Information-centric trust management for big data-enabled IoT

Abstract

Trust management (TM) plays a significant role in big data-enabled Internet of Things (IoT) for trustworthy data mining and fusion operations. It helps to deal with uncertainty and risk when users engage in an increased consumption of IoT services and applications. However, big data-enabled IoT has introduced newer challenges for TM. These challenges are due to the information-centric nature of the IoT rather than the trivial device-centric nature of legacy networks. Given the heterogeneous nature of IoT systems, this has initiated a new debate on ways to manage trust for big data-enabled IoT in a holistic context-dependent way with greater interoperability. From a user's perspective, a fully acceptable IoT-based analytics must be a trustworthy system that offers a range of competent context-aware services, along with effective security and privacy for its personalized data. Focused on this discussion, this chapter first tends to offer the reader with a general understanding of definitions, objectives and necessity of trust. Then it aims to identify the trust requirements of big data-enabled IoT systems such as interoperability, security, privacy, identity and policy requirements. Afterwards, along with an overview of information-centric trusted systems, it discusses the state-of-the-art frameworks, models and methods for information-centric TM in big data-enabled IoT systems and also tries to identify the future trends and open challenges in these areas.