원문정보
보안공학연구지원센터(IJDTA)
International Journal of Database Theory and Application
Vol.9 No.11
2016.11
pp.195-206
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
With the rapid development of the Internet and the continuous expanding of the data network, little potential anomaly can seriously affect the normal operation of the network, and even lead to huge economic losses. In order to be more accurate and efficient in the traffic detection, in this paper, we propose an N-ARMA based traffic anomaly detection model. We also conduct extensive experiments to verify the higher accurate ratio and recall ratio of our model by comparing with other traffic anomaly detection methods.
목차
Abstract
1. Introduction
2. Related Work
3. ARMA Model
4. N-ARMA Traffic Detection Model
4.1. N-ARMA Model Introduction
4.2. N-ARMA Model Building
5. Experiments and Analysis
5.1. Data Preprocessing
5.2. N-ARMA Model Building
5.3. Outlier Detection Experiments
6. Conclusions
References
1. Introduction
2. Related Work
3. ARMA Model
4. N-ARMA Traffic Detection Model
4.1. N-ARMA Model Introduction
4.2. N-ARMA Model Building
5. Experiments and Analysis
5.1. Data Preprocessing
5.2. N-ARMA Model Building
5.3. Outlier Detection Experiments
6. Conclusions
References
저자정보
참고문헌
자료제공 : 네이버학술정보