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About

Sultan Basudan is a leading researcher at the intersection of cybersecurity, the Internet of Medical Robotic Things (IoMRT), and federated learning. His work focuses on securing sensitive data in next-generation healthcare systems, particularly where robotic devices and AI converge. Basudan’s most-cited paper, “A puncturable attribute-based data sharing scheme for the Internet of Medical Robotic Things” (2021, 12 citations), introduces a novel cryptographic approach to enable fine-grained, revocable data access for medical robots—a critical advance for patient privacy. He further explores secure telemedicine in “IPFS-blockchain-based delegation model for internet of medical robotics things telesurgery system” (2024, 7 citations), proposing a decentralized framework to ensure integrity and trust in remote surgical procedures. His 2022 work on network security in the Internet of Robotic Things (9 citations) addresses vulnerabilities in robot-to-robot communication, while his 2024 study on “Trustworthy federated learning model for the internet of robotic things” (3 citations) pioneers privacy-preserving collaborative learning across robotic networks. With a consistent focus on real-world medical applications, Basudan’s research is shaping the secure deployment of autonomous systems in healthcare, earning recognition for bridging theoretical cryptography with practical IoRT challenges.