With the development of cloud computing, privacy security issues have become increasingly
prominent, which is of concern to industry and academia. We review the research progress …

Abstract Location-based Social Networks (LBSNs) enable users to socialize with friends and
acquaintances by sharing their check-ins, opinions, photos, and reviews. A huge volume of …

The problem of information overload and the necessity for precise information retrieval has
led to the extensive use of recommendation systems (RS). However, ensuring the privacy of …

We investigate a privacy-preserving problem for point-of-interest (POI) recommendation
system for rapidly growing location-based social networks (LBSNs). The LBSN-based …

With the emergence of technology, there has been a high influx of information over social
networks. Cybersecurity is thus the need of the hour. The crux of cybersecurity is network …

To solve the privacy image problem stored in cloud, we propose a compressive sensing
(CS) based image compression, authentication, encryption algorithm in cloud, which can …

Point of interest (POI) recommendation can benefit users and merchants. It is a very
important and popular service in modern life. In this paper, we aim to study the next new POI …

Next Point-of-Interest (POI) recommendation aims to predict the next POI for users from their
historical activities. Existing methods typically rely on location-level POI check-in trajectories …

The problem of information overload on the Internet increased the need for personalized
information retrieval (PIR) systems capable of providing information that corresponds to the …

Context-aware recommendation systems are of increasing popularity in the digital era to
recommend personalized items to users. However, how to ensure user data privacy while …