SCAMM: detection and prevention of SQL injection attacks using a machine learning approach

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

Dettagli Bibliografici
Autori principali:	Alam, Auninda, Tahreen, Marjan, Alam, Md Moin, Mohammad, Shahnewaz Ali, Rana, Shohag
Altri autori:	Hossain, Muhammad Iqbal
Natura:	Tesi
Lingua:	English
Pubblicazione:	Brac University 2021
Soggetti:	Machine Learning SQL Injection SCAMM Naive Bayes KNN Neural Network Classifier Random Forest Logistic Regression Machine learning
Accesso online:	http://hdl.handle.net/10361/15331

id	10361-15331
record_format	dspace
spelling	10361-153312022-01-26T10:04:54Z SCAMM: detection and prevention of SQL injection attacks using a machine learning approach Alam, Auninda Tahreen, Marjan Alam, Md Moin Mohammad, Shahnewaz Ali Rana, Shohag Hossain, Muhammad Iqbal Department of Computer Science and Engineering, Brac University Machine Learning SQL Injection SCAMM Naive Bayes KNN Neural Network Classifier Random Forest Logistic Regression Machine learning This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (pages 21-22). Importance of cyber-security in protecting our valuable data and information is huge in this era of technology. Since numerous amounts of cyber-attacks take place every day, the development of a more secured system so that it can predict and stop cyber-attacks from happening, has been our concern for years. This research paper is focused on developing such a means that will be able to detect and prevent SQL Injection Attack successfully. SQL Injection attack is a type of cyber-attack that uses malicious SQL queries for internal data manipulation and retrieving hidden information from the back-end database that were not intended to be displayed. SQL Injection Attack even makes a database vulnerable to other kinds of attacks. Since most of the organizations use a SQL based back end database to store data, all of their data is exposed to a simple form of attack if they are not properly defended. The aim of this research is to develop a model by finding out the best machine learning algorithm to predict and prevent SQL Injection Attack. A brief explanation of our work plan, our experimentation and the results of our experiments are discussed in this paper. Auninda Alam Marjan Tahreen Md Moin Alam Shahnewaz Ali Mohammad Shohag Rana B. Computer Science 2021-10-18T05:41:44Z 2021-10-18T05:41:44Z 2021 2021-01 Thesis ID 19241021 ID 19241020 ID 17101060 ID 19241014 ID 20141033 http://hdl.handle.net/10361/15331 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 22 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Machine Learning SQL Injection SCAMM Naive Bayes KNN Neural Network Classifier Random Forest Logistic Regression Machine learning
spellingShingle	Machine Learning SQL Injection SCAMM Naive Bayes KNN Neural Network Classifier Random Forest Logistic Regression Machine learning Alam, Auninda Tahreen, Marjan Alam, Md Moin Mohammad, Shahnewaz Ali Rana, Shohag SCAMM: detection and prevention of SQL injection attacks using a machine learning approach
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
author2	Hossain, Muhammad Iqbal
author_facet	Hossain, Muhammad Iqbal Alam, Auninda Tahreen, Marjan Alam, Md Moin Mohammad, Shahnewaz Ali Rana, Shohag
format	Thesis
author	Alam, Auninda Tahreen, Marjan Alam, Md Moin Mohammad, Shahnewaz Ali Rana, Shohag
author_sort	Alam, Auninda
title	SCAMM: detection and prevention of SQL injection attacks using a machine learning approach
title_short	SCAMM: detection and prevention of SQL injection attacks using a machine learning approach
title_full	SCAMM: detection and prevention of SQL injection attacks using a machine learning approach
title_fullStr	SCAMM: detection and prevention of SQL injection attacks using a machine learning approach
title_full_unstemmed	SCAMM: detection and prevention of SQL injection attacks using a machine learning approach
title_sort	scamm: detection and prevention of sql injection attacks using a machine learning approach
publisher	Brac University
publishDate	2021
url	http://hdl.handle.net/10361/15331
work_keys_str_mv	AT alamauninda scammdetectionandpreventionofsqlinjectionattacksusingamachinelearningapproach AT tahreenmarjan scammdetectionandpreventionofsqlinjectionattacksusingamachinelearningapproach AT alammdmoin scammdetectionandpreventionofsqlinjectionattacksusingamachinelearningapproach AT mohammadshahnewazali scammdetectionandpreventionofsqlinjectionattacksusingamachinelearningapproach AT ranashohag scammdetectionandpreventionofsqlinjectionattacksusingamachinelearningapproach
_version_	1814306993276452864

SCAMM: detection and prevention of SQL injection attacks using a machine learning approach

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