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Modelling HTTP Requests with Regular Expressions for Detection of Cyber Attacks Targeted at Web Applications

  • Conference paper
International Joint Conference SOCO’14-CISIS’14-ICEUTE’14

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 299))

Abstract

In this paper we present our further research results concerning detection of cyber attacks targeted at the application layer. In particular we focus on detecting SQLIA (SQL Injection Attacks) and XSS (Cross Site Scripting). In our approach, we model normal traffic (HTTP requests) with the use of regular expressions. We report very good results achieved on the large benchmark CISC’10 database and compare them to other solutions.

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References

  1. Choraś, M., Kozik, R., Puchalski, D., Hołubowicz, W.: Correlation Approach for SQL Injection Attacks Detection. In: Herrero, Á., Snášel, V., Abraham, A., Zelinka, I., Baruque, B., Quintián, H., Calvo, J.L., Sedano, J., Corchado, E., et al. (eds.) Int. Joint Conf. CISIS’12-ICEUTE’12-SOCO’12. AISC, vol. 189, pp. 177–185. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  2. Choraś, M., Kozik, R.: Real-Time Analysis of Non-stationary and Complex Network Related Data for Injection Attempts Detection. In: Snasel, V., et al. (eds.) Soft Computing in Industrial Applications. AISC, vol. 223, pp. 257–264. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  3. Choraś, M., Kozik, R.: Evaluation of Various Techniques for SQL Injection Attack Detection. In: Burduk, R., Jackowski, K., Kurzynski, M., Wozniak, M., Zolnierek, A., et al. (eds.) CORES 2013. AISC, vol. 226, pp. 751–760. Springer, Heidelberg (2013)

    Google Scholar 

  4. Kozik, R., Choraś, M.: Machine Learning Techniques for Cyber Attacks Detection. In: Choras, R.S. (ed.) Image Processing and Communications Challenges 5. AISC, vol. 233, pp. 385–392. Springer, Heidelberg (2014)

    Google Scholar 

  5. Needleman Saul, B., Wunsch Christian, D.: A general method applicable to the search for similarities in the amino acid sequence of two proteins. Journal of Molecular Biology 48 (1970)

    Google Scholar 

  6. Kruegel, C., Toth, T., Kirda, E.: Service specific anomaly detection for network intrusion detection. In: Proc. of ACM Symposium on Applied Computing, pp. 201–208 (2002)

    Google Scholar 

  7. Nguyen, H.T., Torrano-Gimenez, C., Alvarez, G., Petrović, S., Franke, K.: Application of the Generic Feature Selection Measure in Detection of Web Attacks. In: Herrero, Á., Corchado, E. (eds.) CISIS 2011. LNCS, vol. 6694, pp. 25–32. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  8. Felzenszwalb, P.F., Huttenlocher, D.P.: Efficient Graph-Based Image Segmentation. International Journal of Computer Vision 59(2) (September 2004)

    Google Scholar 

  9. Herrero, A., Navarro, M., Corchado, E., Julián, V.: RT-MOVICAB-IDS: Addressing real-time intrusion detection. Future Generation Comp. Syst. 29(1), 250–261 (2013)

    Article  Google Scholar 

  10. SNORT. Project homepage, http://www.snort.org/

  11. SCALP. Project homepage, http://code.google.com/p/apache-scalp/

  12. PHPIDS. Project homepage, https://phpids.org/

  13. CSIC 2010 Dataset. Project homepage, http://iec.csic.es/dataset/

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Correspondence to Rafał Kozik .

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© 2014 Springer International Publishing Switzerland

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Kozik, R., Choraś, M., Renk, R., Hołubowicz, W. (2014). Modelling HTTP Requests with Regular Expressions for Detection of Cyber Attacks Targeted at Web Applications. In: de la Puerta, J., et al. International Joint Conference SOCO’14-CISIS’14-ICEUTE’14. Advances in Intelligent Systems and Computing, vol 299. Springer, Cham. https://doi.org/10.1007/978-3-319-07995-0_52

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  • DOI: https://doi.org/10.1007/978-3-319-07995-0_52

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07994-3

  • Online ISBN: 978-3-319-07995-0

  • eBook Packages: EngineeringEngineering (R0)

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