In the dynamic realm of Smart Healthcare Systems (SHS), the integration of IoT devices has revolutionized conventional practices, ushering in an era of real-time data collection and seamless communication across the healthcare ecosystem. Amidst this technological shift, the paramount concern remains the security of sensitive healthcare data within intricate networks. Several cryptographic algorithms have been proposed for smart healthcare systems for the protection of critical and sensitive data in SHS, however, the majority of newly proposed algorithms have shortcomings in terms of resource utilization and the level of security that they provide. Our research delves into the existing highly secure cryptographic algorithms and provides a comparative analysis of two popular and secure cryptographic algorithms viz N-th Degree Truncated Polynomial Ring (NTRU) and Elliptic Curve Cryptography (ECC) and verifies their applicability in SHS. Recognizing ECC's compact key sizes and its vulnerability to quantum computing threats, our study finds NTRU as a resilient and quantum-resistant alternative, providing a robust defense mechanism in the evolving landscape of healthcare cybersecurity. Key findings underscore the efficacy of NTRU in safeguarding healthcare data, emphasizing its superior performance compared to ECC, especially in the face of emerging quantum computing challenges. The comparative analysis depicts that ECC excels in key generation speed, delivering efficient and swift key creation. However, it requires larger keys to withstand potential quantum computing vulnerabilities. On the other hand, the key generation time in NTRU is slightly more than ECC but being quantum-resistant, it provides high security.

Cloud of Things (CoT) relates to the convergence between Cloud Computing (CC) and the Internet of Things (IoT) and has significantly transformed the way services are delivered in the ubiquitous realm of devices. This integration has become essential because of the huge data being generated by IoT devices, requiring an infrastructure for storage and processing. Such infrastructure is provided by Cloud Computing services with massive space for data storage and exceptional platform to process complex data. IoT networks are vulnerable to multiple security breaches because of the growing usage of IoT devices in user personal systems. This leads to security and privacy threats that need to be addressed. IoT consists of resource limited devices which have feeble computing power, battery source and storage capacity. This paper addresses security issue by proposing usage of obfuscation and encryption techniques to scramble the data at IoT devices which is later on stored in encrypted form at the cloud server. The data at IoT devices is classified into highly critical or less critical and accordingly the appropriate technique between encryption and obfuscation is applied. The proposed mechanism is evaluated in terms of processing time for cryptographic operations at IoT devices. Evaluation results depict that the proposed mechanism is 1.17 times faster than [22] in terms of encryption and decryption times.

Due to increased number of IoT devices, the marketplace is showing significant growth of sensor deployments around the world. The context involved in any IoT environment needs proper storage, processing and interpretation to get deeper insights from it. Previous research has not focussed much on context-ware security in IoT environment and has primarily relied on context-ware computing methods. In this research paper we implement logical decisions among IoT nodes in healthcare system using ontological approach. With the help of ontological method collected data is transferred between various healthcare devices to the knowledge base thereby achieving security of context like patient data by providing deeper insights, so as to generate intelligent suggested solutions. Incorporation of context-aware rules based on common experience for specific healthcare scenario is done to get implicit insight among IoT nodes.  This work designs security ontology using Security Toolbox: Attacks & Countermeasures (STAC) framework that is implemented in Protégé 5. Moreover, Pellet (Incremental) reasoned is used to evaluate the ontology. Emergency ontology that can prove helpful at emergency times has also been designed.  Different parameters addressed in this work are authentication, access-control, authorization and privacy using context-awareness methodology that can enable naive users make informed security decision.