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ELF-Based Computer Virus Prevention Technologies

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Information Computing and Applications (ICICA 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 244))

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Abstract

Computer virus has become the important threat to information security. Once attacked by virus, user will suffer from great loss and potential threat. Construct a safe and healthy network environment, it is tireless pursuit of anti-virus expert, and also the wishes of all Internet users. In this article, we will analyze deeply the internal mechanism, algorithm and related technology of ELF virus in Linux system and give related prevention measures. Through the analysis of the code, we can detect the new virus and variations of the existing virus. This article accords with request of the current anti-virus technology’s development.

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References

  1. Kim, E.Y., Lee, C.H., Oh, H.G., Lee, J.S.: The System Modeling for Detections of New Malicious Codes. In: Dongarra, J., Madsen, K., Waśniewski, J. (eds.) PARA 2004. LNCS, vol. 3732, pp. 992–999. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  2. Tool Interface Standards (TIS) Committee, Executable and Linking Format (ELF) Specification, Version 1.2 (May 1995)

    Google Scholar 

  3. Kim, S.-S., Choi, C., Choi, J., Kim, P.-K., Kim, H.: A Method for Efficient Malicious Code Detection Based on Conceptual Similarity. In: Gavrilova, M.L., Gervasi, O., Kumar, V., Tan, C.J.K., Taniar, D., Laganá, A., Mun, Y., Choo, H. (eds.) ICCSA 2006. LNCS, vol. 3983, pp. 567–576. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  4. AT&T, The Santa Cruz Operation, Inc. System V Application Binary Interface, Intel386TM Architecture Processor Supplement. 4 edn.

    Google Scholar 

  5. Schultz, M.G., Eskin, E., Zadok, E., Stolfo, S.: Data mining for detection of new malicious executables. In: Proc. of the 2001IEEE Symposium on Security and Privacy, pp. 38–49. IEEE press, Los Alamitos (2001)

    Google Scholar 

  6. Tian, H.T., Huang, L.S., Zhou, Z., et al.: Arm up Administrators: Automated Vulnerability Management. In: Proceedings of the 7th International Symposiumon Parallel Architectures, Algorithms and Networks, Hongkong, China, pp. 587–593 (2004)

    Google Scholar 

  7. Hughes, L.A., DeLone, G.J.: Viruses, worms, and Trojan horses-Serious crimes, nuisance, or both? Social Science Computer Review 25(1), 78–98 (2007)

    Article  Google Scholar 

  8. Wang, S.J.: Measures of retaining digital evidence to prosecute computer based cybercrimes. Computer Standards & Interfaces 29(2), 216–223 (2007)

    Article  Google Scholar 

  9. Moffie, M., Cheng, W., Kaeli, D.: Hunting Trojan Horses. In: Proc. of the 1st Workshop on Architectural and System Support for Improving Software Dependability (ASID 2006), California, pp. 12–17 (October 2006)

    Google Scholar 

  10. Reddy, D.K.S., Dash, S.K., Pujari, A.K.: New Malicious Code Detection Using Variable Length n-grams. In: Bagchi, A., Atluri, V. (eds.) ICISS 2006. LNCS, vol. 4332, pp. 276–288. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

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Li, Y., Yan, J. (2011). ELF-Based Computer Virus Prevention Technologies. In: Liu, C., Chang, J., Yang, A. (eds) Information Computing and Applications. ICICA 2011. Communications in Computer and Information Science, vol 244. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27452-7_84

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  • DOI: https://doi.org/10.1007/978-3-642-27452-7_84

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27451-0

  • Online ISBN: 978-3-642-27452-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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