Real-Time Cross Data Auto Evaluation System for Enhancing Security and Privacy in the Internet of Things

Abstract

Even though the rapid expansion of the Internet of Things (IoT) has led to significant advancements in a number of industries, security and privacy are still top priorities. Traditional security solutions are often ineffective due to the diversity of IoT devices and their resource limitations. This research proposes the Real-Time Cross-Data Auto Evaluation System (RTCDAES) to enhance security and privacy in IoT ecosystems. The solution swiftly detects and removes security threats by utilizing cross-data analysis from several IoT devices. Furthermore, the RTCDAES ensures privacy protection by implementing secure data signal transmission and storage techniques and lowering the likelihood of data leakage and unauthorized access. The proposed system significantly improves the overall security posture of IoT networks, provides a scalable and dependable solution for real-world applications, and demonstrates high accuracy and efficiency in threat detection.