CyberKids: A Video Game to Promote Cybersecurity Awareness Among Children

The Industrial Internet of Things (IIoT) has transformed industries with large-scale data accumulation and analysis capabilities. While increasing cloud storage-based dependency on IIoT data comes with its major security vulnerabilities and privacy issues, traditional methods of encryption grant privacy while being inefficient for processing and limiting access to control over the shares. For remediation, this work proposes SmartCrypt as an efficient, intelligent IIoT data sharing and storing scheme. SmartCrypt incorporates symmetric homomorphic encryption that facilitates computations over encrypted data without decryption and incurs low computation overhead. Furthermore, it makes use of fine-grained access control to secure the retrieval and processing of information by only qualified parties. Compared to traditional practices, SmartCrypt is privacy-preserving analytics-suitable, especially for time-series IIoT applications like predictive maintenance and anomaly detection. We measure the efficiency of the system with real-world datasets and prove that SmartCrypt enhances query response time by 17% and throughput by 9% against current techniques. These findings authenticate its capability in offering a secure, efficient, and scalable means of IIoT data management. With assurance of strong security without compromising on data utility, SmartCrypt provides a promising solution to addressing the twin challenges of privacy and accessibility in industrial data ecosystems.