Modeling Data, Information and Knowledge for Security Protection of Hybrid IoT and Edge Resources

• Main Authors: Yucong Duan, Xiaobing Sun, Haoyang Che, Chunjie Cao, Zhao Li, Xiaoxian Yang
• Format: Article
• Language: English
• Published: IEEE 2019-01-01
• Series: IEEE Access
• Subjects: Knowledge graph; security protection; typed resources; edge computing
• Online Access: https://ieeexplore.ieee.org/document/8776603/

Currently, with the growth of the Internet of Things devices and the emergence of massive edge resources, security protection content has not only empowered IoT devices with the accumulation of networked computing and storage as a flexible whole but also enabled storing, transferring and processing DIKW (data, information, knowledge, and wisdom) content at the edge of the network from multiple devices in a mobile manner. However, understanding various DIKW content or resources poses a conceptual challenge in unifying the semantics of the core concepts as a starting point. Through building metamodels of the DIKW framework, we propose to cognitively formalize the semantics of the key elements of the DIKW in a conceptual process. The formalization centers on modeling the perceived world only by relationships or semantics as the prime atomic comprising elements. Based on this cognitive world model, we reveal the difference between relationships and entities during the conceptualization process as a foundation for distinguishing data and information. Thereafter, we show the initial case for using this formalization to construct security protection solutions for edge computing scenarios centering on type conversions among typed resources formalized through our proposed formalization of the DIKW.