Analytical Approach for Mitigating Phishing Attempts

As individuals and organizations become more connected, phishing attacks become more and more threatening, with increasingly sophisticated ways to trick users into giving sensitive data. In response, researchers have developed various theoretical frameworks for recognizing and mitigating the risks of phishing attempts. In this study, we review and compare several such frameworks, including cognitive, social, and technical approaches, and propose, develop, and implement a method to protect from phishing attempts by conducting an analysis of phishing attempts approach. In this research, we design and develop an application that verifies the safety of uniform resource locators (URLs) contained in messages before getting access into the received link, to protect users from potential threats such as data theft, malware infections, and privacy violations. A comprehensive review of the literature on online security and URL link verification will be conducted, and the developed algorithm will be tested and evaluated using several metrics. We will consider the use of machine and deep learning algorithms to apply our need and collect data that can be used in future machine learning training. The study will also consider the constraints of time, resources, and data privacy regulations while developing the solution. The ultimate goal is to deliver a high-quality and reliable solution that can make online communication safer for everyone.