Paper Title
A Survey on SQL Injection Detection Techniques for Website Security
Article Identifiers
: Authors
Keywords
SQL injection attack, SQLIA prevention, Query Transformation, Normalization of Queries, Document Similarity, Hidden Markov Model, Support Vector Machine, Graph of Tokens, Centrality Measures, Feature Selection
Abstract
In this survey paper discuss the SQL Injection (SQLi) is a critical web security vulnerability that occurs when attackers exploit input fields on websites to inject malicious SQL queries. These attacks can lead to unauthorized data access, manipulation, or deletion, posing severe threats to the confidentiality and integrity of sensitive information. Detecting SQL injections involves various techniques aimed at preventing such breaches. Signature-based detection identifies known attack patterns, while anomaly-based methods flag deviations from typical behavior in SQL queries. This survey paper explores the Additionally, input validation techniques like whitelisting and parameterized queries help prevent harmful SQL code execution. These methods, when combined with web application firewalls (WAFs) and security testing tools, form a robust defense mechanism to safeguard websites against SQL injection attacks, ensuring higher levels of security and reliability for web applications
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How To Cite (APA)
Pooja panadiya & Prof. Manish Kumar Singhal (October-2024). A Survey on SQL Injection Detection Techniques for Website Security. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(10), c32-c35. https://ijnrd.org/papers/IJNRD2410207.pdf
Issue
Volume 9 Issue 10, October-2024
Pages : c32-c35
Other Publication Details
Paper Reg. ID: IJNRD_301363
Published Paper Id: IJNRD2410207
Downloads: 000122254
Research Area: Science All
Author Type: Indian Author
Country: Bhopal, Madhya Pradesh, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2410207.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2410207
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