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SQL Injection Attack Detection and Prevention Based on Manipulating the SQL Query Input Attributes

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Computational Sciences and Sustainable Technologies (ICCSST 2023)

Abstract

SQL injection refers to one of the types of database attacks for web applications. The database security is compromised when wild card characters, malicious code, or malicious SQL query string are injected into the database. These changes in syntax and semantic allow the attacker to gain access to sensitive information and manipulate the database. Various techniques have been developed to detect and prevent this type of attacks. In this article, we proposed an method for preventing and detecting SQL injection. This method manipulates the SQL query input parameters and determining the distance between query strings. This method satisfies static query and dynamic also.

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References

  1. Anley, C.: Advanced SQL Injection In SQL Server Applications. Next Generation Security Software Ltd, White Paper (2002)

    Google Scholar 

  2. Boyd, S.W., Keromytis, A.D.: SQLrand: preventing SQL injection attacks. In: Jakobsson, M., Yung, M., Zhou, J. (eds.) ACNS 2004. LNCS, vol. 3089, pp. 292–302. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-24852-1_21

    Chapter  Google Scholar 

  3. Gould, C., Su, Z., Devanbu, P.: JDBC checker: a static analysis tool for SQL/JDBC applications. In: Proceedings of the 26th International Conference on Software Engineering (ICSE), pp. 697–698 (2004)

    Google Scholar 

  4. Huang, Y.-W., Yu, F., Hang, C., Tsai, C.-H., Lee, D.T., Kuo, S.-Y.: Securing Web application code by static analysis and runtime protection. In: Proceedings of the 12th International World Wide Web Conference (WWW 2004), pp. 40–52 (2004)

    Google Scholar 

  5. Halfond, W.G., Orso, A.: AMNESIA: analysis and monitoring for NEutralizing SQL-injection attacks. In: ACM, ASE 2005, November 7–11 (2005)

    Google Scholar 

  6. Buehrer, G., Weide, B.W., Sivilotti, P.A.G.: Using parse tree validation to prevent SQL injection attacks. In: Proceeding of the 5th International Workshop on Software Engineering and Middleware, pp. 106–113 ACM (2005)

    Google Scholar 

  7. McClure, R., Krger, I.: SQL DOM: compile time checking of dynamic SQL statements. In: Proceedings of the 27th International Conference on Software Engineering (ICSE 2005), pp. 88–96 (2005)

    Google Scholar 

  8. Buehrer, G., Weide, B.W., Sivilotti, P.A.: Using parse tree validation to prevent SQL InjectionAttacks, SEM 2005. In: Proceedings of the 5th international workshop on Software engineering and middleware, pp. 106–113 (2005)

    Google Scholar 

  9. Halfond, W.G., Orso, A., Manolios, P.: Using positive tainting and syntax-aware evaluation to counter sql injection attacks. In: ACM-SIGSOFT, pp. 175–185 (2006)

    Google Scholar 

  10. Su, Z., Wassermann, G.: The essence of command injection attacks in web applications. In: Conference Record of the 33rd ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, pp. 372–382 (2006)

    Google Scholar 

  11. Rietta, F.S.: Application layer intrusion detection for SQL injection, ACM-SE 44. In: Proceedings of the 44th annual Southeast regional conference, pp. 531–536 (2006)

    Google Scholar 

  12. Wei, K., Muthuprasanna, M., Kothari, S.: Preventing SQL injection attacks in stored procedurce. In: Software Engineering Conference, pp. 18–21 (2006)

    Google Scholar 

  13. Kosuga, Y., Kono, K., Hanaoka, M., Hishiyama, M., Takahama, Y.: Syntactic and semantic analysis for automated testing against SQL injection. In: Proceedings of the Computer Security Application Conference, pp. 107–117 (2007)

    Google Scholar 

  14. Bandhakavi, S., Bisht, P., Madhusudan, P., Venkatakrishnan, V.N.: CANDID: preventing SQL injection attacks using dynamic candidate evaluations. In: Proceedings of the Computer Security Application Conference, pp. 12–24 (2007)

    Google Scholar 

  15. Rawat, R., Dangi, C.S., Patil, J.: Safe guards anomalies against SQL injection attacks. Int. J. Comput. Appl. 22(2), 11–14 (2011)

    Google Scholar 

  16. Das, D., Sharma, U., Bhattacharyya, D.K.: An approach to detection of SQL injection attack based on dynamic query matching. Int. J. Comput. Appl. 127(14), 15–24 (2010)

    Google Scholar 

  17. Ciampa, A., Visaggio, C.A., Di Penta, M.: A heuristic-based approach for detecting SQL-injection vulnerabilities in Web applications. In: SESS 2010: Proceedings of the 2010 ICSE Workshop on Software Engineering for Secure Systems, pp. 43–49 (2010)

    Google Scholar 

  18. Lee, I., Jeong, S., Yeo, S., Moon, J.: Novel method for SQL injection attack detection based on removing SQL query attribute values. Math. Comput. Model. 55(1–2), 58–68 (2012)

    Article  MathSciNet  Google Scholar 

  19. Kar, D., Panigrahi, S., Sundararajan, S.: SQLiGoT: detecting SQL injection attacks using graph of tokens and SVM. Comput. Secur. 60, 206–225 (2016)

    Article  Google Scholar 

  20. Li, Q., Wang, F., Wang, J., Li, W.: LSTM-based SQL injection detection method for intelligent transportation system. IEEE Trans. Veh. Technol. 68(5), 4182–4191 (2019)

    Google Scholar 

  21. Gu, H., et al.: DIAVA: a traffic-based framework for detection of SQL injection attacks and vulnerability analysis of leaked data. IEEE Trans. Reliab. 69(1), 188–202 (2020)

    Article  Google Scholar 

  22. Liu, M., Li, K., Chen, T.: DeepSQLi: deep semantic learning for testing SQL injection, ISSTA 2020. In: Proceedings of the 29th ACM SIGSOFT, pp. 286–297 (2020)

    Google Scholar 

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Correspondence to R. Mahesh .

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Mahesh, R., Chellathurai, S., Thirunavukkarasu, M., Raman, P. (2024). SQL Injection Attack Detection and Prevention Based on Manipulating the SQL Query Input Attributes. In: Aurelia, S., J., C., Immanuel, A., Mani, J., Padmanabha, V. (eds) Computational Sciences and Sustainable Technologies. ICCSST 2023. Communications in Computer and Information Science, vol 1973. Springer, Cham. https://doi.org/10.1007/978-3-031-50993-3_17

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  • DOI: https://doi.org/10.1007/978-3-031-50993-3_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-50992-6

  • Online ISBN: 978-3-031-50993-3

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