arXiv Machine Learning August 4, 2026 By Li Yang

A Multi-Objective AutoML-based Efficient Intrusion Detection System for EV Charging Networks

Read the original on arXiv Machine Learning →

arXiv:2608. 02274v1 Announce Type: cross Abstract: Electric Vehicle Charging Systems (EVCSs) are increasingly connected with Internet of Things (IoT) devices, which improves charging intelligence but also expands their exposure to cyber-attacks.

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efficiency

arXiv Machine Learning

Sep 22

An LLM-Assisted AutoML Framework for Intrusion Detection in IoT Networks

arXiv:2609.23097v1 Announce Type: cross Abstract: Internet of Things (IoT) systems are increasingly deployed in smart homes, transportation, energy systems, and critical infrastructure. This broad co...

By Li Yang

llms

arXiv AI

Jul 1

Comparative Analysis of Machine Learning based Intrusion Detection in Realistic IoT Networks

arXiv:2606. 31594v1 Announce Type: cross Abstract: The Internet of Things (IoT) is rapidly growing and expanding into various sectors, such as healthcare, transportation, smart homes, and more.

By Rana Alharbi, Chuadhry Mujeeb Ahmed

safety

arXiv Machine Learning

Aug 4

Explainable Hybrid Feature Selection for Intrusion Detection in Internet of Medical Things Environments

arXiv:2608. 00869v1 Announce Type: cross Abstract: Internet of Medical Things (IoMT) networks are hard to protect: devices are heterogeneous, computing resources are scarce, and traffic must be analyzed in real time.

By Amira Berrezzek, Hayet Djellali, Giulio Mallardi, Lamia Mahnane

arXiv AI

Jun 2

XAI-SOH-FL: Enhancing SOH-FL with Adaptive Aggregation and Explainable AI for Intrusion Detection in Heterogeneous IoT

arXiv:2606. 00134v1 Announce Type: cross Abstract: Intrusion Detection Systems (IDS) in Internet of Things (IoT) environments face significant challenges due to data heterogeneity, lack of labeled data, and limited model interpretability.

By Ambreen Aslam, Maaz Hassan, Bibi Zahra, Muhammad Khuram Shahzad

safety

arXiv Machine Learning

4d ago

Multi-Class, Multi-Tier Network Intrusion Detection: A Comprehensive and Reproducible Benchmark

arXiv:2609.36039v1 Announce Type: cross Abstract: Machine learning (ML) and deep learning (DL) have dominated Intrusion Detection System (IDS) research in recent years. Unfortunately, many existing s...

By Yufeng Xin, Bryant Goseland, Mohamed Rahouti

benchmarks

arXiv Machine Learning

Jun 10

nCMD: Benign-Anchored Feature Selection for Imbalanced Network Intrusion Detection

arXiv:2606. 09934v1 Announce Type: new Abstract: Feature selection is critical for network intrusion detection systems (NIDS) operating under high-dimensional, highly imbalanced traffic, as found in operational and defense networks.

By Abu Fuad Ahmad, Istiaque Ahmed

benchmarks

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