IIDS: Intelligent Intrusion Detection System for Sustainable Development in Autonomous Vehicles-Reference-Cited by-同舟云学术

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IIDS: Intelligent Intrusion Detection System for Sustainable Development in Autonomous Vehicles

Published:2023-12 Issue:12 Volume:24 Page:15866-15875
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Anbalagan Sudha¹^ORCID,Raja Gunasekaran²^ORCID,Gurumoorthy Sugeerthi³,Suresh R. Deepak²^ORCID,Dev Kapal⁴^ORCID

Affiliation:

1. Centre for Smart Grid Technologies, School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India

2. Department of Computer Technology, NGN Lab, Anna University, MIT Campus, Chennai, India

3. Citicorp Services Pvt. Ltd., Chennai, India

4. Department of Institute of Intelligent Systems, University of Johannesburg, Johannesburg, South Africa

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/10339106/10144487.pdf?arnumber=10144487

Reference32 articles.

1. Early Warning Obstacle Avoidance-Enabled Path Planning for Multi-AUV-Based Maritime Transportation Systems

2. A Secure Adaptive Control for Cooperative Driving of Autonomous Connected Vehicles in the Presence of Heterogeneous Communication Delays and Cyberattacks

3. Field classification, modeling and anomaly detection in unknown CAN bus networks

4. Detection and Isolation of Sensor Attacks for Autonomous Vehicles: Framework, Algorithms, and Validation

5. 5G Evolution: A View on 5G Cellular Technology Beyond 3GPP Release 15

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1. An intelligent dynamic cyber physical system threat detection system for ensuring secured communication in 6G autonomous vehicle networks;Scientific Reports;2024-09-05

2. Private and utility enhanced intrusion detection based on attack behavior analysis with local differential privacy on IoV;Computer Networks;2024-08

3. SEDAT: A Stacked Ensemble Learning-Based Detection Model for Multiscale Network Attacks;Electronics;2024-07-26

4. Federated Deep Reinforcement Learning for Efficient Jamming Attack Mitigation in O-RAN;IEEE Transactions on Vehicular Technology;2024-07

5. HP-LSTM: Hawkes Process–LSTM-Based Detection of DDoS Attack for In-Vehicle Network;Future Internet;2024-05-23

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