Enhancing Mobile Security Through Haptic Feedback: A Multi-Participant Investigation into Mitigating Social Engineering Attacks on Android Devices (Published)
Social engineering attacks, particularly SMS phishing (SMiShing), continue to exploit human vulnerabilities and pose substantial risks to mobile users. This study investigated the effectiveness of a haptic feedback system integrated within an Android application designed to detect and mitigate social engineering threats on mobile devices. Building on original experimentation, this study evaluates the system’s usability and impact by incorporating qualitative and quantitative data from twelve participants of varied demographics, selected for their relevance to social engineering susceptibility. Through interviews and controlled usage, the app demonstrated a detection accuracy of 91.89%, a 3.00% false positive rate, and an average response time of five seconds. Participants reported increased awareness, improved reaction times, and greater confidence in handling suspicious messages. This paper contributes to the human-centred cybersecurity domain by validating the integration of tactile feedback as a viable intervention against deception-based attacks. The study supports the hypothesis that haptic interaction fosters user attentiveness and proactive threat response, offering practical insights for future mobile security innovations.
Keywords: Android Application, Phishing, SMS threat detection, haptic feedback, mobile security, social engineering, usability study
The Evolution of Social Engineering: New Threats in the Age of Generative AI (Published)
This article examines the rapidly evolving landscape of social engineering threats in the age of Generative Artificial Intelligence and deepfake technologies. Traditional social engineering attacks have relied on exploiting human psychology through deception, but the integration of advanced AI capabilities has transformed these threats into significantly more sophisticated and difficult-to-detect attacks. It explores how GenAI systems can now produce highly convincing content that mimics human communication patterns, while deepfake technology enables realistic audio and video manipulation that can fool both humans and automated detection systems. The article analyzes emerging threat vectors including hyper-personalized phishing, AI-enhanced voice fraud, synthetic identity deception, multi-channel orchestrated attacks, and automated reconnaissance. These advancements have profound implications for businesses, society, and national security, necessitating a comprehensive defensive approach that combines technical countermeasures, organizational strategies, and regulatory frameworks. By documenting both the evolution of these threats and potential defensive measures, this research aims to contribute to the development of more effective protection against increasingly sophisticated social engineering attacks in the digital age.
Keywords: Cybersecurity, deepfake technology, digital deception, generative AI, social engineering