Cyber threat trend analysis model using HMM

Do Hoon Kim, Taek Lee, Sung Oh David Jung, Hoh In, Heejo Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

19 Citations (Scopus)

Abstract

Prevention is normally recognized as one of the best defense strategy against malicious hackers or attackers. The desire of deploying better prevention mechanisms has motivated many security researchers and practitioners, who are studies threat trend analysis models. However, threat trend is not directly revealed from the time-series data because the trend is implicit in its nature. Besides, traditional time-series analysis, which predicts the future trend pattern by relying exclusively on the past trend pattern, is not appropriate for predicting a trend pattern in dynamic network environments (e.g., the Internet). Thus, supplemental environmental information is required to uncover a trend pattern from the implicit (or hidden) raw data. In this paper, we propose Cyber Threat Trend Analysis Model using Hidden Markov Model (HMM) by incorporating the supplemental environmental information into the trend analysis.

Original languageEnglish
Title of host publicationProceedings - IAS 2007 3rd Internationl Symposium on Information Assurance and Security
Pages177-182
Number of pages6
DOIs
Publication statusPublished - 2007 Dec 1
Event3rd Internationl Symposium on Information Assurance and Security, IAS 2007 - Manchester, United Kingdom
Duration: 2007 Aug 202007 Aug 31

Other

Other3rd Internationl Symposium on Information Assurance and Security, IAS 2007
CountryUnited Kingdom
CityManchester
Period07/8/2007/8/31

    Fingerprint

ASJC Scopus subject areas

  • Information Systems
  • Information Systems and Management

Cite this

Kim, D. H., Lee, T., Jung, S. O. D., In, H., & Lee, H. (2007). Cyber threat trend analysis model using HMM. In Proceedings - IAS 2007 3rd Internationl Symposium on Information Assurance and Security (pp. 177-182). [4299771] https://doi.org/10.1109/IAS.2007.19