Social Engineering 2.0 Deepfake and Deep Learning-based Cyber-attacks (Phishing)

This research paper examines the emerging risk of deepfake phishing, or modern social engineering, where deep learning techniques are used to produce realistic fake media for cyberattacks. The paper investigates the topic of deepfakes: voice and video manipulation which have become widespread tools to mislead the target audiences and bring severe financial and organizational losses. The study relies on secondary sources and provides trend analysis, case and quantitative data to demonstrate increase in deepfake phishing attacks in the finance, healthcare and technology sectors. By considering sectoral data, the paper determines the biggest focused areas, which stated, finance and healthcare have the highest proportion of the financial damages. The present research also explores the development in the technology of deepfake and explains how the technology has improved the authenticity of fake videos and audio by providing examples of how these technologies have advanced from simple imitations to near-photorealistic replicas of real voices and faces. What consequences do have this progression for the rate of successful phishing attacks? The answer is quite serious – with this progression, the attackers can act more freely as they do not need to overcome conventional security barriers. Finally, the paper urges people to fight these risks using AI tools for time-independent deep fake detection, stricter guidelines and specific informative training for employees for such shiny attacks. Through exploring the current state of deepfake phishing as a threat, the work underscores the importance of continuing caution and development in cyber defence. The research indicates that to address the threats posed by deepfake phishing one needs to employ both, developed technological solutions and actively maintained organizational shields.