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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | SQL Injection Vulnerabilities Prevention through ML IPAAS Architecture |
| Authors Name: | Vivek Thoutam |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_180770
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| Published Paper Id: | IJNRD2203104 |
| Published In: | Volume 7 Issue 3, March-2022 |
| DOI: | |
| Abstract: | XSS and SQL infusion vulnerabilities both show at a crucial level as an inability to safeguard the honesty of HTML reports and SQL inquiries, individually, within the sight of untrusted contribution to the web application. In the former case,an XSS vulnerability allows an attacker to inject dangerous HTML components, regularly including noxious customer side code that executes in the security setting of a confided in web root. In the last case, a SQL infusion injec-tion defenselessness enables an assailant to adjust a current database question — or, now and again, to infuse a totally new one — so that damages the web application's coveted information uprightness or classification strategies. IPAAS consequently and straightforwardly expands generally shaky web application improvement conditions within put validators that result in significant and tangible security improvements for real systems. We implemented IPAAS for PHP and assessed it on five genuine web applications with known XSS and SQL infusion vulnerabilities. Our assessment exhibits that IPAAS would have forestalled 83% of SQL infusion vulnerabilities and 65% of XSS vulnerabilities while causing no developerburden. This paper provides the SQL injection vulnerabilities prevention through ML IPAAS architecture. |
| Keywords: | Machine Learning, SQL, architecture |
| Cite Article: | "SQL Injection Vulnerabilities Prevention through ML IPAAS Architecture", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.7, Issue 3, page no.832-837, March-2022, Available :http://www.ijnrd.org/papers/IJNRD2203104.pdf |
| Downloads: | 000114656 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2203104 Registration ID: 180770 Published In: Volume 7 Issue 3, March-2022 DOI (Digital Object Identifier): Page No: 832-837 Country: -, -, - Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2203104 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2203104 |
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