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Join experts Sean Ensz, Sallie Wright, and Dr. Mark Weiser as they delve into the fundamentals of advanced attack detection and the critical role of infrastructure protection in today’s cybersecurity landscape. This presentation covers a technical overview of honeynet designs, detailing the benefits of production and research in enhancing IT security. Attendees will learn about the evolution of OSU's IT systems security and the importance of collaboration in developing effective tools for malicious traffic identification, intrusion prevention, and research advancement.
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Advanced Attack Detection andInfrastructure Protection Sean Ensz OU IT Security Analyst Sallie Wright OSU IT Security Officer Dr. Mark Weiser OSU Director of CTANS
Agenda • Technical Overview – Sean Ensz • Production Benefits – Sallie Wright • Research Benefits – Dr. Mark Weiser
Technical Overview • Core system based on a Honeynet design • A Honeynet is a network of honeypots • A honeypot is an information system resource whose value lies in illicit use of that resource • A honeypot has no legitimate users • Any traffic going to and from the system in inherently suspicious *Source: www.honeynet.org
Future Improvements • Honeywall • Needs better hardware & network driver support • Beta version to be released today • Host based logging • Currently relies on Sebek • Lacks host log and process tree support • Working with Third Brigade to develop a honeypot version of their product
2005 2003-2004 2001-2002 2000 OSU IT Systems Security Evolution Anti-Spam Intrusion Prevention System AIPS Border Firewall IT Security Plan LaBrea Tarpit IT Security Office Policy Focus Central Anti-virus IDS No real security Program WIDE OPEN
AIPS Production Benefits Identification of malicious hosts Ability to block at the border of Oklahoma’s OneNet state-wide network
Collaboration A key benefit is the ability to provide academic programs with tools to research Develop new ways to strengthen overall IT security.
Production Goal To contain and prevent intrusions while providing the data Flow analysis to tune the IT security process.
How This May Be Extended • Future Research • Related Endeavors
Day Zero Signature Existing Signatures Candidate Detects Day Zero Signature Validation AI/Neural Nets Other Methods HN Design Attacks HN Wild Attacks
MiddleWare Router/ Firewall Honeynet “Solution” Middleware Platform-neutral Solution (file) Router Description / Access Information
Basic Near-Real-Time Activity Detector • Low-cost log gathering w/ local analysis • Central Cumulative Analysis • Trigger points distribute alerts to subscribers
Sean Ensz ensz@ou.edu Sallie Wright sallie.wright@okstate.edu Dr. Mark Weiser weiser@okstate.edu