Social Engineering Attack and Scam Detection Using Advanced Natural Langugae Processing Algorithm

Abstract

The Method of convincing anyone to share their knowledge is known as social engineering. Social engineers rely on people's ignorance of the consequence of sharing their valuable information, as well as their lack of knowledge for securing their systems and IT infrastructure from security attacks. These attacks may be carried out by the employees of an organization, through a third-party agency. They violate the rules of the organization for financial gain or revenge. The attacker uses different tactics to gather sensitive information of the victims, this itself is a method of social engineering attack. The process of gaining confidential information illegally is a criminal act. The proposed research study has developed a framework to find the message received from an unknown source or URL is a spam or legitimate by using natural language process (NLP). During COVID-19, many peoples started using Internet for their daily activities without the knowledge of security risks in Internet. This rise in the number of individuals using the Internet is virtually never accompanied by knowledge about cyber security and other forms of Internet based attacks. This attracted the attackers to target these victims and launch their attacks. SEA is a form of advanced cyber security attack, which use people's natural curiosity to break surveillance systems and have a high success rate. The goal of the study is to look at the details of how the COVID-19 pandemic has paved the way for an expansion of social engineering attacks, as well as various methods for detecting and mitigating these attacks. © 2022 IEEE.