Related papers: A Clustering-based Location Privacy Protection Sch…
With the advent of mobile computing, location-based services have recently gained popularity. Many applications use the location provenance of users, i.e., the chronological history of the users' location for purposes ranging from access…
Concerns about data privacy are omnipresent, given the increasing usage of digital applications and their underlying business model that includes selling user data. Location data is particularly sensitive since they allow us to infer…
Huge volume of data from domain specific applications such as medical, financial, library, telephone, shopping records and individual are regularly generated. Sharing of these data is proved to be beneficial for data mining application. On…
Smart devices have accentuated the importance of geolocation information. Geolocation identification using smart devices has paved the path for incentive-based location-based services (LBS). A location proof is a digital certificate of the…
With the increasing importance of data privacy protection, various privacy-preserving machine learning methods have been proposed. In the clustering domain, various algorithms with a federated learning framework (i.e., federated clustering)…
We present a new algorithm for locating a small cluster of points with differential privacy [Dwork, McSherry, Nissim, and Smith, 2006]. Our algorithm has implications to private data exploration, clustering, and removal of outliers.…
The advent of smartphones in recent years has changed the wireless landscape. Smartphones have become a platform for online user interface to cloud databases. Cloud databases may provide a large set of user-private and sensitive data (i.e.,…
This paper studies the problem of clustering in metric spaces while preserving the privacy of individual data. Specifically, we examine differentially private variants of the k-medians and Euclidean k-means problems. We present polynomial…
Searching for available parking spaces is a major problem for drivers especially in big crowded cities, causing traffic congestion and air pollution, and wasting drivers' time. Smart parking systems are a novel solution to enable drivers to…
Spatial crowdsourcing (SC) is an increasing popular category of crowdsourcing in the era of mobile Internet and sharing economy. It requires workers to arrive at a particular location for task fulfillment. Effective protection of location…
Most existing image privacy protection works focus mainly on the privacy of photo owners and their friends, but lack the consideration of other people who are in the background of the photos and the related location privacy issues. In fact,…
As we transition into the era of B5G/6G networks, the promise of seamless, high-speed connectivity brings unprecedented opportunities and challenges. Among the most critical concerns is the preservation of location privacy, given the…
Recent trend towards cloud computing paradigm, smart devices and 4G wireless technologies has enabled seamless data sharing among users. Cloud computing environment is distributed and untrusted, hence data owners have to encrypt their data…
The growing demand for intelligent environments unleashes an extraordinary cycle of privacy-aware applications that makes individuals' life more comfortable and safe. Examples of these applications include pedestrian tracking systems in…
There is a growing need for spatial privacy considerations in the many geo-spatial technologies that have been created as solutions for COVID-19-related issues. Although effective geo-spatial technologies have already been rolled out, most…
Location-based mobile social network services such as foursquare and Gowalla have grown exponentially over the past several years. These location-based services utilize the geographical position to enrich user experiences in a variety of…
Location data is collected from users continuously to understand their mobility patterns. Releasing the user trajectories may compromise user privacy. Therefore, the general practice is to release aggregated location datasets. However,…
Nowadays, mobile users have a vast number of applications and services at their disposal. Each of these might impose some privacy threats on users' "Personally Identifiable Information" (PII). Location privacy is a crucial part of PII, and…
Cloud computing is a powerful and popular information technology paradigm that enables data service outsourcing and provides higher-level services with minimal management effort. However, it is still a key challenge to protect data privacy…
As nowadays most web application requests originate from mobile devices, authentication of mobile users is essential in terms of security considerations. To this end, recent approaches rely on machine learning techniques to analyze various…