Impact of User Privacy and Mobility on Edge Offloading

Offloading high-demanding applications to the edge provides better quality of experience (QoE) for users with limited hardware devices. However, to maintain a competitive QoE, infrastructure, and service providers must adapt to users' different mobility patterns, which can be challenging, especially for location-based services (LBS). Another issue that needs to be tackled is the increasing demand for user privacy protection. With less (accurate) information regarding user location, preferences, and usage patterns, forecasting the performance of offloading mechanisms becomes even more challenging. This work discusses the impacts of users' privacy and mobility when offloading to the edge. Different privacy and mobility scenarios are simulated and discussed to shed light on the trade-offs (e.g., privacy protection at the cost of increased latency) among privacy protection, mobility, and offloading performance.Comment: 2023 Annual IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications (IEEE PIMRC 2023

Privacy protection in location based services

This thesis takes a multidisciplinary approach to understanding the characteristics of Location Based Services (LBS) and the protection of location information in these transactions. This thesis reviews the state of the art and theoretical approaches in Regulations, Geographic Information Science, and Computer Science. Motivated by the importance of location privacy in the current age of mobile devices, this thesis argues that failure to ensure privacy protection under this context is a violation to human rights and poses a detriment to the freedom of users as individuals. Since location information has unique characteristics, existing methods for protecting other type of information are not suitable for geographical transactions. This thesis demonstrates methods that safeguard location information in location based services and that enable geospatial analysis. Through a taxonomy, the characteristics of LBS and privacy techniques are examined and contrasted. Moreover, mechanisms for privacy protection in LBS are presented and the resulting data is tested with different geospatial analysis tools to verify the possibility of conducting these analyses even with protected location information. By discussing the results and conclusions of these studies, this thesis provides an agenda for the understanding of obfuscated geospatial data usability and the feasibility to implement the proposed mechanisms in privacy concerning LBS, as well as for releasing crowdsourced geographic information to third-parties

Location Privacy Protection in Social Networks

University of Technology Sydney. Faculty of Engineering and Information Technology.Social networks have become more ubiquitous due to new advances in smartphone technology. This has provided an opportunity for social network service providers to utilise location information of users in their services. For example, Facebook Places, Foursquare and Yelp are popular social networks that mostly rely on utilising users' location data in their services. They offer a variety of useful services, from location recommendations to nearby friend alerts. However, protecting location privacy of users is still an open challenge for social network service providers. It has been shown that hiding real identity and choosing a pseudonym does not guarantee to protect a user's privacy since privacy may be invaded by analysing position data only. This is really a big issue since other private information of users can be revealed by analysing their location data (e.g., home address, health condition, interests, etc.). In this study, we investigate the location privacy issue of social networks and propose several solutions. We classify the proposed solutions into three categories based on the selected approaches, i.e. (i) differential privacy-based, (ii) cryptography-based, and (iii) anonymity-based solutions. We first study the approach in which differential privacy is utilised to preserve privacy of users. In this regard, we develop Distance-Based Location Privacy Protection mechanism (DBLP2), a customisable location privacy protection approach that is uniquely designed for social network users. It utilises the concept of social distance to generalise users' location data before it is published in a social network. The level of generalisation is decided based on the social distance between users. Secondly, we study cryptography-based methods for location privacy protection in Location-Based Services (LBS) and social networks. In this domain, we propose three cryptography-based and privacy-aware location verification schemes to preserve location privacy of users: (i) Privacy-Aware and Secure Proof Of pRoximiTy (PASPORT), (ii) Secure, Privacy-Aware and collusion Resistant poSition vErification (SPARSE), and (iii) a blockchain-based location verification scheme. These schemes prevent location spoofing attacks conducted by dishonest users while protect location privacy of users. To the best of our knowledge, majority of the existing location verification schemes do not preserve location privacy of users. Thirdly, we investigate anonymity as another approach to preserve users' privacy in social networks. In this regard, we first study the relevant protocols and discuss their features and drawbacks. Then, we introduce Harmonized and Stable DC-net (HSDC-net), a self-organizing protocol for anonymous communications in social networks. As far as we know, social networks do not offer any secure anonymous communication service. In social networks, privacy of users is preserved using pseudonymity, i.e., users select a pseudonym for their communications instead of their real identity. However, it has been shown that pseudonymity does not always result in anonymity (perfect privacy) if users' activities in social media are linkable. This makes users' privacy vulnerable to deanonymization attacks. Thus, by employing a secure anonymous communication service, social network service providers will be able to effectively preserve users' privacy. We perform extensive experiments and provide comprehensive security and privacy analysis to evaluate performance of the proposed schemes and mechanisms. Regarding the DBLP2 mechanism, our extensive analysis shows that it offers the optimum data utility regarding the trade-off between privacy protection and data utility. In addition, our experimental results indicate that DBLP2 is capable of offering variable location privacy protection and resilience to post processing. For the SPARSE scheme, our analysis and experiments show that SPARSE provides privacy protection as well as security properties for users including integrity, unforgeability and non-transferability of the location proofs. Moreover, it achieves a highly reliable performance against collusions. To validate performance of the PASPORT scheme, we implement a prototype of the proposed scheme on the Android platform. Extensive experiments indicate that the proposed method can efficiently protect location-based applications against fake submissions. For the proposed blockchain-based scheme, our prototype implementation on the Android platform shows that the proposed scheme outperforms other currently deployed location proof schemes. Finally, our prototype implementation of the HSDC-net protocol shows that it achieves low latencies that makes it a practical protocol. In summary, this research study focuses on developing new mechanisms for preserving location privacy of social network users. This is done through different approaches. Moreover, extensive effort is made to make the current location-related schemes and protocols privacy-aware. In this regard, several solutions in the form of scheme, mechanism, and protocol are introduced and their performance is evaluated. The results of this research work have also been presented in seven papers published in peer-reviewed journals and conferences

