Phishing

Purpose: Electronic Tourism is one of the important components of expanding Tourism by synchronizing this industry with information technology. It has not been long since its emergence. Methodology: this field is a combination of tourism and information technology that is one of the most common types of income-generating businesses which is producing job opportunities in the modern world. The advancement of science alongside communication and information technologies presented many opportunities and threats to this field due to tech such as smartphones and sensors, virtual and augmented reality tools, NFC, RFID, etc. Findings: The disclosure of the tourists' information and the possible abuse of it is one such threat. Therefore privacy and non-disclosure of information should be important factors. Recognition of reputable sites is an important factor in solving this problem. In this study, we have presented a model for recognizing fake and phishing sites which use the CFS+PSO and a combination of Info+Ranger alongside their results to reduce the test dataset features so that it could present a model for categorizing and higher accuracy in recognizing phishing sites by using the Multilayer Perceptron method. The proposed model was successful in recognizing 95.5% of phishing sites. Counclusion: The effect of information technology on the tourism industry and the usage of internet websites for selling and providing tourism services to tourists have created new security challenges. Protecting the privacy and personal information of people and tourists is one of these challenges and the disclosure of such information could lead to abuse by unqualified people and dissatisfaction and distrust of such systems.

This paper provides a comprehensive overview of the evolving Artificial Intelligence (AI) threat to cybersecurity, emphasizing the urgent need for finance leaders and cybersecurity professionals to adapt their strategies and controls to effectively combat AI-powered scams and cyber-attacks. The study delves into the specific ways in which AI is being used maliciously in cybercrime, such as enhanced phishing and Business Email Compromise (BEC) attacks, the creation of synthetic media including deepfakes, targeted attacks, automated attack strategies, and the availability of black-market AI tools on the dark web. Furthermore, it highlights the critical need for enhanced cybersecurity strategies and international cooperation to combat cyber threats effectively. The findings of this study provide valuable insights for finance leaders, cybersecurity professionals, policymakers, and researchers in understanding and addressing the challenges posed by generative AI in the cyber threat landscape.