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Decentralized Online Social Networks (DOSNs) are evolving as a promising approach to mitigate design-inherent privacy flaws of logically centralized services such as Facebook, Google+ or Twitter. Common approaches to implement a DOSN build upon a peer-to-peer (P2P) architecture in order to avoid the central aggregation of sensitive user data at one provider-controlled location. While the absence of a single point of data aggregation strikes the most powerful attacker from the list of adversaries, the decentralization also removes some privacy protection afforded by the provider's intermediation of all communication in a centralized Online Social Network (OSN). As content storage, access right management, retrieval and other administrative tasks of the service become the obligation of the users, it is non-trivial to hide the metadata of objects and information flows, even when the content itself is encrypted. Such metadata is, deliberately or as a side effect, hidden by the provider in a centralized system. Implementing the different features of a privacy-presvering DOSN does not only face these general challenges but must also cope with the absence of a trusted agent with full access to all data. For example user authentication should provide the same usabilty known from common centralized OSN services, such as ease of changing a password, revoking the access of a stolen device or resetting a forgotten password via e-mail or security questions. All this without relying on a trusted third party such as an identity provider. Another example is user search, where the challenge is to protect user data while making user findable at the same time. An implementation of such a feature in a DOSN has to work without assuming a trusted provider having access to all user profiles maintaining a global search index. In this work we analyze the general privacy-problems in a DOSN, especially those arising from metadata. Furthermore, we suggest two privacy-preserving implementations of standard OSN features, i.e., user authentication via password-login and user search via a knowledge threshold. Both implementations do not rely on a trusted, central provider and are therefore applicable in a DOSN cenario but can be applied in other P2P or low-trust environments as well. / I dagens populära sociala nätverkstjänster, såsom Facebook, Google+ och Twitter, finns en risk för integritetskränkningar. Risken är en oundviklig konsekvens av den logiskt centraliserade struktur som dessa tjänster bygger på.  Decentraliserade sociala nätverkstjänster (eng. Decentralized Online Social Networks, DOSNs) är en lovande utveckling för att minska risken och skydda användarnas personliga information från tjänsteleverantören och dem som leverantören samarbetar med. Ett vanligt sätt att implementera ett DOSN är genom en icke-hierarkisk nätverksarkitektur (eng. peer-to-peer network) för att undvika att känsliga personuppgifter ansamlas på ett ställe under tjäns televerantörens kontroll.   Att inte längre ha en tjänsteleverantör som har tillgång till alla data tar bort den största risken för integritetskränkningar. Men genom att ersätta den centrala tjänsteleverantören med ett decentraliserat system tar vi även bort visst integritetsskydd. Integritetsskyddet var en konsekvens av att förmedlingen av all användarkommunikation skedde genom tjänsteleverantörens mellanservrar. När ansvaret för lagring av innehållet, hantering av behörigheterna, åtkomst och andra administrativa uppgifter övergår till användarna själva, då blir det en utmaning att skydda metadata för objekten och informationsflöden, även om innehållet är krypterat. I ett centraliserat system är dessa metadata faktiskt skyddade av tjänsteleverantören - avsiktligt eller som en sidoeffekt.   För att implementera de olika funktioner som ska finnas i ett integritetsskyddande DOSN, är det nödvändigt att både lösa dessa generella utmaningar och att hantera frånvaron av ett betrodd tredjepart som har full tillgång till all data. Autentiseringen av användarna, till exempel, borde ha samma användbarhet som finns i centraliserade system. Det vill säga att det är lätt att ändra lösenordet, dra tillbaka rättigheterna för en stulen klientenhet, eller återställa ett glömt lösenord med hjälp av e-post eller säkerhetsfrågor - allt utan att förlita sig på en betrodd tredjepart. Ett annat exempel är funktionen att kunna söka efter andra användare. Utmaningen där är att skydda informationen om användarna samtidigt som det måste vara möjligt att hitta användare baserad på samma information. En implementation av denna funktion i ett DOSN måste klara sig utan en betrodd tjänsteleverantör som med tillgång till alla användares data kan upprätthålla ett globalt sökindex. I den här avhandlingen analyserar vi de generella risker för integritetskränkningar i DOSN, särskilt de som orsakas av metadata. Dessutom föreslår vi två integritetskyddande implementationer av vanliga funktioner i en socialt nätverkstjänst: lösenordbaserad användarautentisering och en användarsökfunktionen med en kunskaptröskel. Båda implementationerna är lämpliga för DOSN-scenarier eftersom de klarar sig helt utan en betrodd, central tjänstleverantör, och kan därför också användas i andra sammanhang: såsom icke-hierarkiska nätverk eller andra system som måste klara sig utan en betrodd tredjepart. / <p>QC 20150428</p>

