On the adoption of privacy-enhancing technologies

We propose a model, based on the work of Brock and Durlauf, which looks at how agents make choices between competing technologies, as a framework for exploring aspects of the economics of the adoption of privacy-enhancing technologies. In order to formulate a model of decision-making among choices of technologies by these agents, we consider the following: context, the setting in which and the purpose for which a given technology is used; requirement, the level of privacy that the technology must provide for an agent to be willing to use the technology in a given context; belief, an agent’s perception of the level of privacy provided by a given technology in a given context; and the relative value of privacy, how much an agent cares about privacy in this context and how willing an agent is to trade off privacy for other attributes. We introduce these concepts into the model, admitting heterogeneity among agents in order to capture variations in requirement, belief, and relative value in the population. We illustrate the model with two examples: the possible effects on the adoption of iOS devices being caused by the recent Apple–FBI case; and the recent revelations about the non-deletion of images on the adoption of Snapchat

Examining older users’ online privacy-enhancing experience from a human-computer interaction perspective

The advancement of Internet technologies, including instant and unlimited access to information and services, has been an excellent source of support for older adults. However, pervasive and continuous online tracking can pose severe threats to older adults’ information privacy. Surprisingly, very few empirical studies have focused on older users’ online privacy-enhancing experience from a Human-Computer Interaction perspective. Therefore, it remains unclear how older users protect their online information privacy and what factors influence their online behaviors. Thus, my thesis aims to study older users’ online privacy-enhancing experience by examining the following questions: 1) what older users know and do to protect their online information privacy, 2) how their emotional state influences their adoption of privacy-enhancing technologies (PETs), and 3) what usability challenges they encounter while using one of the most popular PETs currently available to the public. To examine these questions, a diverse set of empirical approaches was adopted, including a survey, a quasi-experiment, and a usability study. My research findings suggest that three are three elements that play a crucial role in older users' online privacy-enhancing practices. First, older users' knowledge of online privacy has a significant influence on their daily online privacy protection behaviors. In addition, there seems to be a privacy knowledge gap among older users that reveals the phenomenon of ‘Privacy Divide.' Second, the design of privacy-enhancing features affects older users’ emotional state and their attitudes regarding their future adoption of the tool. Third, the findings of usability study indicate that the current design of a privacy- enhancing browsing tool, Tor Browser, poses particular challenges for older users. For instance, the technical terminologies and recurring warning messages have made Tor Browser more difficult for older users to use. These usability challenges not only decrease older users’ satisfaction in but also deter their future adoption of the tool. Therefore, it is crucial that current design of PETs considers older users’ needs. My thesis research contributes to the privacy literature in several ways. First of all, this is the first empirical research examining older users’ actual online privacy protection behaviors. In addition, this thesis includes the very first empirical study that illustrate the importance of the role of emotion in users’ adoption of a privacy-enhancing tool. Furthermore, this thesis provides usability recommendations that can improve the current design of Tor Browser for older user audiences. As the world's aging population continues to grow and advances in Internet technologies progress rapidly, the design of future technologies, from smart homes to self-driving cars, has to adopt user-centered approach, which consider end-users' needs of all age groups. Also, information privacy has become a significant aspect in our digital world, which makes the design of user-friendly privacy-enhancing tools an essential mission ahead of us. Moreover, knowledge and awareness are a key factor in older users’ online privacy- enhancing practices. Henceforth, creating educational programs for older adults is extremely important in protecting their online privacy

StyleID: Identity Disentanglement for Anonymizing Faces

Privacy of machine learning models is one of the remaining challenges that hinder the broad adoption of Artificial Intelligent (AI). This paper considers this problem in the context of image datasets containing faces. Anonymization of such datasets is becoming increasingly important due to their central role in the training of autonomous cars, for example, and the vast amount of data generated by surveillance systems. While most prior work de-identifies facial images by modifying identity features in pixel space, we instead project the image onto the latent space of a Generative Adversarial Network (GAN) model, find the features that provide the biggest identity disentanglement, and then manipulate these features in latent space, pixel space, or both. The main contribution of the paper is the design of a feature-preserving anonymization framework, StyleID, which protects the individuals' identity, while preserving as many characteristics of the original faces in the image dataset as possible. As part of the contribution, we present a novel disentanglement metric, three complementing disentanglement methods, and new insights into identity disentanglement. StyleID provides tunable privacy, has low computational complexity, and is shown to outperform current state-of-the-art solutions.Comment: Accepted to Privacy Enhancing Technologies Symposium (PETS), July 2023. Will appear in Proceedings on Privacy Enhancing Technologies (PoPETs), volume 1, 2023. 15 pages including references and appendix, 16 figures, 5 table

Internet Localization of Multi-Party Relay Users: Inherent Friction Between Internet Services and User Privacy

