Location
https://www.kennesaw.edu/ccse/events/computing-showcase/fa24-cday-program.php
Event Website
https://github.com/kamalksu/nsl-kdd/
Document Type
Event
Start Date
19-11-2024 4:00 PM
Description
Information security in the era of AI and automation is the biggest challenge for cybersecurity professionals. Traditional information security protection has limitations in detecting zero-day attacks, which can be overcome with machine learning-based information security. An ML-powered intrusion detection system uses statistical analysis to spot deviations from normal behavior and helps to detect new and unknown threats. This poster will demonstrate how an open-source platform can be used for cybersecurity by leveraging various machine-learning algorithms.
Included in
GMR-8193 Harnessing ML-Powered HPCC Systems for Advanced Cybersecurity Analytics
https://www.kennesaw.edu/ccse/events/computing-showcase/fa24-cday-program.php
Information security in the era of AI and automation is the biggest challenge for cybersecurity professionals. Traditional information security protection has limitations in detecting zero-day attacks, which can be overcome with machine learning-based information security. An ML-powered intrusion detection system uses statistical analysis to spot deviations from normal behavior and helps to detect new and unknown threats. This poster will demonstrate how an open-source platform can be used for cybersecurity by leveraging various machine-learning algorithms.
https://digitalcommons.kennesaw.edu/cday/Fall_2024/Masters_Research/13