Cyber Attack Detection On Self-Driving Cars Using Machine Learning Techniques

Author:

Pawar Yashaswini S1,Honnavalli Prasad1,Eswaran Sivaraman2

Affiliation:

1. PES University,Dept. of Computer Science,Bangalore,India

2. Curtin University Malaysia,Dept. of Electrical and Computer Engineering,Miri,Sarawak,Malaysia

Publisher

IEEE

Reference13 articles.

1. Steering control for autonomous vehicles using pid control with gradient descent tuning and behavioral cloning;bed;2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES),0

2. Steering Angle Prediction Techniques for Autonomous Ground Vehicles: A Review

3. Hybrid intrusion detection in connected self-driving vehicles;lheeti;2016 22nd International Conference on Automation and Computing (ICAC),0

4. dacity Self Driving Car Dataset;Kaggle,2021

5. A Machine Learning Approach for Combating Cyber Attacks in Self-Driving Vehicles;erry;SoutheastCon 2021,2021

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1. A Fast and Effective Automated Wavelet-Deep learning-based Method to Detect Cyberattacks in Microgrids with EV Fast Charging Stations;2024 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE);2024-08-06

2. Early Detection of Cyber-Physical Attacks on Electric Vehicles Fast Charging Stations Using Wavelets and Deep Learning;IEEE Transactions on Industrial Cyber-Physical Systems;2024

3. Online Quantitative Analysis of Perception Uncertainty Based on High-Definition Map;Sensors;2023-12-17

4. Detecting the Anomaly Attacks in Industrial IoT using Hybrid Feature Selection Based Modified Convolutional Neural Network;2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT);2023-10-20

5. Detection of Cyber Attacks in Self-Driving Vehicles By Machine Learning;2023 International Conference Automatics and Informatics (ICAI);2023-10-05

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