Protecting Against Cyber Threats in Networked Information Systems

L. Ertoz, A. Lazarevic, E. Eilertson, Pang Ning Tan, Paul Dokas, V. Kumar, Jaideep Srivastava

Research output: Contribution to journalConference articlepeer-review

10 Scopus citations


This paper provides an overview of our efforts in detecting cyber attacks in networked information systems. Traditional signature based techniques for detecting cyber attacks can only detect previously known intrusions and are useless against novel attacks and emerging threats. Our current research at the University of Minnesota is focused on developing data mining techniques to automatically detect attacks against computer networks and systems. This research is being conducted as a part of MINDS (Minnesota Intrusion Detection System) project at the University of Minnesota. Experimental results on live network traffic at the University of Minnesota show that the new techniques show great promise in detecting novel intrusions. In particular, during the past few months our techniques have been successful in automatically identifying several novel intrusions that could not be detected using state-of-the-art tools such as SNORT.

Original languageEnglish (US)
Pages (from-to)51-56
Number of pages6
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 2003
EventPROCEEDINGS OF SPIE SPIE - The International Society for Optical Engineering:Battlespace Digitization and Network-Centric Systems III - Orlando, FL, United States
Duration: Apr 23 2003Apr 25 2003


  • Anomaly / outlier detection
  • Characterization
  • Cyber threat analysis
  • Data mining
  • Learning from rare classes
  • Network intrusion detection


Dive into the research topics of 'Protecting Against Cyber Threats in Networked Information Systems'. Together they form a unique fingerprint.

Cite this