UNCW MS Computer Science Information Systems Proceedings
Anomalous Network Protocols with Machine Learning and Zeek
Trevor Longmire
Jeffrey Cummings (Chair)
Geoff Stoker
Gulustan Dogan
Abstract
The USDA Office of the Chief Information Officer (OCIO) has requested the Cyber
Defense Operations Division (CDOD) provide a fully scalable system to monitor network
traffic in real time. Continuous monitoring on a large-scale organizational network
requires strategy, timely information and 24/7 vigilance. The Infrastructure Security
Center (ISC) within CDOD is tasked to provide ongoing solutions to manage risk within
the network. ISC uses a comprehensive tool suite for alerting and reacting to a variety of
network intrusion attempts. Some of those tools include Zeek intrusion detection systems
(IDS), and security event management systems (SIEM). There are many other systems
for integration and correlation of data and the licensing costs of these systems are enough
to explore the possibilities of having an open-source alternative. Using Zeek to detect
network anomalies will improve visibility of the network while driving down costs.
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Recommended Citation: Longmire T., Cummings J., Stoker G., Dogan G., (2023). Anomalous Network Protocols with Machine Learning and Zeek.
UNCW MS CSIS Proceedings.
V. 17
, N. 13
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