Automated Machine Learning Prototype for Detecting Phishing, Deepfakes, and Fraudulent Audio Patterns: A Systematic Literature Mapping
摘要
The pervasiveness of cybercrime poses a significant threat to individuals and organizations worldwide, particularly in the realm of audio-based interactions. To combat this evolving threat landscape, this study delves into the application of artificial intelligence (AI), specifically machine learning techniques [1], to develop a prototype for mitigating cybercrime [2]. The prototype aims to address emerging threats such as phishing, deepfakes [3], and social engineering [4], which exploit audio signals and compromise personal data and security.