I-Corps: Machine Learning Based Graph Analytics for Cyber Security Applications
Abstract
Cyber security is a key issue in today s highly connected and digital world. High profile cyber networks ranging from the public sector to the private sector are constantly under attack from adversaries with intentions ranging from vandalism to espionage. Unfortunately, as seen through the frequent news reports, high profile networks are frequently getting infiltrated, and sensitive information exfiltrated, and often put up for sale on the dark web. For this reason, improved defensive cyber security measures can greatly benefit society as a whole, better protecting the industries and services we all rely on. The goal of this T-Corps project is to perform customer discovery of our research on graph analytics for cyber threat detection and network monitoring. Our technology provides real-time, highly accurate detection of a wide range of cyber attacks that are traditionally challenging to detect in enterprise networks (e.g., insider threats and zero-day attacks). The outcome of the project includes a deep understanding of the marketplace and the formalization of the commercialization strategy for our research.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jun 25, 2021
- Source ID
- W911NF2110104
Entities
People
- Hao Huang
Organizations
- Army Contracting Command
- George Washington University
- Office of the Secretary of Defense