ma-Does the implementation of machine-learning-based anomaly detection increase the risk of system latency and false-positive trips in automated smart grid controllers compared to traditional regex-based filtering?
The findings indicate that hybrid-based approach to architecture should be suggested, where rule-based filtering is applied to address the time-sensitive deterministic checks, and the ML models give the context-driven anomaly analysis on both the SCADA and the wide-area layers.
The findings indicate that hybrid-based approach to architecture should be suggested, where rule-based filtering is applied to address the time-sensitive deterministic checks, and the ML models give the context-driven anomaly analysis on both the SCADA and the wide-area layers.
Wenxuan Cao· Science and Technology of En...· 0 citations
SA-IDS is proposed, a self-supervised and adaptive intrusion detection framework designed for resource-constrained IIoT edge devices that leverages contrastive self-supervised learning to learn robust representations of benign telemetry data without requiring labeled attacks.
Modern vehicles depend on dozens of Electronic Control Units (ECUs) that exchange messages over the Controller Area Network (CAN) bus. Because CAN lacks authentication and encryption, it remains susceptible to message-injection attacks. We present an empirical study of reconstruction-based CAN intrusion detection acros...
Amirmasoud Pourmiri, Ali Eslami, Sergio A. Salinas Monroy· International Conference on...· 0 citations
A hybrid IDS framework that integrates supervised Random Forest classification, unsupervised Isolation Forest anomaly monitoring, and Kolmogorov–Smirnov (KS)-based concept drift monitoring is presented, providing initial evidence of generalization to one held-out attack family but should not be interpreted as proof of...
Muath A. Obaidat, Meryem Abouali, Aneeza Shakeel· Italian National Conference...· 0 citations
Security researchers rely heavily on Network Intrusion Detection Systems (NIDS) to keep an eye on network traffic and notify administrators of any suspicious activities. The purpose of this paper is to offer a comprehensive overview of intrusion detection systems (IDS), including the following topics: fundamentals, kin...
Madhav Sharma· International Journal of Cyb...· 0 citations
This study proposes an anomaly-based deep learning model for detecting both known and zero-day attacks in heterogeneous network environments that integrates advanced traffic preprocessing, automated feature extraction, deep neural representation learning, adaptive anomaly scoring, and intelligent attack classification...
Aswathy N. Rajan· Journal of Intelligent Decis...· 0 citations
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