On (The Lack Of) Location Privacy in Crowdsourcing Applications

Crowdsourcing enables application developers to benefit from large and diverse datasets at a low cost. Specifically, mobile crowdsourcing (MCS) leverages users' devices as sensors to perform geo-located data collection. The collection of geo-located data raises serious privacy concerns for users. Yet, despite the large research body on location privacy-preserving mechanisms (LPPMs), MCS developers implement little to no protection for data collection or publication. To understand this mismatch, we study the performance of existing LPPMs on publicly available data from two mobile crowdsourcing projects. Our results show that well-established defenses are either not applicable or offer little protection in the MCS setting. Additionally, they have a much stronger impact on applications' utility than foreseen in the literature. This is because existing LPPMs, designed with location-based services (LBSs) in mind, are optimized for utility functions based on users' locations, while MCS utility functions depend on the values (e.g., measurements) associated with those locations. We finally outline possible research avenues to facilitate the development of new location privacy solutions that fit the needs of MCS so that the increasing number of such applications do not jeopardize their users' privacy

User Controlled Privacy Protection in Location-Based Services

The rapid development of location-determining technologies has enabled tracking of people or objects more accurately than ever before and the volume and extent of tracking has increased dramatically over time. Within the broader domain of tracking technologies, location-based services (LBS) are a subset of capabilities that allow users to access information relative to their own physical location. However, the personal location information generated by such technologies is at risk of being misused or abused unless protection capabilities are built into the design of such systems. These concerns may ultimately prevent society from achieving the broad range of benefits that otherwise would be available to consumers. The assumption of the emerging location-based industry is that corporations will own and control location and other information about individuals. Traditionally, privacy has been addressed through minimum standard approaches. However, regulatory and technological approaches focused on one size fits all standards are ill equipped to accommodate the interests of individuals or broad groups of users. This research explores the possibility of developing an approach for protecting privacy in the use of location-based services that supports the autonomy of an individual through a combined technological and legal model that places the power to protect location privacy in the hands of consumers. A proof of concept user interface to illustrate how personal information privacy could be protected in the conceptual model is demonstrated. A major goal of this project is to create an operational vision supporting user controlled protection of privacy that can help direct technological efforts along appropriate paths

The privacy concerns in location based services: protection approaches and remaining challenges

Despite the growth in the developments of the Location Based Services (LBS) applications, there are still several challenges remaining. One of the most important concerns about LBS, shared by many users and service providers is the privacy. Privacy has been considered as a big threat to the adoption of LBS among many users and consequently to the growth of LBS markets. This paper discusses the privacy concerns associated with location data, and the current privacy protection approaches. It reviews the advantages and disadvantages of each approach and evaluates the effectiveness of the available solutions. In order to detection of the remaining challenges (including the gaps between users demand and what the available solution can offer, a survey is conducted. This helps to estimates the importance and required protection level of the location privacy for different LBS applications. The results of the survey shows the public view on privacy concerns has changed over last years, this may be because of the wider popularity of social media and location based social networking services. Although there are technical, social regulatory policies to protect location privacy, there are still big challenges remaining, including misunderstanding about the privacy threats due to the lack of mutual understanding between users and LBS providers (including developers, policy makers and researchers)