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2008 International Conference on Computational Intelligence and Security
An Evaluation of API Calls Hooking Performance
December 13-December 17
ISBN: 978-0-7695-3508-1
| ASCII Text | x | ||
| Mohd Fadzli Marhusin, Henry Larkin, Chris Lokan, David Cornforth, "An Evaluation of API Calls Hooking Performance," 2012 Eighth International Conference on Computational Intelligence and Security, vol. 1, pp. 315-319, 2008 International Conference on Computational Intelligence and Security, 2008. | |||
| BibTex | x | ||
| @article{ 10.1109/CIS.2008.199, author = {Mohd Fadzli Marhusin and Henry Larkin and Chris Lokan and David Cornforth}, title = {An Evaluation of API Calls Hooking Performance}, journal ={2012 Eighth International Conference on Computational Intelligence and Security}, volume = {1}, year = {2008}, isbn = {978-0-7695-3508-1}, pages = {315-319}, doi = {http://doi.ieeecomputersociety.org/10.1109/CIS.2008.199}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - 2012 Eighth International Conference on Computational Intelligence and Security TI - An Evaluation of API Calls Hooking Performance SN - 978-0-7695-3508-1 SP315 EP319 A1 - Mohd Fadzli Marhusin, A1 - Henry Larkin, A1 - Chris Lokan, A1 - David Cornforth, PY - 2008 KW - Malicious code KW - API sequence KW - system call KW - malware detection VL - 1 JA - 2012 Eighth International Conference on Computational Intelligence and Security ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CIS.2008.199
An open research question in malware detection is how to accurately and reliably distinguish a malware program from a benign one, running on the same machine. In contrast to code signatures, which are commonly used in commercial protection software, signatures derived from system calls have the potential to form the basis of a much more flexible defense mechanism. However, the performance degradation caused by monitoring systems calls could adversely impact the machine. In this paper we report our experimental experience in implementing API hooking to capture sequences of API calls. The loading time often common programs was benchmarked with three different settings: plain, computer with antivirus and computer with API hook. Results suggest that the performance of this technique is sufficient to provide a viable approach to distinguishing between benign and malware code execution.
Index Terms:
Malicious code, API sequence, system call, malware detection
Citation:
Mohd Fadzli Marhusin, Henry Larkin, Chris Lokan, David Cornforth, "An Evaluation of API Calls Hooking Performance," cis, vol. 1, pp.315-319, 2008 International Conference on Computational Intelligence and Security, 2008
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