[HTML][HTML] Autonomous driving architectures: insights of machine learning and deep learning algorithms
MR Bachute, JM Subhedar - Machine Learning with Applications, 2021 - Elsevier
Abstract Research in Autonomous Driving is taking momentum due to the inherent
advantages of autonomous driving systems. The main advantage being the disassociation …
advantages of autonomous driving systems. The main advantage being the disassociation …
Deep reinforcement learning for cyber security
The scale of Internet-connected systems has increased considerably, and these systems are
being exposed to cyberattacks more than ever. The complexity and dynamics of …
being exposed to cyberattacks more than ever. The complexity and dynamics of …
In-vehicle communication cyber security: challenges and solutions
In-vehicle communication has become an integral part of today's driving environment
considering the growing add-ons of sensor-centric communication and computing devices …
considering the growing add-ons of sensor-centric communication and computing devices …
Adversarial Deep Learning approach detection and defense against DDoS attacks in SDN environments
MP Novaes, LF Carvalho, J Lloret… - Future Generation …, 2021 - Elsevier
Over the last few years, Software Defined Networking (SDN) paradigm has become an
emerging architecture to design future networks and to meet new application demands. SDN …
emerging architecture to design future networks and to meet new application demands. SDN …
Machine learning for security in vehicular networks: A comprehensive survey
A Talpur, M Gurusamy - IEEE Communications Surveys & …, 2021 - ieeexplore.ieee.org
Machine Learning (ML) has emerged as an attractive and viable technique to provide
effective solutions for a wide range of application domains. An important application domain …
effective solutions for a wide range of application domains. An important application domain …
A comprehensive survey of v2x cybersecurity mechanisms and future research paths
R Sedar, C Kalalas, F Vázquez-Gallego… - IEEE Open Journal …, 2023 - ieeexplore.ieee.org
Recent advancements in vehicle-to-everything (V2X) communication have notably improved
existing transport systems by enabling increased connectivity and driving autonomy levels …
existing transport systems by enabling increased connectivity and driving autonomy levels …
CNN‐OHGS: CNN‐oppositional‐based Henry gas solubility optimization model for autonomous vehicle control system
S Ravikumar, D Kavitha - Journal of Field Robotics, 2021 - Wiley Online Library
Numerous developments in technology toward autonomous vehicle systems (AVSs) have
been performed for so many years all over the world. As our day‐to‐day life is becoming …
been performed for so many years all over the world. As our day‐to‐day life is becoming …
Cyber-security and reinforcement learning—A brief survey
AMK Adawadkar, N Kulkarni - Engineering Applications of Artificial …, 2022 - Elsevier
This paper presents a comprehensive literature review on Reinforcement Learning (RL)
techniques used in Intrusion Detection Systems (IDS), Intrusion Prevention Systems (IPS) …
techniques used in Intrusion Detection Systems (IDS), Intrusion Prevention Systems (IPS) …
Detection and isolation of sensor attacks for autonomous vehicles: Framework, algorithms, and validation
This paper investigates the cyber-security problem for autonomous vehicles under sensor
attacks. In particular, a model-based framework is proposed which can detect sensor attacks …
attacks. In particular, a model-based framework is proposed which can detect sensor attacks …