A Multi-Objective AutoML-based Efficient Intrusion Detection System for EV Charging Networks
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. Intrusion Detection Systems (IDSs) are essential for securing EV charging networks; however, conventional Machine Learning (ML)-based IDSs often rely on manual model design and mainly optimize detection performance without fully considering inference latency and model size. In this paper, a Multi-Objecti
Record details
Published: 3 August 2026
Source: arXiv cs.CR (AI security)
Category: Research
Topics: Military & security
Retrieved: 4 August 2026
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ethics.ai (3 August 2026), “A Multi-Objective AutoML-based Efficient Intrusion Detection System for EV Charging Networks,” evidence record 16136, https://ethics.ai/record/16136 (originally published by arXiv cs.CR (AI security)).
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