Efficient cryptographic algorithms for enhancing patient data privacy in medical IoT systems

Despite the development of Medical Internet of Things (IoT) systems has completely changed the way healthcare is delivered, patient data security and privacy are still major worries. In this work, we suggest a new method to improve patient data privacy by integrating light cryptographic algorithms. AES-128 encryption efficiency and CBC-MAC (CCM) authentication integrity assurance are combined in our proposed hybrid algorithm. With reference to several performance metrics including encryption and decryption speeds, key size, memory footprint, communication overhead, security strength, and energy consumption, we assess this hybrid approach in comparison to two conventional lightweight cryptographic techniques, ChaCha20-Poly1305 and Elliptic Curve Cryptography (ECC). We show by thorough analysis and comparison how well our hybrid approach protects data robustly while minimizing resource limitations that are typical in medical IoT settings. Our results emphasize how important specialized cryptographic solutions are to protect patient privacy in networked healthcare systems.