Recent Advances in Machine-Learning Driven Intrusion Detection in Transportation: Survey

[1]  Sidi-Mohammed Senouci,et al.  An accurate and efficient collaborative intrusion detection framework to secure vehicular networks , 2015, Comput. Electr. Eng..

[2]  Walid Saad,et al.  Machine Learning for Wireless Connectivity and Security of Cellular-Connected UAVs , 2018, IEEE Wireless Communications.

[3]  Sana Ullah,et al.  An intelligent clustering scheme for distributed intrusion detection in vehicular cloud computing , 2015, Cluster Computing.

[4]  Liang Xiao,et al.  UAV-Aided Cellular Communications with Deep Reinforcement Learning Against Jamming , 2018, IEEE Wireless Communications.

[5]  Maode Ma,et al.  A filter model for intrusion detection system in Vehicle Ad Hoc Networks: A hidden Markov methodology , 2019, Knowl. Based Syst..

[6]  F. Richard Yu,et al.  A novel Intrusion Detection System for Vehicular Ad Hoc Networks (VANETs) based on differences of traffic flow and position , 2019, Appl. Soft Comput..

[7]  Ashish Srivastava,et al.  Future FANET with application and enabling techniques: Anatomization and sustainability issues , 2021, Comput. Sci. Rev..

[8]  George Loukas,et al.  A taxonomy and survey of cyber-physical intrusion detection approaches for vehicles , 2019, Ad Hoc Networks.

[9]  Abdulhadi Shoufan,et al.  Drone Pilot Identification by Classifying Radio-Control Signals , 2018, IEEE Transactions on Information Forensics and Security.

[10]  Mouzhi Ge,et al.  Big Data for Internet of Things: A Survey , 2018, Future Gener. Comput. Syst..

[11]  Khattab M. Ali Alheeti,et al.  Using discriminant analysis to detect intrusions in external communication for self-driving vehicles , 2017, Digit. Commun. Networks.

[12]  Arman Sargolzaei,et al.  Detection of Fault Data Injection Attack on UAV Using Adaptive Neural Network , 2016 .

[13]  Hongwei Lu,et al.  Distributed collaborative intrusion detection system for vehicular Ad Hoc networks based on invariant , 2020, Comput. Networks.

[14]  Rojeena Bajracharya,et al.  Challenges of Future VANET and Cloud-Based Approaches , 2018, Wirel. Commun. Mob. Comput..

[15]  Jianyu Zhao,et al.  Abnormal Behavior Detection Scheme of UAV Using Recurrent Neural Networks , 2019, IEEE Access.

[16]  Khattab M. Ali Alheeti,et al.  Intelligent Intrusion Detection of Grey Hole and Rushing Attacks in Self-Driving Vehicular Networks , 2016, Comput..

[17]  Trung Q. Duong,et al.  Detection of Eavesdropping Attack in UAV-Aided Wireless Systems: Unsupervised Learning With One-Class SVM and K-Means Clustering , 2020, IEEE Wireless Communications Letters.

[18]  Gang Su,et al.  Hierarchical Growing Neural Gas Network (HGNG)-Based Semicooperative Feature Classifier for IDS in Vehicular Ad Hoc Network (VANET) , 2018, J. Sens. Actuator Networks.

[19]  Liang Xiao,et al.  Reinforcement Learning-Based Control for Unmanned Aerial Vehicles , 2018, Journal of Communications and Information Networks.

[20]  Nirwan Ansari,et al.  A Hierarchical Detection and Response System to Enhance Security Against Lethal Cyber-Attacks in UAV Networks , 2018, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[21]  Chao Li,et al.  Protecting Secure Communication Under UAV Smart Attack With Imperfect Channel Estimation , 2018, IEEE Access.

[22]  Quanyan Zhu,et al.  Distributed Privacy-Preserving Collaborative Intrusion Detection Systems for VANETs , 2018, IEEE Transactions on Signal and Information Processing over Networks.

[23]  Farhan Aadil,et al.  IMOC: Optimization Technique for Drone-Assisted VANET (DAV) Based on Moth Flame Optimization , 2020, Wirel. Commun. Mob. Comput..

