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Journal of Mass Communication & Journalism

ISSN: 2165-7912

Open Access

An Exploratory Factor Analysis of AI Enabled SE Attacking Risk in Higher Learning Institute

Abstract

Khidzir NZ and Abdullah-Al-Musa Ahmed S

Any kind of business organization or individual organization one word is very common that is information. Depending on the information and its communication medium ensure the effective of business. Whereas it is very much essential to understanding Artificial Intelligence (AI) Enabled Social Engineering (SE) attacks and its security risk management approach. Under such circumstance, information is exchanged from one country to another country for various purposes. In that case, artificial intelligence enabled social engineering attack must be considered in any kind of organization. Any kind of business venture is disturbed by this kind of attacks which will be failure the business operation, whilst enabling them to concentrate on their core business activities. Social engineering is one kind of criminal activities in the information security. It has proven to be very successful way for a criminal to get inside an organization. Once social engineering got password from an employee, then snooping around the sensitive data. However social engineering are the types of attacks inherent risk and any kind of organization should be aware of its potential risks. So, it could be identify and resolved quickly. The objective of this article, therefore, conducting an Exploratory Factor Analysis (EFA) in artificial intelligence enabled social engineering attacks on various organizations. Which consequently provide knowledge of the most relevant information security risk factor. For this article distributed 300 questionnaires in education sector for the study and 110 were returned. That means the response rate is 36%. In that case, the finding of the article shows that threat and vulnerability factors in artificial intelligence enabled social engineering attacks. So, for any organization these two factors are the most
for information security risk. 

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