Abstract
With the spread use of the computers, a new crime space and method are presented for criminals. Computer evidence plays a key part in criminal cases. Traditional computer evidence searches require that the computer specialists know what is stored in the given computer. Binary-based information flow tracking which concerns on the changes of control flow is an effective way to analyze the behavior of a program. The existing systems ignore the modifications of the data flow, which may be also a malicious behavior. Function recognition is introduced to improve the information flow tracking, which recognizes the function body from the software binary. And no false positive and false negative in our experiment strongly prove that our approach is effective.
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References
Baek, E., Kim, Y., Sung, J., Lee, S.: The Design of Framework for Detecting an Insiders Leak of Confidential Information. e-Forensics (2008)
Pan, L., Margaret Batten, L.: Robust Correctness Testing for Digital Forensic Tools. e-Forensics (2009)
Guilfanov, I.: Fast Library Identification and Recognition Technology, http://www.hex-rays.com
Song, D.X., Brumley, D., Yin, H., Caballero, J., Jager, I., Kang, M.G., Liang, Z., Newsome, J., Poosankam, P., Saxena, P.: BitBlaze: A new approach to computer security via binary analysis. In: Sekar, R., Pujari, A.K. (eds.) ICISS 2008. LNCS, vol. 5352, pp. 1–25. Springer, Heidelberg (2008)
Clause, J.A., Li, W., Orso, A.: Dytan: a generic dynamic taint analysis framework. In: ISSTA 2007 (2007)
Cifuentes, C., Simon, D.: Procedure Abstraction Recovery from Binary Code. In: CSMR 2000 (2000)
Clause, J.A., Orso, A.: Penumbra: automatically identifying failure-relevant inputs using dynamic tainting. In: ISSTA 2009 (2009)
Mittal, G., Zaretsky, D., Memik, G., Banerjee, P.: Automatic extraction of function bodies from software binaries. In: ASP-DAC 2005 (2005)
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© 2011 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Zhou, K., Huang, S., Qi, Z., Gu, J., Shen, B. (2011). Enhance Information Flow Tracking with Function Recognition. In: Lai, X., Gu, D., Jin, B., Wang, Y., Li, H. (eds) Forensics in Telecommunications, Information, and Multimedia. e-Forensics 2010. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 56. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23602-0_16
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DOI: https://doi.org/10.1007/978-3-642-23602-0_16
Publisher Name: Springer, Berlin, Heidelberg
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