Copertina

Cybersecurity-Focused Anomaly Detection in Connected Autonomous Vehicles Using Machine Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Lebaku, Prathyush Kumar Reddy, Gao, Lu, Zhang, Yunpeng, Li, Zhixia, Liu, Yongxin, Arafin, Tanvir
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Deep Learning for Pavement Condition Evaluation Using Satellite Imagery
di: Lebaku, Prathyush Kumar Reddy, et al.
Pubblicazione: (2025)

Systematic Review: Anomaly Detection in Connected and Autonomous Vehicles
di: Solaas, J. R. V., et al.
Pubblicazione: (2024)

Enhancing Trust Management System for Connected Autonomous Vehicles Using Machine Learning Methods: A Survey
di: Xu, Qian, et al.
Pubblicazione: (2025)

Assessing the Influence of Pavement Performance on Road Safety Through Crash Frequency and Severity Analysis
di: Lebaku, Prathyush Kumar Reddy, et al.
Pubblicazione: (2025)

Semi-supervised Anomaly Detection via Adaptive Reinforcement Learning-Enabled Method with Causal Inference for Sensor Signals
di: Chen, Xiangwei, et al.
Pubblicazione: (2024)

Quantum Autoencoders for Anomaly Detection in Cybersecurity
di: Senthil, Rohan, et al.
Pubblicazione: (2025)

Anomaly Detection in Electric Vehicle Charging Stations Using Federated Learning
di: C, Bishal K, et al.
Pubblicazione: (2025)

Intrusion Detection in Internet of Vehicles Using Machine Learning
di: Le, Hop, et al.
Pubblicazione: (2025)

Enhancing Cybersecurity in IoT Networks: A Deep Learning Approach to Anomaly Detection
di: Pang, Yining, et al.
Pubblicazione: (2024)

Assessing Cybersecurity Risks and Traffic Impact in Connected Autonomous Vehicles
di: Silwal, Saurav, et al.
Pubblicazione: (2026)

Cross-cultural Deployment of Autonomous Vehicles Using Data-light Inverse Reinforcement Learning
di: Lu, Hongliang, et al.
Pubblicazione: (2025)

A Survey on Deep Multi-Task Learning in Connected Autonomous Vehicles
di: Wang, Jiayuan, et al.
Pubblicazione: (2025)

GRAD: Real-Time Gated Recurrent Anomaly Detection in Autonomous Vehicle Sensors Using Reinforced EMA and Multi-Stage Sliding Window Techniques
di: Naeimi, Mohammad Hossein Jafari, et al.
Pubblicazione: (2025)

Multilingual Financial Fraud Detection Using Machine Learning and Transformer Models: A Bangla-English Study
di: Uddin, Mohammad Shihab, et al.
Pubblicazione: (2026)

A Survey of Heterogeneous Graph Neural Networks for Cybersecurity Anomaly Detection
di: Jiang, Laura, et al.
Pubblicazione: (2025)

URB -- Urban Routing Benchmark for RL-equipped Connected Autonomous Vehicles
di: Akman, Ahmet Onur, et al.
Pubblicazione: (2025)

Forecasting Antimicrobial Resistance Trends Using Machine Learning on WHO GLASS Surveillance Data: A Retrieval-Augmented Generation Approach for Policy Decision Support
di: Turja, Md Tanvir Hasan
Pubblicazione: (2026)

Federated Learning for Drowsiness Detection in Connected Vehicles
di: Lindskog, William, et al.
Pubblicazione: (2024)

Context-Aware Hybrid Routing in Bluetooth Mesh Networks Using Multi-Model Machine Learning and AODV Fallback
di: Islam, Md Sajid, et al.
Pubblicazione: (2025)

Real-Time Machine Learning for Embedded Anomaly Detection
di: Benmachiche, Abdelmadjid, et al.
Pubblicazione: (2025)

AnoGAN for Tabular Data: A Novel Approach to Anomaly Detection
di: Singh, Aditya, et al.
Pubblicazione: (2024)

Pruning-Based TinyML Optimization of Machine Learning Models for Anomaly Detection in Electric Vehicle Charging Infrastructure
di: Dehrouyeh, Fatemeh, et al.
Pubblicazione: (2025)

Optimal Actuator Attacks on Autonomous Vehicles Using Reinforcement Learning
di: Wang, Pengyu, et al.
Pubblicazione: (2025)

Supervised Machine Learning in Cybersecurity
di: Loza, Boris
Pubblicazione: (2025)

Bi-directional Curriculum Learning for Graph Anomaly Detection: Dual Focus on Homogeneity and Heterogeneity
di: Hao, Yitong, et al.
Pubblicazione: (2025)

Hyperedge Anomaly Detection with Hypergraph Neural Network
di: Alam, Md. Tanvir, et al.
Pubblicazione: (2024)

Unsupervised Anomaly Detection in Wearable Foot Sensor Data: A Baseline Feasibility Study Towards Diabetic Foot Ulcer Prevention
di: Turja, Md Tanvir Hasan
Pubblicazione: (2026)

Machine Learning-based Layer-wise Detection of Overheating Anomaly in LPBF using Photodiode Data
di: Hasan, Nazmul, et al.
Pubblicazione: (2024)

Multi-agent Reinforcement Learning for Cooperative Lane Changing of Connected and Autonomous Vehicles in Mixed Traffic
di: Zhou, Wei, et al.
Pubblicazione: (2021)

Quantum Machine Learning in Log-based Anomaly Detection: Challenges and Opportunities
di: Qi, Jiaxing, et al.
Pubblicazione: (2024)

Building Machine Learning Challenges for Anomaly Detection in Science
di: Campolongo, Elizabeth G., et al.
Pubblicazione: (2025)

Cybersecurity Assessment of Smart Grid Exposure Using a Machine Learning Based Approach
di: Jeje, Mofe O.
Pubblicazione: (2025)

Batch Distillation Data for Developing Machine Learning Anomaly Detection Methods
di: Arweiler, Justus, et al.
Pubblicazione: (2025)

Unsupervised Machine Learning for Detecting Structural Anomalies in European Regional Statistics
di: Oancea, Bogdan
Pubblicazione: (2026)

CICADA: Cross-Domain Interpretable Coding for Anomaly Detection and Adaptation in Multivariate Time Series
di: Lan, Tian, et al.
Pubblicazione: (2025)

Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models
di: Gao, Lu, et al.
Pubblicazione: (2025)

Explainable Anomaly Detection for Electric Vehicles Charging Stations
di: Cederle, Matteo, et al.
Pubblicazione: (2025)

Multi-Agent Probabilistic Ensembles with Trajectory Sampling for Connected Autonomous Vehicles
di: Wen, Ruoqi, et al.
Pubblicazione: (2023)

Autonomous Navigation of Unmanned Vehicle Through Deep Reinforcement Learning
di: Xu, Letian, et al.
Pubblicazione: (2024)

Tensor Networks for Explainable Machine Learning in Cybersecurity
di: Aizpurua, Borja, et al.
Pubblicazione: (2023)