Earticle

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

키워드

저자

• Meisam Eslahi [ Faculty of Electrical Engineering, Universiti Teknologi MARA, Malaysia ] Corresponding author
• Moslem Yousefi [ Center for Advanced Mechatronics and Robotics, Universiti Tenaga Nadional Malaysia ]
• Maryam Var Naseri [ Advanced Informatics School, University Technology Malaysia, Malaysia. ]
• Y.M.Yussof [ Faculty of Electrical Engineering, Universiti Teknologi MARA, Malaysia ]
• N.M.Tahir [ Faculty of Electrical Engineering, Universiti Teknologi MARA, Malaysia ]
• H. Hashim [ Faculty of Electrical Engineering, Universiti Teknologi MARA, Malaysia ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Security and Its Applications

• 간기

  격월간

• pISSN

  1738-9976

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605