Privacy in the Internet of Things

Sensory data has become an indispensable component in wide variety of applications, including manufacturing, marketing, healthcare, transportation, entertainment, environmental monitoring, indoor localization, and traffic monitoring, and will continue to play an even more pivotal role in the near future. Unfortunately, conventional privacy protection methodologies are mainly for small-scale or isomorphic data, and they are not effective or efficient for big sensory data. [...]corresponding privacy protection technologies and tools are eagerly expected so that people can enjoy the benefits of sensory data with privacy being preserved anytime and anywhere. The work in the paper titled “A Location Prediction-Based Helper Selection Scheme for Suspicious Eavesdroppers” aims to improve security performance of data transmission by a mobile eavesdropper in a wireless network.