In-execution malware detection using task structures of Linux processes

IEEE International Conference on Communications

Volumn , Issue , 2011, Pages

  Shahzad, Farrukh ^a   Bhatti, Sohail ^a   Shahzad, Muhammad ^a   Farooq, Muddassar ^a  

^a NATIONAL UNIVERSITY OF COMPUTER AND EMERGING SCIENCES   (Pakistan)

Author keywords

[No Author keywords available]

Indexed keywords

DETECTION ACCURACY; FALSE ALARM RATE; KERNEL MODULES; KERNEL STRUCTURE; LOW-LEVEL SYSTEMS; MALWARE DETECTION; OPERATING SYSTEM KERNEL; PROCESSING OVERHEAD; PROOF OF CONCEPT; RUN-TIME ANALYSIS; TASK STRUCTURE;

COMPUTER OPERATING SYSTEMS; TIME SERIES;

TIME SERIES ANALYSIS;

EID: 80052179015     PISSN: 05361486     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/icc.2011.5963012     Document Type: Conference Paper

References (17)

1. VX Heavens, A Malware Collection Web-site, http://hvx.netlux.org
2. J. Giffin, S. Jha and B. Miller, Efficient Context-sensitive Intrusion Detection, Network and Distributed Systems Security Symposium, 2004.
3. O. Ben-Cohen, A. Wool, Korset: Automated, Zero False-Alarm Intrusion Detection for Linux, Linux Symposium, pp. 31, 2008.
4. L. Vokorokos, A. Balaz, M.Chovanec, Intrusion Detection System using Self Organizing Maps, Acta Electrotechnica et Informatica No. 1, pp. 1-5, 2006.
5. S. Bandyopadhyay, A Study on Performance Monitoring Counters in x86-Architecture, Indian Statistical Institute.
6. L. Sun, T. Katori, A Lightweight Kernel Object Monitoring Infrastructure for Embedded Linux Systems, IEEE Conference on Embedded and Real-Time Computing Systems and Applications, pp. 55-60, 2008.
7. K. Zhao, Q. Li, J. Kang, D. Jiang, L. Hu, Design and Implementation of Secure Auditing System in Linux Kernel, IEEE Workshop on Anticounterfeiting, Security, Identification, pp. 232-236, 2007.
8. B. Dolan-Gavitt , A. Srivastava , P. Traynor , J. Giffin, Robust Signatures for Kernel Data Structures, ACM Conference on Computer and Communications Security, pp. 566-577, 2009.
9. S. Forrest, S. A. Hofmeyr, A. Somayaji, T. A. Longstaff, A Sense of Self for Unix Processes, IEEE Symposium on Security and Privacy, pp. 120-128, 1996.
10. W. Xun, Y. Wei, A. Champion, F. Xinwen, X. Dong, Detecting Worms via Mining Ddynamic Program Execution, International Conference on Security and Privacy in Communication Networks and the Workshops, pp. 412-421, 2007.
11. J. B. D. Cabrera, L. Lewis, R. K. Mehra, Detection and Classification of Intrusions and Faults using Sequences of System Calls, ACM SIGMOD Record, vol.30, no.4, pp. 25-34, 2001.
12. D. Wagner, D. Dean, Intrusion Detection via Static analysis, IEEE Symposium on Security and Privacy, pp. 156-168, 2001.
13. Jonathon T. Giffin, D. Dagon, S. Jha, W. Lee, B. P. Miller, Environment-sensitive Intrusion Detection, International Conference on Recent Advances in Intrusion Detection, pp.185-206, 2006.
14. H. H. Feng, J. T. Giffin, Y. Huang, S. Jha, W. Lee, B. P. Miller, Formalizing Sensitivity in Static Analysis for Intrusion Detection, IEEE Symposium on Security and Privacy, pp. 194-208, 2004.
15. I. H. Witten, E. Frank, Data mining: Practical Machine Learning Tools and Techniques, Morgan Kaufmann, Second Edition, 2005.
16. P. Beaucamps, J. Y. Marion, Optimized Control Flow Graph Construction for Malware Detection, International Workshop on the Theory of Computer Viruses, 2008.
17. F. Ahmed, H. Hameed, M. Z. Shafiq, M. Farooq, Using Spatio-Temporal Information in API Calls with Machine Learning Algorithms for Malware Detection, ACM workshop on Security and Artificial Intelligence, pp. 55-62, 2009.