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DC Field | Value | Language |
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dc.contributor.author | Variya, Yash | - |
dc.date.accessioned | 2022-11-15T06:50:13Z | - |
dc.date.available | 2022-11-15T06:50:13Z | - |
dc.date.issued | 2022-06-01 | - |
dc.identifier.uri | http://10.1.7.192:80/jspui/handle/123456789/11372 | - |
dc.description.abstract | The current world relies heavily on web applications. As a result, providing security to every web application is a huge challenge. In most cases, the information is already in the database on the back-end of the web application. The number of online platform hacks is growing daily as everything becomes digital. Hackers frequently target online database applications. One of the most common types of attacks is SQL injection. A malicious code is injected into the SQL query of the user by the attacker. As a result, they get access to the database and they can change the information. The internet is the most reliable and commonly utilized channel for communication and business activities in today’s modern world. Users load massive amounts of data onto the web every day through numerous means, and user input might be malicious. As a result, web application security getting more crucial. Because they are so easily available, they are vulnerable to a variety of flaws that, if ignored, can result in harm. Attackers use these weaknesses to get unauthorized access through a variety of illegal activities. The machine learning concept with the Support Vector Machine (SVM) algorithm was introduced to overcome the above-mentioned attacks. It is used to detect and prevent SQL injection queries. Attacks on the internet are increasing in number and severity on a regular basis. The massive amount of data available on the internet encourages hackers to attempt innovative attacks. The Structured Query Language is a most dangerous attack that targets web applications. Several studies work had been carried out to mitigate this assault both by stopping it from an early Level or detecting it whilst it happens. We present an overview of SQL Injection attacks in this paper, as well as a classification of the recently presented detection and prevention solutions. More and more persons are using computers in their daily lives in this planet. As a result, more data is stored. The core aspects of computer backups are recovery and storage. Unfortunately, data loss occurs for a variety of reasons, including accident deletion, software or hardware failure, and cybercrime-related actions. Every organization should have a solid security plan in place because a breach of security can cost a lot of money and risk embarrassing the company in the eyes of customers or clients. | en_US |
dc.publisher | Institute of Technology | en_US |
dc.relation.ispartofseries | 20MCEI14; | - |
dc.subject | Computer 2020 | en_US |
dc.subject | Project Report 2020 | en_US |
dc.subject | Computer Project Report | en_US |
dc.subject | Project Report | en_US |
dc.subject | 20MCEI | en_US |
dc.subject | 20MCEI14 | en_US |
dc.subject | INS | en_US |
dc.subject | INS 2020 | en_US |
dc.subject | CE (INS) | en_US |
dc.title | SQL Injection Attack Detection using Naive Bayes Classifier | en_US |
dc.type | Dissertation | en_US |
Appears in Collections: | Dissertation, CE (INS) |
Files in This Item:
File | Description | Size | Format | |
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20MCEI14.pdf | 20MCEI14 | 642.97 kB | Adobe PDF | ![]() View/Open |
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