amount of images online, it’s important that computers can see and understand images. And while humans can do this easily without a thought, it’s not so easy for computers! This is where Computer Vision comes in. Computer Vision uses Artificial Intelligence to extract information from images. This information can be object detection in the image, identification of image content to group various images together, etc. An application of computer vision is navigation for autonomous vehicles by analyzing images of surroundings such as AutoNav used in the Spirit and Opportunity rovers which landed on Mars.

🚗 Autonomous vehicle (AV) technology aims to reduce road accidents by utilizing robust perception systems for real-time object detection and classification. Factors such as scene complexity, sensor capability, and AI algorithm performance affect the system's robustness and vulnerability to cyber-physical attacks. The mathematical modeling for system-level risk evaluation of AV perception systems, adapted from ISO/SAE 21434 should be considered, incorporating real traffic crash data and AI/ML detection algorithms. Additionally, mask autoencoder (MAE)-based image reconstruction methods can be proposed to enhance traffic sign classification accuracy, demonstrating improved performance even with input abnormalities. If you are interested in these subjects, I invite you to explore our most recent conference papers available on IEEE Xplore. "Object-focused Risk Evaluation of AI-driven Perception Systems in Autonomous Vehicles" Link: https://lnkd.in/gPgmGfFv "An Enhanced Classification Technique for Mitigating Unexpected Noise Intrusions in Autonomous Vehicles" Link: https://lnkd.in/gFYRaVaa #AV #Security #Perception #Robustness #AI #ML #Classification #CNN

We sat down with Dr. B Brian park of UVA in this month's SMARTER Transportation Talk to discuss the challenges and implications of Connected and Autonomous Vehicle (CAV) deployment in the US. What does this new suite of technologies mean for cybersecurity, the environment, auto manufacturers, and pedestrians? Watch now and and learn how CAVs are poised to change our roads!