원문정보
보안공학연구지원센터(IJSIA)
International Journal of Security and Its Applications
Vol.10 No.9
2016.09
pp.39-44
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
The dynamic nature of Botnets along with their sophisticated characteristics makes them one of the biggest threats to cyber security. Recently, the HTTP protocol is widely used by Botmaster as they can easily hide their command and control traffic amongst the benign web traffic. This paper proposes a Neural Network based model to detect mobile HTTP Botnets with random intervals independent of the packet payload, commands content, and encryption complexity of Bot communications. The experimental test results that were conducted on existing datasets and real world Bot samples show that the proposed method is able to detect mobile HTTP Botnets with high accuracy.
목차
Abstract
1. Introduction
2. Related Works
3. Proposed Architecture and Detection Methodology
3.1. Data Collection, Preparation and Grouping
3.2. Data Reduction and Filtering
3.3. Feature Preprocessing
3.4.Pattern Recognition Engine
4. Testbed Architecture and Experimental Data Collection
5. Experimental Result Analysis and Discussion
6. Conclusion
Acknowledgments
References
1. Introduction
2. Related Works
3. Proposed Architecture and Detection Methodology
3.1. Data Collection, Preparation and Grouping
3.2. Data Reduction and Filtering
3.3. Feature Preprocessing
3.4.Pattern Recognition Engine
4. Testbed Architecture and Experimental Data Collection
5. Experimental Result Analysis and Discussion
6. Conclusion
Acknowledgments
References
저자정보
참고문헌
자료제공 : 네이버학술정보