GENERATIVE AI RESEARCH ANALYSIS
Phishing Attacks in the Age of Generative Artificial Intelligence: A Systematic Review of Human Factors
This systematic review analyzes the growing threat of phishing attacks, particularly with the advent of Generative AI (GenAI). It highlights how cybercriminals exploit human vulnerabilities, such as lack of training, cognitive biases (System 1 thinking, authority bias), and external influences (workplace culture). GenAI significantly escalates these risks by enabling highly personalized, sophisticated attacks (deepfakes, voice mimicry, tailored messages) that bypass traditional defenses. The paper proposes human-centered solutions like advanced interactive training programs and technological countermeasures including AI/ML-driven detection systems and Explainable AI for transparency. The research emphasizes a holistic approach to cybersecurity, combining technological advancements with a deep understanding of human factors to build secure digital interactions against evolving AI-powered threats.
Key Takeaways:
- GenAI significantly amplifies phishing attack sophistication and personalization.
- Human factors (bias, neglect, lack of training) are critical vulnerabilities exploited by attackers.
- Traditional cybersecurity training is often insufficient against GenAI-driven attacks.
- Holistic solutions require combining advanced AI/ML defense with human-centered strategies.
- Understanding cognitive biases and external influences is key to effective countermeasures.
Key Enterprise Impact Metrics
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Financial Losses (AUD) in Jan 2025
Source: Australian Government's scam watcher
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Cybercrime Reports (AUD) in 2023-2024
Source: Australian Signals Directorate (ASD)
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UK Businesses Affected by Phishing
Source: UK Government Cybersecurity Breaches Survey, 2024
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Human Factors in Phishing
This section delves into the intrinsic human vulnerabilities that attackers exploit, including psychological traits, cognitive biases, and lack of awareness, as identified in Section 4.1.
GenAI's Role in Attacks
Explores how Generative AI transforms phishing, making attacks more sophisticated, personalized, and difficult to detect, as detailed in Section 4.2.
Solutions & Countermeasures
Presents a dual approach of human-centred and technology-driven solutions to combat advanced phishing threats, as discussed in Section 4.3.
472%
Increase in Financial Losses 2021-2022 due to Phishing (Australia)
Holistic View of Human Behavior Factors
Character
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Personality
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Experience
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Biological
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Organizational Culture
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Social Norm
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Training
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System Design
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Unforeseen Incidents
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The PEST (Phishing Email Suspicion Test)
The Phishing Email Suspicion Test (PEST) is a lab-based task evaluating cognitive mechanisms of phishing detection (Hakim et al., 2021). It helps identify how individuals react to phishing attempts and provides insights into factors like digital literacy, critical thinking, and emotional reactivity. Its findings are crucial for developing targeted training programs.
Advanced ROI Calculator
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Estimated Annual Savings
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Hours Reclaimed Annually
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Implementation Roadmap
A phased approach to integrating advanced AI cybersecurity, ensuring a smooth transition and maximum impact.
Phase 1: Current State Assessment & Strategy
Conduct a comprehensive audit of existing cybersecurity measures, identify human factor vulnerabilities, and define an AI-driven security strategy tailored to your organization.
Phase 2: Pilot AI Solution & Training Development
Implement a pilot AI/ML-driven detection system. Develop interactive, GenAI-aware cybersecurity training modules focusing on cognitive biases and advanced phishing recognition.
Phase 3: Full-Scale Deployment & Continuous Improvement
Roll out AI defence systems across the enterprise. Establish a continuous feedback loop for training, threat intelligence, and AI model refinement against evolving GenAI attack vectors.
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