Location-based services (LBSs) are useful for many applications in internet of things(IoT). However, LBSs has raised serious concerns about users' location privacy. In this paper, we propose a new location privacy attack in LBSs called hidden location inference attack, in which the adversary infers users' hidden locations based on the users' check-in histories. We discover three factors that influence individual check-in behaviors: geographic information, human mobility patterns and user preferences. We first separately evaluate the effects of each of these three factors on users' check-in behaviors. Next, we propose a novel algorithm that integrates the above heterogeneous factors and captures the probability of hidden location privacy leakage. Then, we design a novel privacy alert framework to warn users when their sharing behavior does not match their sharing rules. Finally, we use our experimental results to demonstrate the validity and practicality of the proposed strategy.

This work presents novel technical and legal approaches that address privacy concerns for personal data in RFID systems. In recent years, to minimize the conflict between convenience and the privacy risk of RFID systems, organizations have been requested to disclose their policies regarding RFID activities, obtain customer consent, and adopt appropriate mechanisms to enforce these policies. However, current research on RFID typically focuses on enforcement mechanisms to protect personal data stored in RFID tags and prevent organizations from tracking user activity through information emitted by specific RFID tags. A missing piece is how organizations can obtain customers' consent efficiently and flexibly. This study recommends that organizations obtain licenses automatically or semi-automatically before collecting personal data via RFID technologies rather than deal with written consents. Such digitalized and standard licenses can be checked automatically to ensure that collection and use of personal data is based on user consent. While individuals can easily control who has licenses and license content, the proposed framework provides an efficient and flexible way to overcome the deficiencies in current privacy protection technologies for RFID systems.