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

COVID-19 Pandemic: Balancing Privacy and Saving Lives in Technology Usage

COVID-19 is sweeping across the globe. Some countries are collecting anonymized data to study the movement of people and others are providing more detailed information about individuals in addition to the movement data. Surveillance tools are widely used to stem the spread of the COVID-19. South Korea uses smartphone location data, surveillance camera footage, and credit card data to create a publicly available map that tracks the paths of COVID-19 patients. Austria’s network operators share anonymized location data with the government, but the data may remain at risk from re-identification in the future. The Polish government releases an app for people in quarantine, requiring them to upload geo-located selfies periodically. In some countries, police and military personnel are also involved in enforcing quarantines, curfews, and social distancing, which may encroach on personal freedom and privacy. There is no doubt that the use of technologies, such as geolocation and facial recognition, can help to slow and manage the spread of COVID-19 and enforce social distancing, but people are concerned about the expanded and potentially questionable uses of technologies that may result in privacy issues (Siau & Wang, 2020). Many questions remain to be answered. How the data is being shared? How to deal with the data and the surveillance capabilities once the pandemic subsides? How to prevent unauthorized individuals or institutions from gaining access to the data? Privacy is recognized as a fundamental human right, essential for freedom, democracy, and psychological well-being. As technology developed, especially the progress of mobile devices (Siau & Shen, 2002, 2006), concerns about privacy (location data in particular) increase (Shokri et al. 2011). Some organizations are dedicated to protecting individual privacy while sharing information, and encrypting the data collected to prevent a hacker from accessing identifiable information. However, as evidenced by data breaches, information is increasingly exposed to hacking, which results in information security and privacy issues (Siau & Wang, 2018; Wang & Siau, 2019). This qualitative study will examine how organizations and authorities are dealing with the tradeoff between protecting individual privacy and saving lives in the pandemic. In the first phase of the study, data security and privacy officers in various government and healthcare organizations will be interviewed. In the second phase, the findings from the first phase will be used to design questionnaires, which will be administered in government organizations. This will be a multi-country and multi-culture research

Improving pedestrian’s crosswalk accessibility through digital fencing

One of the major challenges for visually impaired people is to walk safely in any urban landscape. Modern cities are using passive solutions, like audible signals, to promote the security of that pedestrians. However, these solutions may be insufficient to provide the relevant information about the traffic flow, and the length of the crosswalk among many other questions. Smart crosswalks can improve the access to such information by providing a way for the user to share data with them. This paper addresses this question by presenting the VALLPASS project that aims to develop a smart pedestrians crosswalk that, besides other design requirements, aims to promote accessibility by sharing local traffic data with the user. Besides that, pedestrian security will be tackled by defining a digital protecting fence based on the user location obtained from the RSSI values between two beacons and the user’s smartphone. Details behind its operation and the overall functionality of a custom-made app will be provided.info:eu-repo/semantics/publishedVersio

Secure and Private Proofs for Location-Based Activity Summaries in Urban Areas

Activity-based social networks, where people upload and share information about their location-based activities (e.g., the routes of their activities), are increasingly popular. Such systems, however, raise privacy and security issues: the service providers know the exact locations of their users; the users can report fake location information to, for example, unduly brag about their performance. In this paper, we propose a secure privacy-preserving system for reporting location-based activity summaries (e.g., the total distance covered and the elevation gain). Our solution is based on a combination of cryptographic techniques and geometric algorithms, and it relies on existing Wi-Fi access point networks deployed in urban areas. We evaluate our solution by using real data-sets from the FON community networks and from the Garmin Connect activity-based social network, and show that it can achieve tight (up to a median accuracy of 79%) verifiable lower-bounds of the distance covered and of the elevation gain, while protecting the location privacy of the users with respect to both the social network operator and the access point network operator(s)

Willingness to pay for the conservation and management of wild geese in Scotland

In past times wild geese were an important resource, providing a source of meat, grease for lubrication and waterproofing, and feathers for bedding and arrow flights. Today, with the sale of goose meat no longer allowed in law, the only current market for geese is commercial shooting of non-endangered species such as the pink-footed goose. However, there are other benefits associated with geese which are not priced in the marketplace, but are valued. For example, some people positively value the opportunity to observe geese in the wild (a use-value), while others may take pleasure from simply knowing that they exist (a non-use value). These benefits cannot be provided by conventional markets because it would be prohibitively expensive to exclude people from watching geese and impossible to exclude them from caring about geese. In recent years a number of techniques such as Contingent Valuation (CV) and Choice Experiments (CE) have been established to establish the monetary values of non-market benefits. These techniques aim to measure the willingness to pay (WTP) of beneficiaries through the establishment of hypothetical markets