Cyber Threat Trend Analysis Model Using HMM

Prevention, not reaction, is normally recognized as one of the best defense strategy against malicious hackers or attackers. The desire of deploying better prevention mechanism motivated many security researchers and practitioners to develop a threat trend analysis model. However, threat trend is not directly revealed from the time-series data because it is normally 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 the dynamic network environment. Thus, supplemental environment information is required to discover a trend pattern from the implicit (or hidden) raw data. In this paper, by applying the supplemental environment information into the trend analysis, Cyber Threat Trend Analysis Model using Hidden Markov Model (HMM) is proposed.

• Type: Conference
• Year: 2007
• Where: IEEEIAS
• Authors: Do-Hoon Kim, Taek Lee, Sung-Oh David Jung, Hoh Peter In, Heejo Lee
• Keywords: IEEEIAS 2007, Information Technology, Threat Trend, Threat Trend Analysis, Trend Pattern