1 citations · 3 across the 5 of their papers we have counts for
5 papers
Exposing Surveillance Detection Routes via Reinforcement Learning, Attack Graphs, and Cyber Terrain
Lanxiao Huang, Tyler Cody, Christopher Redino +8
Reinforcement learning (RL) operating on attack graphs leveraging cyber terrain principles are used to develop reward and state associated with determination of surveillance detect…
Zero Day Threat Detection Using Metric Learning Autoencoders
Dhruv Nandakumar, Robert Schiller, Christopher Redino +7
The proliferation of zero-day threats (ZDTs) to companies' networks has been immensely costly and requires novel methods to scan traffic for malicious behavior at massive scale. Th…
Anomaly Detection via Federated Learning
Marc Vucovich, Amogh Tarcar, Penjo Rebelo +11
Machine learning has helped advance the field of anomaly detection by incorporating classifiers and autoencoders to decipher between normal and anomalous behavior. Additionally, fe…
Zero Day Threat Detection Using Graph and Flow Based Security Telemetry
Christopher Redino, Dhruv Nandakumar, Robert Schiller +6
Zero Day Threats (ZDT) are novel methods used by malicious actors to attack and exploit information technology (IT) networks or infrastructure. In the past few years, the number of…
Crown Jewels Analysis using Reinforcement Learning with Attack Graphs
Rohit Gangupantulu, Tyler Cody, Abdul Rahman +3
Cyber attacks pose existential threats to nations and enterprises. Current practice favors piece-wise analysis using threat-models in the stead of rigorous cyber terrain analysis a…