Training
Featured CourseView All Courses

SEC595: Applied Data Science and AI/Machine Learning for Cybersecurity Professionals

SEC595Cyber Defense, Artificial Intelligence
SEC595: Applied Data Science and AI/Machine Learning for Cybersecurity Professionals
View course detailsRegister
Get a Free Hour of SANS Training

Experience SANS training through course previews.

Learn More
Learning Paths
FeaturedView all Focus Areas
NEW - AI Security Training
Can't find what you are looking for?

Let us help.

Contact us
Free Resources

SANS Community Benefits

Connect, learn, and share with other cybersecurity professionals

Customer Case Studies

Discover how organizations and individual cyber practitioners use SANS training and GIAC certifications

AI Risk & Readiness

Explore expert-driven guidance, training, and tools to help defend against AI-powered threats and adopt AI securely

Join the SANS Community

Become a member for instant access to our free resources.

Sign Up
For Organizations

Public Sector

Mission-focused cybersecurity training for government, defense, and education

Partnerships

Explore industry-specific programming and customized training solutions

Sponsorship Opportunities

Sponsor a SANS event or research paper

Interested in developing a training plan to fit your organization’s needs?

We're here to help.

Contact Us
Group Purchasing
Group Purchasing

Open Source Host Based Intrusion Detections System (OHIDS)

Download File
Open Source Host Based Intrusion Detections System (OHIDS) (PDF, 3.36MB)Published: 06 Sep, 2013
Created by:
Tom Webb

Responding to incidents in an efficient manner is critical for all CIRTS. This paper presents a new open source tool for the enterprise. With this tool, responders will be able to detect incidents using aggregated data collected from hosts and applying anomaly detection. OHIDS includes a sensitive data finder to allow appropriate escalation of the incident. This software can be utilized in a proactive manner by removing SSNs and credit card data before incidents occur or by detecting unauthorized software running.