Web Anomaly Misuse Intrusion Detection Framework for SQL Injection Detection

Abstract

 Databases at the background of e-commerce applications are vulnerable to SQL injection attack which is considered as one of the most dangerous web attacks. In this paper we propose a framework based on misuse and anomaly detection techniques to detect SQL injection attack. The main idea of this framework is to create a profile for legitimate database behavior extracted from applying association rules on XML file containing queries submitted from application to the database. As a second step in the detection process, the structure of the query under observation will be compared against the legitimate queries stored in the XML file thus minimizing false positive alarms

Authors and Affiliations

Shaimaa Ezzat Salama , Mohamed I. Marie , Laila M. El-Fangary , Yehia K. Helmy

Keywords

Related Articles

RIN-Sum: A System for Query-Specific Multi-Document Extractive Summarization

In paper, we have proposed a novel summarization framework to generate a quality summary by extracting Relevant-Informative-Novel (RIN) sentences from topically related document collection called as RIN-Sum. In the propo...

Classifying Red and Healthy Eyes using Deep Learning

Eye is one of the most vital organs of human body. Despite being small in size, humans cannot see the life around them without it. Human eye is protected by a thin covering termed as conjunctiva which protects the eye fr...

Constraint on Repair Resources, Optimal Number of Repairers and Optimal Size of a Serviced System

The focus of this paper is the analysis of the constraint on the repair resources caused by breakdowns of components in large systems. The study has been conducted by creating a very efficient discrete-event simulator, b...

original work is properly cited. Predicting Potential Banking Customer Churn using Apache Spark ML and MLlib Packages: A Comparative Study

This study was conducted based on an assumption that Spark ML package has much better performance and accuracy than Spark MLlib package in dealing with big data. The used dataset in the comparison is for bank customers t...

Finite Element Analysis based Optimization of Magnetic Adhesion Module for Concrete Wall Climbing Robot

Wall climbing robot can provide easier accessibility to tall structures for Non Destructive Testing (NDT) and improve working environments of human operators. However, existing adhesion mechanism for climbing robots such...

Download PDF file
  • EP ID EP150760
  • DOI -
  • Views 99
  • Downloads 0

How To Cite

Shaimaa Ezzat Salama, Mohamed I. Marie, Laila M. El-Fangary, Yehia K. Helmy (2012).  Web Anomaly Misuse Intrusion Detection Framework for SQL Injection Detection. International Journal of Advanced Computer Science & Applications, 3(3), 123-129. https://europub.co.uk/articles/-A-150760