Identifying SQL Injection Risks Using the SMO  Algorithm

Author(s)	N. Dhansukh Rao, D. Lalitha, D. P. Laxman
Country	India
Abstract	The rapid expansion of online applications and services has heightened concerns about potential cyberattacks. SQL injection, a prevalent attack method, exploits vulnerabilities in online applications to gain unauthorized access to databases. Ensuring the security and integrity of online systems requires effective identification and prevention of SQL injection attacks. This study introduces a novel approach for detecting SQL injection attacks in network traffic data using the Sequential Minimal Optimization (SMO) algorithm. By leveraging machine learning, this research addresses the urgent need for efficient and accurate detection methods. The focus is on applying the SMO technique to identify and counter SQL injection threats through analysis of network traffic data. Network flow data, which captures interactions between hosts, offers valuable insights for detecting unusual patterns indicative of potential attacks
Keywords	Network, SQL injection, Attack, Sequential minimal optimization algorithm, Defense Mechanism.
Field	Engineering
Published In	Volume 4, Issue 4, July-August 2023
Published On	2023-08-21

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Advanced International Journal for Research