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Akinwole Obafemi

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Open access Sep 2026

DO CAN INTRUSION DETECTORS TRAVEL? A CROSS-DATASET AND ZERO-DAY STUDY WITH IDENTIFIER-AGNOSTIC, LOCALLY CALIBRATED ENSEMBLES

Intrusion detection systems (IDS) for the vehicular CAN bus that use Machine Learning are usually evaluated and reported to achieve very high detection accuracy, commonly above 99%, on random splits of a single dataset. We test and reproduce such high detection accuracy for four publicly available CAN IDS benchmark cor...

Akinwole Obafemi · 0 citations
#edge computing Open access Sep 2026

INTELLIGENT BANDWIDTH ALLOCATION FOR COOPERATIVE PERCEPTION IN EDGE–IOT VEHICULAR SYSTEMS: LEARNING WHAT TO SHARE UNDER COMMUNICATION BUDGETS

The objective is to decide what to share under a single hard ego-side communication budget, and the allocator reaches 97% of full-fusion accuracy at lower energy than the baseline in all 243 parameterisations tested, and in 240 of 243 on total energy, where the helpers' compute dominates.

Akinwole Obafemi · 0 citations

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