Internet privacy is increasingly important on the modern Internet. Users are looking to control the trail of data that they leave behind on the systems that they interact with. Multi-Party Relay (MPR) architectures lower the traditional barriers to adoption of privacy enhancing technologies on the Internet. MPRs are unique from legacy architectures in that they are able to offer privacy guarantees without paying significant performance penalties. Apple's iCloud Private Relay is a recently deployed MPR service, creating the potential for widespread consumer adoption of the architecture. However, many current Internet-scale systems are designed based on assumptions that may no longer hold for users of privacy enhancing systems like Private Relay. There are inherent tensions between systems that rely on data about users -- estimated location of a user based on their IP address, for example -- and the trend towards a more private Internet. This work studies a core function that is widely used to control network and application behavior, IP geolocation, in the context of iCloud Private Relay usage. We study the location accuracy of popular IP geolocation services compared against the published location dataset that Apple publicly releases to explicitly aid in geolocating PR users. We characterize geolocation service performance across a number of dimensions, including different countries, IP version, infrastructure provider, and time. Our findings lead us to conclude that existing approaches to IP geolocation (e.g., frequently updated databases) perform inadequately for users of the MPR architecture. For example, we find median location errors >1,000 miles in some countries for IPv4 addresses using IP2Location. Our findings lead us to conclude that new, privacy-focused, techniques for inferring user location may be required as privacy becomes a default user expectation on the Internet

A User-centered Perspective of mHealth: Understanding Patients’ Intentions to Use Mobile Video Consultation Services

Research has shown that the use of the mobile phone technology in combination with a web-based interface in health care could provide enormous benefits. In this work, we shed light on users’ acceptance of mHealth with the example of mobile video consultation with a doctor. Our quantitative study is based on a survey of 210 respondents. We draw on TAM, one of the most-used and often-cited concepts for explaining adoption behavior for newly introduced technologies and technical services. The results reveal that an interaction between personal innovativeness and perceived privacy risk has an effect on user’s perceived ease of use. The findings contribute to research by enhancing our understanding of mHealth adoption from a user’s acceptance perspective

Revealing the Landscape of Privacy-Enhancing Technologies in the Context of Data Markets for the IoT: A Systematic Literature Review

IoT data markets in public and private institutions have become increasingly relevant in recent years because of their potential to improve data availability and unlock new business models. However, exchanging data in markets bears considerable challenges related to disclosing sensitive information. Despite considerable research focused on different aspects of privacy-enhancing data markets for the IoT, none of the solutions proposed so far seems to find a practical adoption. Thus, this study aims to organize the state-of-the-art solutions, analyze and scope the technologies that have been suggested in this context, and structure the remaining challenges to determine areas where future research is required. To accomplish this goal, we conducted a systematic literature review on privacy enhancement in data markets for the IoT, covering 50 publications dated up to July 2020, and provided updates with 24 publications dated up to May 2022. Our results indicate that most research in this area has emerged only recently, and no IoT data market architecture has established itself as canonical. Existing solutions frequently lack the required combination of anonymization and secure computation technologies. Furthermore, there is no consensus on the appropriate use of blockchain technology for IoT data markets and a low degree of leveraging existing libraries or reusing generic data market architectures. We also identified significant challenges remaining, such as the copy problem and the recursive enforcement problem that-while solutions have been suggested to some extent-are often not sufficiently addressed in proposed designs. We conclude that privacy-enhancing technologies need further improvements to positively impact data markets so that, ultimately, the value of data is preserved through data scarcity and users' privacy and businesses-critical information are protected.Comment: 49 pages, 17 figures, 11 table

Distributed Performance Measurement and Usability Assessment of the Tor Anonymization Network

While the Internet increasingly permeates everyday life of individuals around the world, it becomes crucial to prevent unauthorized collection and abuse of personalized information. Internet anonymization software such as Tor is an important instrument to protect online privacy. However, due to the performance overhead caused by Tor, many Internet users refrain from using it. This causes a negative impact on the overall privacy provided by Tor, since it depends on the size of the user community and availability of shared resources. Detailed measurements about the performance of Tor are crucial for solving this issue. This paper presents comparative experiments on Tor latency and throughput for surfing to 500 popular websites from several locations around the world during the period of 28 days. Furthermore, we compare these measurements to critical latency thresholds gathered from web usability research, including our own user studies. Our results indicate that without massive future optimizations of Tor performance, it is unlikely that a larger part of Internet users would adopt it for everyday usage. This leads to fewer resources available to the Tor community than theoretically possible, and increases the exposure of privacy-concerned individuals. Furthermore, this could lead to an adoption barrier of similar privacy-enhancing technologies for a Future Internet. View Full-Tex

Personal data breach notification system in the European Union: Interpretation of “without undue delay”

This is the post-print version of the Article - Copyright @ 2011 Kluwer Law InternationalThe fast-moving technologies continually challenge present rules on data-privacy protection. The expansion of computing functions, speed of processing and storage capabilities makes personal information difficult to be controlled. In the EU, the revised EC e-Privacy Directive amended by the Directive 2009/136/EC modifies existing provisions and makes new provisions to enhance privacy protection in the electronic communications sector, which includes the further development of the system of notification of the personal data breach to minimise adverse effects. This paper aims to examine and evaluate the personal data breach notification system, interpret the requirement of "without undue delay" duty and discuss the impact of the revised Directive to business organisations. It finally proposes solutions to improve the notification system to increase the efficiency of privacy protection