Face Recognition in the Context of Website Authentication
Mohamad Amir Dliwati, Dinesh Kumar · 2021 Asian Conference on Innovation in Technology (ASIANCON) · 2021
In 1995, developers and programmers have begun focusing on developing websites and data protection. This came as a result of the increase and growth of many digital services such as e-shopping services, bank account management, e-mails, and many other services that require a high level of protection and security. As the penetration internet gowned it throws many challenges towards information protection. Hence the importance of providing protection and security for websites and users to protect their data and privacy, and bearing in mind that authentication is the first and basic step to protect and encrypt information sources, it also provides a safe environment for Internet users, which gives them comfort and security when dealing with these sites. The idea of our research aims for developing a security system that combines some recognition algorithms based on machine learning and deep learning techniques to verify the identity of each user (authentication) for the website and all the services associated with it. Thus, we can achieve the highest level of protection and security from the digital gaps that hackers may exploit. Therefore, the facial expression became the most important technique to identify hackers. The obtained results reveal that deep learning-based techniques for face recognition over a collected dataset are superior to conventional machine learning techniques.