Rohaya Latip

Abstract Recent advances in generative modeling have enabled the creation of highly realistic deepfake facial images, posing significant risks to digital security, media integrity, and public trust. Although deep learning–based detection methods have achieved strong performance, they often suffer from limited cross-dataset generalization, sensitivity to manipulation-specific artifacts, and reduced interpretability.

1. Introduction The cloud environment offers a platform that enables shared access to servers in a data center when clients make service requests. [1]. The three main elements of cloud computing architecture are infrastructure as a service (IaaS), software as a service (SaaS), and platform as a service (PaaS). SaaS makes it possible for customers, software vendors, and cloud service providers to work together.

Over the past decade, technology has rapidly evolved, significantly expanding its application. Traditional networks, with each application maintaining its own data center, led to high operational and maintenance costs. However, the revolution of cloud computing which infusing a data-centric computing paradigm has countered these issues. Cloud providers deliver on-demand and scalable services to their clients, in different locations, through variety of virtualized resources [1].