Research Article
Cyber Threat Trend Analysis Model Using HMM
@INPROCEEDINGS{10.1109/IAS.2007.19, author={ Do Hoon Kim and Taek Lee and Sung-Oh David Jung and Hoh Peter In and Hee Jo Lee}, title={Cyber Threat Trend Analysis Model Using HMM}, proceedings={3rd International ICST Symposium on Information Assurance and Security}, publisher={IEEE}, proceedings_a={IAS}, year={2007}, month={9}, keywords={Data analysis Data security Economic forecasting Hidden Markov models Information analysis Information security Internet Pattern analysis Predictive models Time series analysis}, doi={10.1109/IAS.2007.19} }- Do Hoon Kim
Taek Lee
Sung-Oh David Jung
Hoh Peter In
Hee Jo Lee
Year: 2007
Cyber Threat Trend Analysis Model Using HMM
IAS
IEEE
DOI: 10.1109/IAS.2007.19
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.
