@article{Article_63,

title = {A New Approach in Diagnosing and Preventing SQLIA with Large Language Models (LLMs)},

journal = {Communications in Combinatorics, Cryptography & Computer Science},

volume = {2023},

issue = {2},

issn = { 2783-5456 },

year = {2023},

url = {http://cccs.sgh.ac.ir/Articles/2023/issue 2/2-3-ANewApproachinDiagnosing.pdf},

author = {Amin Rezanejad and Amir Seyed Danesh and and Farid Feyzi},

keywords = {SQL injection attack; large language models; Natural Language Processing; database security; software vulnerability.},

abstract = {SQL injection attack is considered to be one of the most important and common methods of intrusion into databases. The current research was conducted with the aim of improving the security of databases and web applications by relying on artificial intelligence (AI) and natural language processing (NLP). According to the research done in the past, to detect and prevent SQL injection attacks, we will present a new approach using natural language processing (NLP) approaches such as large language models (LLMs), which has the ability to reduce the database vulnerabilities and neutralize SQL Injection attacks.}

};