A new set partitioning strategy using Grassmann distance and a gain mutual influence metric enables distributed attack detection in large IoT networks with at most 1.648% performance gap and O(1/m) computation reduction.
author Yaseen, M.U
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.DC 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Robust Set Partitioning Strategy for Malicious Information Detection in Large-Scale Internet of Things
A new set partitioning strategy using Grassmann distance and a gain mutual influence metric enables distributed attack detection in large IoT networks with at most 1.648% performance gap and O(1/m) computation reduction.