Linguistics for Crimes in the World by AI-Based Cyber Security

Effective communication and comprehension of cyber threats in varied linguistic contexts are crucial for robust defense mechanisms in the ever-changing global cybersecurity scene. This study centers on incorporating language processing and translation technologies into advanced artificial intelligence (AI)-based cybersecurity frameworks to improve the identification and handling of cyber crimes worldwide. The frequency of cyber-attacks is steadily increasing due to the various types of online transactions, such as internet banking and shopping. Web applications are vulnerable to numerous types of attacks, such as Cross Site Scripting (XSS) and Structured Query Language (SQL) injection attacks, among others. SQL injection is a significant threat to web applications, as it allows attackers to manipulate the backend database through the server. Meanwhile, artificial intelligence (AI) and deep learning algorithms are commonly employed to detect or address various online security concerns. This paper presents various AI algorithms and compares them to determine the most optimal one.