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IoT is emerging as a massive web of heterogeneous networks estimated to interconnect over 41 billion devices by 2025, generating around 79 zettabytes of data. The heterogeneous network shall bring in a plethora of digital services leveraging cloud and communication technologies to drive smart city applications. As users access these services remotely in a ubiquitous environment over public channels, it becomes imperative to secure their communication. Both entity and message authentication emerge as a critical security primitive to thwart unauthorized access and prevent the falsification of messages. While researchers have given due attention to achieving mutual authentication between the subscriber (remote user) and gateway node (broker), the mutual authentication between the gateway node and an IoT sensor node is left to be desired. It could be done at the peril of a rogue or a shadow IoT device unauthorizedly joining an IoT-based network. Some of the widely used IoT-specific application layer protocols like constrained application protocol (COAP) and message queue telemetry transport (MQTT) protocol are not inherently equipped with adequate security safeguards. They, therefore, rely on underlying transport layer security protocols, which are highly computationally intensive. To address this issue, this paper proposes a three-factor authentication framework suitable for IoT-driven critical applications based upon identity, password and a digital signature scheme. The framework employs publish-subscribe pattern leveraging elliptical curve cryptography (ECC) and computationally low hash chains. The formal and informal security analysis shows that the framework is resistant to different types of cryptographic attacks. Furthermore, the automated validation performed with the Scyther tool verifies that there are no cryptographic attacks found on any of the claims stated in the proposed framework. Finally, a comparison of the framework security features, computational, and communication overheads is carried out with other existing protocols.

Digital technologies enable huge potential for cultivating healthcare access and quality globally, including in India. The Internet of Things (IoT) allows connection between devices and healthcare specialists, thus enhancing healthcare delivery with reduced overheads such as manual intervention, time consumption and administrative cost. However, the incorporation of IoT technology in the healthcare sector has experienced obstacles due to security issues. These concerns involve unauthorized access arising from vulnerabilities in open wireless channels and the limitations of device abilities, which may hamper the performance of complex security algorithms. Existing solutions often rely on conventional security algorithms that incur high computational overhead. Moreover, the inclusion of non-unique identifiers as authenticating parameters, makes them vulnerable to security attacks including replay attack, identity collisions etc. Furthermore, the current solutions fail to balance adequately between security and efficiency, thus leading to increased energy consumption. Therefore, to address these challenges, we propose a minimally intrusive authentication scheme that integrates the Ayushman Bharat Health Account (ABHA) number – a unique identifier, with Physical Unclonable Function (PUF), and Zero-Knowledge Proof (ZKP) as the authenticating parameters. The scheme prevents from several security attacks including replay attack, man-in-the-middle attack, impersonation and insider attack, eavesdropping and message modification attack, password guessing attack, DoS attack alongside it provides session key security as well . Further it undergoes a wide range of evaluation and validation using the “Automated Validation of Internet Security Protocols and Applications (AVISPA)” tool, providing convincing evidence of its resilience against security threats. Since the scheme exploits lightweight techniques such as PUF, message digest, and ZKP, thus it yields lower cost overhead compared to traditional methods. Upon comparison, the scheme presents an average of 99.14 ms for computation cost and 1248 bits of communication cost which is far lesser than most of the existing schemes. Therefore, the proposed scheme outperforms many of the existing protocols in terms of complexity, communication and computation cost and presents a comprehensive solution for e-healthcare security.

The dominance and prevalence of social media in the present world are significant because the role supplied by social networks is gradually growing with the passage of time. These social networks are often complicated networks in which each user is designated by a node and interactions between two users are symbolized by edges. People often express their opinions on any event via social media platforms. The interaction between users at a specific event, such as COVID-19, may constitute social synchrony, defined as a large population of users performing a specific action in unison. Identifying the seed users (influential users) from that event can be vital for a range of applications. Therefore, the current study proposes a framework to identify the seed users that works on the principles of graph analysis, viz. clustering, transitivity, and network centrality. Extensive experimentation is carried out using a self-collected dataset of COVID-19 tweets. Our dataset shows encouraging results in finding seed users in complicated networks.