A Detection Framework for SQL Injections and Cross Site Scripting

Vamsi Mohan V , Dr. Sandeep Malik

SQL Injections, Cross Site Scripting, Regression Neural Network, Static Analysis, Dynamic Analysis.

Designing secure web applications are most important aspect to avoid SQL injections and Cross Site Scripting (XSS) attacks. XSS vulnerabilities are classified into three types. i.e., Reflected XSS, Stored XSS and Dynamic XSS. From these types of XSS, DOM XSS is different from the two others. There are many researches and detection methods proposed for Reflected XSS and Stored XSS. However, it is not suitable for Dynamic XSS. Due to increase of web applications, the threats are getting increased. XSS often included in OWASP top-10 list from the last decade and hence an appropriate XSS detection method is necessary. In this paper, we propose a detection framework for SQLI and XSS. We introduced Regression Neural Network (RNN). It provides accurate and quick solution to regression, approximation, classification and fitting problems. RNN can be used in system identification of dynamic systems as well as control of dynamic systems. Here we are integrating multi-objective optimization which involves integration of objective formulation from dragon fly optimization (DA) and Genetic algorithm (G A). Integrating of optimization algorithm, crossover and mutation is used instead of alignment process of DA.

Published Paper   E-Certificate

"A Detection Framework for SQL Injections and Cross Site Scripting", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.4, Issue 1, page no.288 - 291, January-2019, Available :https://ijsdr.org/papers/IJSDR1901050.pdf

Volume 4 Issue 1, January-2019

Pages : 288 - 291

Paper Reg. ID: IJSDR_190051

Published Paper Id: IJSDR1901050

Downloads: 000347154

Research Area: Engineering

Country: Bangalore, Karnataka, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR1901050

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR1901050

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition