Psychological Mechanisms in Social Engineering Attacks

EasyChair Preprint no. 13835

Abstract

Social engineering attacks exploit human psychology to manipulate individuals into divulging confidential information or performing actions that compromise security. This research explores the psychological mechanisms underlying social engineering attacks, aiming to identify key factors that contribute to their effectiveness. The study synthesizes findings from cognitive psychology, behavioral science, and cybersecurity to provide a comprehensive understanding of the cognitive biases, emotional triggers, and social influences that facilitate these attacks.

Introduction: Social engineering attacks are a significant threat in the cybersecurity landscape, leveraging psychological manipulation rather than technical exploits. Understanding the psychological mechanisms at play is crucial for developing effective countermeasures. This research addresses the gap in literature concerning the intersection of psychology and social engineering by examining how attackers exploit cognitive biases, emotional states, and social dynamics to deceive targets.

Methods: The study employs a mixed-methods approach, including a systematic literature review, experimental simulations, and qualitative interviews with cybersecurity professionals and individuals who have experienced social engineering attacks. The literature review covers existing theories and models of social engineering, while experimental simulations recreate common attack scenarios to observe real-time responses. Qualitative interviews provide insights into personal experiences and professional perspectives on the psychological manipulation tactics used in these attacks.

Keyphrases: cognitive biases, Cybersecurity, Deception, emotional manipulation, Human Factors, psychological mechanisms, social dynamics, Social Engineering, Trust

@Booklet{EasyChair:13835,
  author = {John Owen},
  title = {Psychological Mechanisms in Social Engineering Attacks},
  howpublished = {EasyChair Preprint no. 13835},

  year = {EasyChair, 2024}}