Digital Deception - Generative Artificial Intelligence in Social Engineering and Phishing

The paper: http://arxiv.org/abs/2310.13715

## Purpose 
This paper by Marc Schmitt and Ivan Flechais investigates the transformative role of [[Generative AI]] in [[Social Engineering (SE)]] and [[Phishing]] attacks. It aims to deepen understanding of the risks, human implications, and countermeasures associated with AI-driven SE attacks, contributing to more secure human-computer interactions.

## Methods 
- Systematic literature review of social engineering and AI capabilities.
- Analysis of AI technologies, focusing on Generative AI.
- Identification of three primary pillars exacerbating the impact of SE attacks: Realistic Content Creation, Advanced Targeting and Personalization, and Automated Attack Infrastructure.
- Development of a conceptual framework: the "Generative AI Social Engineering Framework."
- Application of the framework to investigate the impact of generative AI on phishing attacks and identify countermeasures.

## Key Findings 
1. Generative AI significantly amplifies the effectiveness of SE attacks through realistic content creation, including text, images, voice, and videos.
2. Advanced targeting and personalization capabilities of AI enable highly tailored phishing campaigns, increasing their success rate.
3. The use of AI in automated attack infrastructures allows large-scale, sophisticated phishing campaigns with minimal human involvement.
4. Generative AI poses a dual threat: while it can be used for defensive purposes, its misuse for malicious activities is a significant concern.
5. Current countermeasures, particularly user awareness and education, are inadequate against the evolving sophistication of AI-driven attacks.

## Discussion 
This research is crucial in understanding the growing threat posed by AI in cybersecurity. It highlights the urgent need for advanced defensive strategies and technologies to combat these AI-enhanced threats.

## Critiques 
1. The paper could explore more in-depth the ethical implications of Generative AI in cybersecurity.
2. A more detailed discussion on the technical aspects of AI-driven attacks and their detection might strengthen the research.
3. While the framework developed is comprehensive, real-world application and validation studies could further solidify its effectiveness.

## Tags
#GenerativeAI #SocialEngineering #Phishing #Cybersecurity #AIethics #AIthreats.