This thesis elaborates on the design process of a mobile phone based application for indoor positioning at workplaces. The aim of the application is to ease workflow management and help increase the work efficiency of individuals and teams by reducing the amount of time spent in looking and waiting for each other. In doing so, the research takes a closer look on the user’s perspective on sharing one’s location data. An attempt is made to explore users’ behavior, investigating if any privacy concerns arise out of sharing one’s indoor location data and how it effects the adoption of the service within the context of a workspace. This exploratory approach employed a number of qualitative tools in order to gather data and analyze it. In order to understand the complex context of a work environment where activities (or actions) are defined by a number of factors, actors, mediators, communication channels, etc., the research followed an activity centred approach. The resulting solution is in the form of a service that provides layers of contextual information, responding to the overall activity being performed and the smaller actions that constitute it. A prototype of this application is then taken for user testing. The test results show that the users were hesitant in sharing their location data; citing a number of speculated scenarios where this information may be used in ways that induced a sense of being spied upon. However, in the overall acceptance and adoption of the system, the context of use (the workspace) was found to play a very crucial role.

A collection of short stories exploring patterns that play out in people's lives and relationships.

Autonomous systems have progressed from theory to application especially in the last decade, thanks to the recent technological evolution. The number of autonomous systems in our surroundings is increasing rapidly. Since these systems in most cases handle privacy-sensitive data, the privacy concerns are also increasing at a similar rate. However, privacy research has not been in sync with these developments. Moreover, the systems are heterogeneous in nature and continuously evolving which makes the privacy problem even more challenging. The domain poses some unique privacy challenges which are not always possible to solve using existing solutions from other related fields. In this thesis, we identify open privacy challenges of autonomous systems and later propose solutions to some of the most prominent challenges. We investigate the privacy challenges in the context of smart home-based systems including Ambient Assisted Living (AAL) systems as well as autonomous vehicles. In the case of smart home, we propose a framework to enhance the privacy of owners during ownership change of IoT devices and conduct a systematic literature review to identify the privacy challenges of home-based health monitoring systems. For autonomous vehicles, we quantify, improve, and tune the privacy utility trade-off of the image de-identification process. Our investigation reveals that there is a lack of consideration when it comes to the privacy of autonomous systems and there are several open research questions in the domain regarding, for instance, privacy-preserving data management, quantification of privacy utility trade-off, and compliance with privacy laws. Since the field is evolving, this work can be seen as a step towards privacy preserving autonomous systems. The identified privacy concerns and their corresponding solutions presented in this thesis will help the research community to identify and address existing privacy concerns of autonomous systems. Solving the concerns will encourage the end-users to adopt the systems and enjoy the benefits without bothering about privacy. / <p>QC 20201116</p>

The scale of modern surveillance and the debate surrounding its nature have become expansively complex. Consequently, the field of communication and surveillance studies represent a critical area of scholarship with interwoven academic, policy and social implications. This thesis, a critical ideological study of modern surveillance founded upon an empirical study, draws on participant observation, militant ethnography and semistructured interviews as research methods. From a participant insider perspective, it explores and interprets the experiences, meanings and views of counter-surveillance actors targeted by surveillance based on participant observation and militant ethnography conducted during the 2017 Chaos Communication Congress in Leipzig and the 2019 Chaos Communication Camp in Mildenberg, Germany. Drawing on Jeffrey Juris’ militant ethnography and based on the participants’ own experiences in resisting modern surveillance, I focus on the lessons learned from those belonging to the third-wave of privacy activism. Through their personal experiences, this research reveals control strategies, lessons learned and views of privacy activists, hacktivists and civic-hackers on the state of modern surveillance. This thesis concludes that the current symbiotic nature of the state-corporate surveillance and disinformation nexus means any legislative solution to be unlikely.

Smart speakers are a category of smart devices with a built-in voice assistant and a variety of specialized sensors. Introducing these devices into our homes has proven to be a potential privacy threat to the unaware user because of its “microphone always on” nature. The smart speaker provides convenience at the cost of personal information being shared with the company who built the product. In this paper we introduce our readers to smart speaking devices, their management of personal information and its privacy implications. Firstly, with our literature review, we dig deeper into the current understanding of smart speakers, data management, general opinions and awareness. Secondly, we conclude a survey by means of a questionnaire where we discover the opinions of residents in Blekinge county, southern Sweden, towards smart speakers management of personal data in order to evaluate the general position of said residents towards these devices with the hopes to bring added value and understanding to the current research and to give additional information that can be useful by smart speakers manufacturers in terms of the user experience. We find that there is low demand for the product in Blekinge, that sensitive information is unlikely to be shared knowingly by the user and that an IT background doesn’t have a large impact on the opinion or interest of the user.

