Evaluating Deepfake Applications in Biometric Technology – A Review

Abstract

Purpose: This paper aims to comprehensively evaluate the impact of deepfake applications on biometric technologies by utilizing the Theories, Contexts, Characteristics, and Methodologies (TCCM) framework. The objective is to identify and analyze the vulnerabilities, threats, and opportunities posed by deepfake technologies to enhance the understanding and security of biometric systems.

Methodology: The research follows a systematic review of literature with the TCCM framework. Various academic sources through scopus database are analysed to obtain data regarding the intersection of deepfake technologies and biometric systems. The research focuses on analyzing the theoretical underpinnings, contextual applications, distinctive characteristics, and methodologies for detection and prevention.

Findings/Results: The review reveals that deepfake technologies pose significant threats to the integrity and reliability of biometric systems. Key findings highlight the potential of deepfakes to manipulate biometric data, leading to privacy breaches and security vulnerabilities. The study also identifies advancements in detection and prevention technologies, emphasizing the necessity for reliable security measures and ethical guidelines to mitigate risks.

Originality/Value: This review provides a novel application of the TCCM framework in regard to deepfake and biometric technologies, offering a complete analysis of current challenges and future directions. The study’s findings are vital for researchers, practitioners, and policymakers seeking to understand and address the implications of deepfake technologies on biometric systems, ensuring the development of more secure and reliable biometric applications.

Paper Type: Review Paper.