A Critical Analysis of Deepfake Detection Software: Emerging Challenges and Quality Assurance

Abstract

Deepfakes have proven their identity in the field of digital forensics. The article explains how Deepfakes create highly realistic but synthetic videos, images, and audio clips, which create doubt about whether they are real or fake. This article identifies some important tools and technologies. In every field of life, such as entertainment, education, and content writing, deepfakes help impose a sense of authenticity. Digital forensics investigation agencies, law enforcement officials, and offices are also concerned about day-to-day social engineering attacks, identity theft, and misinformation. Software Quality Assurance (SQA) and testing features of the deepfake forensic systems, including accuracy, reliability, security, robustness, scalability, and explainability. The discussion covers testing challenges, including dataset validation, performance evaluation, adversarial testing, and real-world scenario testing, to enhance the reliability of AI-driven forensic solutions.