Results for “computational-pathology”

Detect poisoned training data and backdoored models across the ML pipeline using statistical analysis, activation clustering, and spectral signatures.

Analyzes malware command-and-control (C2) communication protocols to understand beacon patterns, command structures, data encoding, and infrastructure for detection development and threat intelligence.

Analyze PCAP files by reconstructing TCP/UDP sessions, decoding application-layer protocols, and correlating packet sequences with host or malware behavior for CTF challenges.