Abstract
Structured query language (SQL) injection is an attack method that explores the functional and storage vulnerabilities of web applications that have data stored in a database. The attacker is capable of affecting the security by intentionally deciding the content that will be forwarded to the database for information retrieval. The attacker gets the benefit by exploiting the syntax and storage vulnerabilities that are responsible for weak points generated in the DBMS security system. This study makes use of the Snort intrusion detection system log files that contain information affiliated to attackers and can provide timed attack notifications via digital notification systems, like emails. In this research, a web server-based network system is initialized using the Snort intrusion detection system (IDS) to detect various methods of SQL injection attacks possible. The method used is based on NIST standards which are based on major risk assessment phases. This is a five phase-based research that performs exploit site testing, simulating attack circumstances, configuring IDS, collecting data and final phase of performing analysis. This study contributes to a web server-based IDS snort system that is capable of detecting a significant number of SQL injection attacks and real-time response notifying system via digital notifications.
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Bhardwaj, S., Dave, M. (2021). SQL Injection Attack Detection, Evidence Collection, and Notifying System Using Standard Intrusion Detection System in Network Forensics. In: Balas, V.E., Hassanien, A.E., Chakrabarti, S., Mandal, L. (eds) Proceedings of International Conference on Computational Intelligence, Data Science and Cloud Computing. Lecture Notes on Data Engineering and Communications Technologies, vol 62. Springer, Singapore. https://doi.org/10.1007/978-981-33-4968-1_53
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DOI: https://doi.org/10.1007/978-981-33-4968-1_53
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