A flood of information is generated by Social Internet of Things (SIoT) through the combination of social networks and IoT technology, allowing different people to communicate differently than they have before. Information spreads rapidly and frequently in the real-time digital era, and thus, inaccurate or misleading content can also be spread. Proposing a context-aware, rule-engine-driven and proactive dissemination method for social network information based on real-time IoT data in this study. Therefore, IoT technology can be applied to regulate the spread of information and solve this problem. Only reliable and contextually appropriate data are provided to Context-Aware Dissemination by IoT and Rule Engine CADIRE model, which gives users control over when, how and with whom the information is shared on social media platforms. This will promote the sharing of content in a responsible and safe manner using intelligence. A rule-based IoT-driven dissemination classical is employed to collect real-time user context data through IoT devices and, based on this, establish the foundation of the methodology. Intelligently distribute based on context parameters such as location, time, device identity and user behaviour, and in doing so, avoid waiting to block or filter content after it has spread. Replace the old AES algorithm with ECC for encryption in the CADIRE model to boost security during transmission. ECC is more suitable for the limited processing power and energy in the Internet of Things environment; therefore, a low-overhead, high-security encryption algorithm is required. ECC can be employed to achieve high-performance, resource-limited devices while maintaining the confidentiality of social network messages end-to-end. Based on the above experiments, the proposed CADIRE prototypes have greatly improved the security, management and efficiency of information sharing in online social networks.