[24]  Sushanta Karmakar,et al.  A game theory based multi layered intrusion detection framework for VANET , 2018, Future Gener. Comput. Syst..

[25]  Anis Laouiti,et al.  VANet security challenges and solutions: A survey , 2017, Veh. Commun..

[26]  Mary L. Cummings,et al.  Operator Strategy Model Development in UAV Hacking Detection , 2019, IEEE Transactions on Human-Machine Systems.

[27]  Wenchao Xu,et al.  Big Data Driven Vehicular Networks , 2018, IEEE Network.

[28]  N Vanitha,et al.  Traffic Analysis of UAV Networks Using Enhanced Deep Feed Forward Neural Networks (EDFFNN) , 2020 .

[29]  Zhen Zuo,et al.  Intrusion Detection of UAVs Based on the Deep Belief Network Optimized by PSO , 2019, Sensors.

[30]  Sherali Zeadally,et al.  Data analytics for Cooperative Intelligent Transport Systems , 2019, Veh. Commun..

[31]  Xiangjie Kong,et al.  Spatio-Temporal Network Traffic Estimation and Anomaly Detection Based on Convolutional Neural Network in Vehicular Ad-Hoc Networks , 2018, IEEE Access.

[32]  Weihua Zhuang,et al.  User-Centric View of Unmanned Aerial Vehicle Transmission Against Smart Attacks , 2018, IEEE Transactions on Vehicular Technology.

[33]  Kamalrulnizam Abu Bakar,et al.  Fog Based Intelligent Transportation Big Data Analytics in The Internet of Vehicles Environment: Motivations, Architecture, Challenges, and Critical Issues , 2018, IEEE Access.

[34]  Weihua Zhuang,et al.  UAV Relay in VANETs Against Smart Jamming With Reinforcement Learning , 2018, IEEE Transactions on Vehicular Technology.

[35]  Ajay Kaul,et al.  Hybrid fuzzy multi-criteria decision making based multi cluster head dolphin swarm optimized IDS for VANET , 2018, Veh. Commun..

[36]  Zhiwei Li,et al.  A Dyna-Q-Based Solution for UAV Networks Against Smart Jamming Attacks , 2019, Symmetry.

[37]  Xiaojun Jing,et al.  Anti-Intelligent UAV Jamming Strategy via Deep Q-Networks , 2019, ICC 2019 - 2019 IEEE International Conference on Communications (ICC).

[38]  Gongjun Yan,et al.  Data Mining Intrusion Detection in Vehicular Ad Hoc Network , 2014, IEICE Trans. Inf. Syst..

[39]  Jamal Bentahar,et al.  CEAP: SVM-based intelligent detection model for clustered vehicular ad hoc networks , 2016, Expert Syst. Appl..

[40]  David A. Schmidt,et al.  Spline‐based intrusion detection for VANET utilizing knot flow classification , 2020, Internet Technol. Lett..

[41]  Ing-Ray Chen,et al.  Adaptive Intrusion Detection of Malicious Unmanned Air Vehicles Using Behavior Rule Specifications , 2014, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[42]  Nan Guan,et al.  Efficient drone hijacking detection using two-step GA-XGBoost , 2020, J. Syst. Archit..

[43]  Helge Janicke,et al.  A novel Intrusion Detection System against spoofing attacks in connected Electric Vehicles , 2020, Array.

[44]  Chirag Gohel,et al.  Securing VANET by Preventing Attacker Node Using Watchdog and Bayesian Network Theory , 2016 .

[45]  Mosa Ali Abu-Rgheff,et al.  An Efficient and Lightweight Intrusion Detection Mechanism for Service-Oriented Vehicular Networks , 2014, IEEE Internet of Things Journal.

[46]  Syed Asad Hussain,et al.  A game theory based trust model for Vehicular Ad hoc Networks (VANETs) , 2017, Comput. Networks.

[47]  Ahmet Rizaner,et al.  Trust aware support vector machine intrusion detection and prevention system in vehicular ad hoc networks , 2018, Comput. Secur..