Security Framework for Social Internet of Things: A Relativity Strength Approach

Security Framework for Social Internet of Things: A Relativity Strength Approach

Автор: K.S. Santhosh Kumar, Hanumanthappa J., S.P. Shiva Prakash, Kirill Krinkin

Журнал: International Journal of Information Engineering and Electronic Business @ijieeb

Статья в выпуске: 4 vol.16, 2024 года.

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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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Security, Relative strength, Social Internet of Things, Decision Tree, Reinforcement Learning, Attacks

Короткий адрес: https://sciup.org/15019424

IDR: 15019424   |   DOI: 10.5815/ijieeb.2024.04.03

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