This repository includes code for the AutoML-based IDS and adversarial attack defense case studies presented in the paper "Enabling AutoML for Zero-Touch Network Security: Use-Case Driven Analysis" published in IEEE Transactions on Network and Service Management.

This repository includes code for the paper "Towards Zero Touch Networks: Cross-Layer Automated Security Solutions for 6G Wireless Networks" published in IEEE TCOM, focusing on autonomous cybersecurity (physical-layer authentication and cross-layer intrusion detection) using AutoML techniques.

This repository includes code for the paper "Towards Autonomous Cybersecurity: An Intelligent AutoML Framework for Autonomous Intrusion Detection" accepted in AutonomousCyber, ACM CCS, 2024.

With the increasing demand for real-time processing on IoT devices, optimizing machine learning models' size, latency, and efficiency is crucial. This repository implements pruning techniques aimed at improving computational efficiency in resource-constrained environments, specifically targeting Electric Vehicle Charging Infrastructure (EVCI).

This repository serves as a platform for posting a diverse collection of Python codes for signal processing, facilitating various operations within a typical signal processing pipeline (pre-processing, processing, and application).

This repository includes the implementation to the Feature Drift Explanation method for identifying drift source in a cyber-security attack scenario.

This code includes the implementation of a Transformer-based Reinforcement Learning approach for Hyper-parameter Optimization

This code includes the implementation of WrapperRL method that progressively selects image patches of industrial data mirroring the forward feature selection process.