Detecting Deception with Emotion -The Role of Emotional AI in Combating Social Engineering Attacks by Stephen Mikah Makoshi

Detecting Deception with Emotion: The Role of Emotional AI in Combating Social Engineering AttacksAuthor: Stephen Mikah MakoshiDate: April 12, 2025Type: Copyrighted ManuscriptDetailed Description:This manuscript provides a comprehensive investigation into the integration of Emotional Artificial Intelligence (Emotional AI) into modern cybersecurity practices, with a focus on its potential to combat social engineering attacks. Unlike traditional cyber threats that exploit system vulnerabilities, social engineering targets the human psyche—manipulating users through tactics based on fear, trust, urgency, authority, and curiosity.Authored by Stephen Mikah Makoshi, the paper begins by unpacking the psychology behind social engineering and detailing the most prevalent attack techniques, including phishing, grooming, pretexting, and baiting. It emphasizes that human error continues to be the weakest link in cybersecurity despite the advancement of technical defenses, thereby underscoring the need for emotionally aware systems that can interpret and respond to human behavior.The core of the study introduces Emotional AI as an emerging, multidisciplinary approach that combines Natural Language Processing (NLP), computer vision, behavioral biometrics, and machine learning to assess emotional cues in real time. These cues—extracted from text, voice tone, facial expressions, and user interaction patterns—can be used to detect signs of manipulation or distress that precede a social engineering exploit.The paper outlines how Emotional AI can be applied across various domains within cybersecurity, including:Phishing email detection through sentiment and tone analysis.Voice and chatbot security by analyzing stress and urgency in conversations.Insider threat monitoring through behavioral and emotional baselining.Continuous real-time monitoring to flag deviations in user behavior tied to emotional shifts.Beyond its practical applications, the manuscript also explores the ethical, legal, and social implications of deploying Emotional AI. Issues such as emotional data privacy, informed consent, algorithmic bias, and compliance with global data protection regulations (e.g., GDPR, CCPA) are critically examined.To support real-world adoption, the paper presents a detailed implementation framework covering:Data collection and multimodal input analysisMachine learning model training and customizationIntegration with SIEM and behavioral analytics toolsEthical governance and compliance safeguardsPilot testing and continuous system improvementFinally, the manuscript concludes that Emotional AI is not a replacement for traditional cybersecurity systems, but a strategic augmentation—a tool that strengthens the "human firewall" by equipping systems with the emotional awareness necessary to detect and disrupt socially engineered cyber threats.