1 research outputs found
LPTD: Achieving Lightweight and Privacy-Preserving Truth Discovery in CIoT
In recent years, cognitive Internet of Things (CIoT) has received
considerable attention because it can extract valuable information from various
Internet of Things (IoT) devices. In CIoT, truth discovery plays an important
role in identifying truthful values from large scale data to help CIoT provide
deeper insights and value from collected information. However, the privacy
concerns of IoT devices pose a major challenge in designing truth discovery
approaches. Although existing schemes of truth discovery can be executed with
strong privacy guarantees, they are not efficient or cannot be applied in
real-life CIoT applications. This article proposes a novel framework for
lightweight and privacy-preserving truth discovery called LPTD-I, which is
implemented by incorporating fog and cloud platforms, and adopting the
homomorphic Paillier encryption and one-way hash chain techniques. This scheme
not only protects devices' privacy, but also achieves high efficiency.
Moreover, we introduce a fault tolerant (LPTD-II) framework which can
effectively overcome malfunctioning CIoT devices. Detailed security analysis
indicates the proposed schemes are secure under a comprehensively designed
threat model. Experimental simulations are also carried out to demonstrate the
efficiency of the proposed schemes