1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CR2026
TERMon: Detecting Persistent Behavioral Threats in Edge AI via Hardware-Native Ternary Runtime Monitor
Arish Sateesan, Edlira Dushku
Edge AI accelerators are increasingly deployed in safety-critical environments, where model outputs may control physical actuators, make access-control decisions, or trigger alarms…
cs.CR2023★ 1 cited
ALBUS: a Probabilistic Monitoring Algorithm to Counter Burst-Flood Attacks
Simon Scherrer, Jo Vliegen, Arish Sateesan +3
Modern DDoS defense systems rely on probabilistic monitoring algorithms to identify flows that exceed a volume threshold and should thus be penalized. Commonly, classic sketch algo…
cs.NI2021
Low-Rate Overuse Flow Tracer (LOFT): An Efficient and Scalable Algorithm for Detecting Overuse Flows
Simon Scherrer, Che-Yu Wu, Yu-Hsi Chiang +7
Current probabilistic flow-size monitoring can only detect heavy hitters (e.g., flows utilizing 10 times their permitted bandwidth), but cannot detect smaller overuse (e.g., flows…