Work place: Department of Studies in Computer Science, University of Mysore, Manasagangothri campus, Mysuru-570006, Karnataka, India
E-mail: santhosh@compsci-uni.mysore.ac.in
Website:
Research Interests:
Biography
K. S. Santhosh Kumar, presently a Research Scholar actively pursuing a Ph.D. in Computer Science and Application within the Department of Studies in Computer Science at the Manasagangothri campus of the University of Mysore, Mysuru and achieved an M. Tech. in Software Engineering from the Department of Information Science and Engineering at Sri Jayachamarajendra College of Engineering, Mysuru, Karnataka, India, in 2016. Demonstrating an impressive publication record, he has filed three Indian patent requests and authored more than 5 research papers, all of which have been accepted and published in peer-reviewed national and international journals and conferences.
By K. S. Santhosh Kumar Hanumanthappa J. S. P. Shiva Prakash Kirill Krinkin
DOI: https://doi.org/10.5815/ijieeb.2024.04.03, Pub. Date: 8 Aug. 2024
The evolution of the Internet of Things (IoT) into the Social Internet of Things (SIoT) involves the integration of social networking features into smart devices. In this paradigm, smart devices emulate human social behavior by forming social relationships with other devices within the network. These relationships are leveraged for service discovery, emphasizing the need for robust security to foster collaboration and cooperation among devices. Security is paramount in the SIoT landscape, as malicious messages from devices can disrupt service functionality, impacting service quality and reliability. These challenges are particularly pronounced in social networks, introducing unique considerations such as heterogeneity and navigability. This study introduces a Security Framework for the Social Internet of Things, adopting a Relativity Strength Approach to enhance the security and reliability of IoT devices within social network contexts. The framework incorporates a relativity-based security model, utilizes Q-learning for efficient device navigation, and employs decision tree classification for assessing service availability. By optimizing hop counts and considering the strength of relationships between devices, the framework enhances security, resource utilization, and service reliability. The proposed security framework introduces a” Relationship key” derived from device-to-device relationships as a central element. This key, coupled with a standard 256-bit Advanced Encryption Standard (AES) algorithm, is employed for encryption and decryption processes. The relationship key technique ensures data protection during transmission, guaranteeing confidentiality and service integrity during network navigation. The system demonstrates an overall security effectiveness of 88.75%, showcasing its robustness in thwarting attacks and preventing unauthorized access. With an impressive overall communication efficiency of 91.75%, the framework minimizes errors and delays, facilitating optimal information trans- mission in smart environments. Furthermore, its 97.5% overall service availability assures a continuous and reliable user experience, establishing the framework’s capability to deliver secure, efficient, and highly accessible smart services.
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