Human-Computer Decision Systems Poster (SEI 2015 Research Review)
October 2015 • Poster
Describes work to use learning theory advances to account for persistent human expert teams and experiments to improve the human-computer decision syste
Publisher:
Software Engineering Institute
Abstract
Security decision systems aim to distinguish malicious activity from benign and often use a combination of human expert and automated analysis, including machine learning (ML). Systems using only human experts scale badly; pure ML systems are susceptible to structured attack by adversaries and, in most cases, have unsatisfactory performance on
their own.