The increasing heterogeneity of Internet of Things (IoT) environments makes intrusion diagnosis challenging because device behaviours, traffic patterns, and attack distributions can vary across deployment conditions, while data-locality requirements limit centralized access to network data. This study proposes CA-AFiD...
Cloud-centric internet of things (IoT) environments continuously generates heterogeneous network traffic, making intrusion detection increasingly challenging as attack behaviors evolve beyond previously observed patterns. Conventional intrusion detection systems (IDS) rely primarily on supervised classification, limiti...
Jawahar Muthusamy, Palani Latha, R. Ponnumani et al.· Bulletin of Electrical Engin...· 0 citations
The increasing heterogeneity and scale of Internet of Things (IoT) ecosystems have intensified cybersecurity challenges associated with highly imbalanced traffic distributions, evolving attack patterns, and resource-constrained deployment environments. Conventional cloud-centric intrusion detection systems often intr...
Ashutosh Shankhdhar, A. Sivakumaran, Nithya Rekha Sivakumar et al.· Scientific Reports· 0 citations
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