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Distributed Packet Trace Processing Method for Information Security Analysis

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Internet of Things, Smart Spaces, and Next Generation Networks and Systems (NEW2AN 2014)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 8638))

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Abstract

Information security is an important topic today. Internet Service Providers use network traffic analysis for evaluating network performance, collecting statistics and detecting vulnerabilities. Analysing traffic traces collected from large network requires a computer system where both storage and computing resources can be scaled out to handle and process multi-Terabyte files. Cloud platforms and clustered file systems provide re-sizable compute and storage capacity. MapReduce programming model developed by Google, allows distributed processing of massive data amounts by defining map and reduce functions. In this paper, we propose a cloud computing framework based on MapReduce approach for fast internet traffic analytics.

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References

  1. IEEE 802 Numbers (2014), http://www.iana.org/assignments/ieee-802-numbers/ieee-802-numbers.xhtml

  2. Dean, J., Ghemawat, S.: Mapreduce: Simplified data processing on large clusters. In: Proceedings of the 6th Conference on Symposium on Opearting Systems Design & Implementation, OSDI 2004, vol. 6, pp. 10–10 (2004)

    Google Scholar 

  3. Kumawat, T., Sharma, P.K., Verma, D., Joshi, K., Kumawat, V.: Implementation of spark cluster technique with scala. International Journal of Scientific and Research Publications (IJSRP) 2(11) (2012)

    Google Scholar 

  4. Lee, Y., Kang, W., Lee, Y.: A hadoop-based packet trace processing tool. In: Domingo-Pascual, J., Shavitt, Y., Uhlig, S. (eds.) TMA 2011. LNCS, vol. 6613, pp. 51–63. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  5. Lee, Y., Lee, Y.: Toward scalable internet traffic measurement and analysis with hadoop. Computer Communication Review 43(1), 5–13 (2013)

    Article  Google Scholar 

  6. Lee, Y., Kang, W., Son, H.: An internet traffic analysis method with mapreduce. In: 2010 IEEE/IFIP Network Operations and Management Symposium Workshops (NOMS Wksps), pp. 357–361 (April 2010)

    Google Scholar 

  7. Lukashin, A., Zaborovsky, V.: Secure heterogeneous cloud platform for scientific computing. In: Proceedings of The Tenth International Conference on Networking and Services, ICNS 2014, pp. 24–28 (2014)

    Google Scholar 

  8. Lukashin, A., Zaborovsky, V.: Dynamic access control using virtual multicore firewalls. In: Proceedings of The Fourth International Conference on Evolving Internet, INTERNET 2012, pp. 37–43 (2012)

    Google Scholar 

  9. Lukashin, A., Zaborovsky, V., Kupreenko, S.: Access isolation mechanism based on virtual connection management in cloud systems - how to secure cloud system using high perfomance virtual firewalls. In: ICEIS, vol. (3) (2011)

    Google Scholar 

  10. Qiao, Y.Y., Lei, Z.M., Yuan, L., Guo, M.J.: Offline traffic analysis system based on hadoop. The Journal of China Universities of Posts and Telecommunications 20, 97–103 (2013)

    Article  Google Scholar 

  11. Vieira, T., Soares, P., Machado, M., Assad, R., Garcia, V.: Measuring distributed applications through mapreduce and traffic analysis. In: Proceedings of the 2012 IEEE 18th International Conference on Parallel and Distributed Systems, ICPADS 2012, pp. 704–705 (2012)

    Google Scholar 

  12. Vieira, T.P.D.B., Fernandes, S.F.D.L., Garcia, V.C.: Evaluating mapreduce for profiling application traffic. In: Proceedings of the First Edition Workshop on High Performance and Programmable Networking, HPPN 2013, pp. 45–52 (2013)

    Google Scholar 

  13. Xin, R.S., Rosen, J., Zaharia, M., Franklin, M.J., Shenker, S., Stoica, I.: Shark: Sql and rich analytics at scale. In: Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data, SIGMOD 2013, pp. 13–24. ACM, New York (2013)

    Google Scholar 

  14. Zaborovskiy, V., Lukashin, A., Popov, S., Vostrov, A.: Adage mobile services for its infrastructure. In: Proceedings of The 13th International Conference on ITS Telecommunications, ITST 2013, pp. 127–132 (2013)

    Google Scholar 

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Lukashin, A., Laboshin, L., Zaborovsky, V., Mulukha, V. (2014). Distributed Packet Trace Processing Method for Information Security Analysis. In: Balandin, S., Andreev, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. NEW2AN 2014. Lecture Notes in Computer Science, vol 8638. Springer, Cham. https://doi.org/10.1007/978-3-319-10353-2_49

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  • DOI: https://doi.org/10.1007/978-3-319-10353-2_49

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10352-5

  • Online ISBN: 978-3-319-10353-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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