<div>Vast amounts of sensitive personal information are collected by companies, institutions and governments. A key technological challenge is how to effectively extract knowledge from data while preserving the privacy of the individuals involved. In this dissertation, we address this challenge from the perspective of privacy-preserving data collection and analysis. We focus on investigation of a technique called local differential privacy (LDP) and studied several aspects of it. </div><div><br></div><div><br></div><div>In particular, the thesis serves as a comprehensive study of multiple aspects of the LDP field. We investigated the following seven problems: (1) We studied LDP primitives, i.e., the basic mechanisms that are used to build LDP protocols. (2) We then studied the problem when the domain size is very big (e.g., larger than $2^{32$), where finding the values with high frequency is a challenge, because one needs to enumerate through all values. (3) Another interesting setting is when each user possesses a set of values, instead of a single private value. (4) With the basic problems visited, we then aim to make the LDP protocols practical for real-world scenarios. We investigated the case where each user's data is high-dimensional (e.g., in the census survey, each user has multiple questions to answer), and the goal is to recover the joint distribution among the attributes. (5) We also built a system for companies to issue SQL queries over the data protected under LDP, where each user is associated with some public weights and holds some private values; an LDP version of the values is sent to the server from each user. (6) To further increase the accuracy of LDP, we study how to add post-processing steps to protocols to make them consistent while achieving high accuracy for a wide range of tasks, including frequencies of individual values, frequencies of the most frequent values, and frequencies of subsets of values. (7) Finally, we investigate a different model of LDP which is called the shuffler model. While users still use LDP algorithms to report their sensitive data, now there exists a semi-trusted shuffler that shuffles the users' reports and then send them to the server. This model provides better utility but at the cost of requiring more trust that the shuffler should not collude with the server.</div>

I en tid där digitaliseringen är mer utbredd än någonsin ökar också mängden data som samlas och delas online. I takt med att nya tekniker utvecklas öppnas det upp för nya utmaningar för integritetsfrågor. En aktiv användare online ägnar sig med största sannolikhet också åt ett eller flera sociala medier, där ändamålen ofta innebär att dela med sig av information till andra. Eftersom tekniken Augmented Reality används mer frekvent i några av de största sociala medieapplikationerna blev studiens syfte att undersöka potentiella integritetsproblem med Augmented Reality. Studiens tillvägagångssätt har bestått av en empirisk datainsamling för att skapa ett teoretiskt ramverk för studien. Utifrån detta har det genomförts en digital enkät samt intervjuer för att närmare undersöka användarens beteende online och The Privacy Paradox. Utifrån undersökningens resultat kunde The Privacy Paradox bekräftas och ge en bättre förståelse för hur användaren agerar genom digitala kanaler. I studien behandlas olika aspekter kring integritetsfrågor såsom användarvillkor, sekretessavtal, datamäklare, framtida konsekvenser och vad tekniken möjliggör. Studien kommer fram till att användare, företaget och dagens teknik tillåter att en känsligare information kan utvinnas genom ett dataintrång. Även om det ännu inte har inträffat ett dataintrång som grundat sig i Augmented Reality före denna studie, finns det en risk att det endast handlar om en tidsfråga innan detta sker. / In a time when digitalization is more widespread than ever, the amount of data collected and shared is increasing. As new technologies develop, challenges for privacy concerns arises. An active online user is likely to engage in one or many social media platforms, where the purpose often involves sharing information with others. Since Augmented Reality is more frequently supported in some of the biggest social media applications, the purpose of this study was to investigate potential privacy concerns with Augmented Reality. The study’s approach consisted of an empirical data collection to create a theoretical framework for the study. Based on this, a digital survey and interviews were conducted to further investigate the user's behavior online and The Privacy Paradox. Based on the results of the survey, The Privacy Paradox could be confirmed and a better understanding of how the user interacts through digital channels was achieved. The study treats different aspects of privacy concerns such as user terms, privacy policies, data brokers, future consequences and what technology enables. The study reached the conclusion that users, businesses and today's technology allow a more sensitive type of information to be collected through a data breach. Even if there has not yet occurred a data breach enabled by Augmented Reality prior to this study, there is a risk that it is only a matter of time until this happens.

Background. As long as Facebook has existed, advertisements have been present in the application in one way or another. The ads have evolved and become more sophisticated over the years. Today, Facebook creates groups with members having specific attributes and advertisers requests groups for whom Facebook shows the advertisement. Besides this, Facebook receives information from other sources such as browser cookies and ad pixels. All information that Facebook receive or collect is used in their algorithms to target relevant advertisement for each user. Objectives. To examine the possibility of Facebook eavesdropping through the microphone for marketing purposes and identify eventual keywords mapped between a spoken conversation and advertisement. Methods. Five controlled experiments were performed with two test phones and two control phones. These were treated equally beside the test phones being exposed to spoken conversations containing randomly chosen products, companies and brands. The content of the phones was compared to see whether advertisement was adapted to the spoken conversation in the test phones but not in the control phones. Results. No sponsored advertisements were present on the Facebook and Instagram application. Messenger contained ads indicating that Facebook might analyse the content of private messages to adapt advertisement. After adding the Wish application to the research, the results were still the same. Other contents in the Facebook news feed were analysed, however, the content analysed did not contain any evidence that Facebook eavesdrops on spoken conversations for marketing purpose. Conclusions. The experiments conducted were not sufficient enough to trigger sponsored advertisement. Therefore, no indications were found that Facebook is eavesdropping through the microphone or not.