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Towards data mining temporal patterns for anomaly intrusion detection systems

  • S. Sengupta
  • , B. Andriamanalimanana
  • , S. W. Card
  • , P. Kadam
  • , S. Ranwadkar
  • , K. Das
  • , S. Parikh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

A reasonably light-weight host and net-centric network IDS architecture model is indicated. The model is anomaly based on a state-driven notion of "anomaly". Therefore, the relevant distribution function need not remain constant; it could migrate from states to states without any a priori warning so long as its residency time at a next steady state is sufficiently long to make valid observations there. Only those intrusion events (basically DOS and DDOS variety) capable of triggering anomalous streams of attacks/response both near and/or far of target monitoring point(s) are considered at the first level of detection. At the next level of detection, the filtered states could be fine-combed in a batch mode to mine unacceptable strings of commands or known attack signatures.

Original languageEnglish
Title of host publicationProceedings of the 2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems
Subtitle of host publicationTechnology and Applications, IDAACS 2003
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages205-209
Number of pages5
ISBN (Electronic)0780381386, 9780780381384
DOIs
StatePublished - 2003
Event2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems, IDAACS 2003 - Lviv, Ukraine
Duration: Sep 8 2003Sep 10 2003

Publication series

NameProceedings of the 2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2003

Conference

Conference2nd IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems, IDAACS 2003
Country/TerritoryUkraine
CityLviv
Period09/8/0309/10/03

Keywords

  • Data mining
  • Event detection
  • Information resources
  • Information technology
  • Internet
  • Intrusion detection
  • Monitoring
  • Protection
  • Telecommunication traffic
  • Traffic control

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