Simon Atuah Asakipaam
Papers
2
Total Citations
16
H-Index
2
About
Simon Atuah Asakipaam is a researcher at the forefront of cybersecurity and intelligent systems, specializing in the intersection of machine learning, the Internet of Things (IoT), and cryptographic security. His work addresses critical vulnerabilities in modern infrastructure, particularly in health monitoring and industrial transmission systems. Asakipaam’s most cited paper, "Hybrid Encryption Method for Health Monitoring Systems Based on Machine Learning" (2022, 9 citations), pioneers a robust framework that combines machine learning with encryption to protect sensitive health data transmitted over vulnerable wireless sensor networks. His follow-up study, "Enhanced Secure Technique for Detecting Cyber Attacks Using Artificial Intelligence and Optimal IoT" (2022, 7 citations), advances real-time cyberattack detection by integrating AI-driven anomaly detection with optimal IoT configurations, reducing reliance on human intervention. These contributions are vital for securing remote monitoring systems against disasters, vandalism, and cyber threats. Asakipaam’s work demonstrates a clear impact on applied cybersecurity, offering scalable solutions for resilient, autonomous infrastructure. His research is particularly notable for bridging theoretical AI models with practical, real-world security challenges, making him a key voice in the evolving landscape of IoT safety and data integrity.
Research Focus
Key Achievements
Top Papers
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