The ever increasing popularity of Facebook and other Online Social Networks has left a wealth of personal and private data on the web, aggregated and readily accessible for broad and automatic retrieval. Protection from both undesired recipients as well as harvesting through crawlers is implemented by simple access control at the provider, configured by manual authorization through the publishing user. Several studies demonstrate that standard settings directly cause an unnoticed over-sharing and that the users have trouble understanding and configuring adequate settings. Using the three simple principles of color coding, ease of access, and application of common practices, we developed a new privacy interface that increases the usability significantly. The results of our user study underlines the extent of the initial problem and documents that our interface enables faster, more precise authorisation and leads to increased intelligibility.
Improving security in OSNs is a very widely discussed issue in literature. A vast amount of approaches have been published, mainly assuming not only malicious users, but a malicious provider, as well. The range starts with cutting the profile in centralized OSNs into atomic parts, to encrypt each part separately and distribute keys to authorized recipients @cite_10 @cite_11 . It ends with completely distributed p2p OSNs like PeerSoN @cite_1 or Safebook @cite_4 . Common to these approaches is the attempt to enhance service's infrastructure or to even develop an entirely new social network service. All of them are based on encryption or decentralized storage of private content. Distrusting the service provider, they consequently aim at implementing distributed access control and confidential data storage. Assuming benign service providers, the usability of the interfaces emerges as the prevalent challenge for privacy.
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To address privacy concerns over Online Social Networks (OSNs), we propose a distributed, peer-to-peer approach coupled with encryption. Moreover, extending this distributed approach by direct data exchange between user devices removes the strict Internet-connectivity requirements of web-based OSNs. In order to verify the feasibility of this approach, we designed a two-tiered architecture and protocols that recreate the core features of OSNs in a decentralized way. This paper focuses on the description of the prototype built for the P2P infrastructure for social networks, as a first step without the encryption part, and shares early experiences from the prototype and insights gained since first outlining the challenges and possibilities of decentralized alternatives to OSNs. While highly successful, today's online social networks (OSNs) have made a conscious decision to sacrifice privacy for availability and centralized control. Unfortunately, tradeoffs in this "walled garden" architecture naturally pit the economic interests of OSN providers against the privacy goals of OSN users, a battle that users cannot win. While some alternative OSN designs preserve user control over data, they do so by de-prioritizing issues of economic incentives and sustainability. In contrast, we believe any practical alternative to today's centralized architecture must consider incentives for providers as a key goal. In this paper, we propose a distributed OSN architecture that significantly improves user privacy while preserving economic incentives for OSN providers. We do so by using a standardized API to create a competitive provider marketplace for different components of the OSN, thus allowing users to perform their own tradeoffs between cost, performance, and privacy. We describe Polaris, a system where users leverage smartphones as a highly available identity provider and access control manager, and use application prototypes to show how it allows data monetization while limiting the visibility of any single party to users' private data. We consider the privacy-preserving link prediction problem in decentralized online social network (OSNs). We formulate the problem as a sparse logistic regression problem and solve it with a novel decentralized two-tier method using alternating direction method of multipliers (ADMM). This method enables end users to collaborate with their online service providers without jeopardizing their data privacy. The method also grants end users fine-grained privacy control to their personal data by supporting arbitrary public private data split. Using real-world data, we show that our method enjoys various advantages including high prediction accuracy, balanced workload, and limited communication overhead. Additionally, we demonstrate that our method copes well with link reconstruction attack. Today's online social networking (OSN) sites do little to protect the privacy of their users' social networking information. Given the highly sensitive nature of the information these sites store, it is understandable that many users feel victimized and disempowered by OSN providers' terms of service. This paper presents Lockr, a system that improves the privacy of centralized and decentralized online content sharing systems. Lockr offers three significant privacy benefits to OSN users. First, it separates social networking content from all other functionality that OSNs provide. This decoupling lets users control their own social information: they can decide which OSN provider should store it, which third parties should have access to it, or they can even choose to manage it themselves. Such flexibility better accommodates OSN users' privacy needs and preferences. Second, Lockr ensures that digitally signed social relationships needed to access social data cannot be re-used by the OSN for unintended purposes. This feature drastically reduces the value to others of social content that users entrust to OSN providers. Finally, Lockr enables message encryption using a social relationship key. This key lets two strangers with a common friend verify their relationship without exposing it to others, a common privacy threat when sharing data in a decentralized scenario. This paper relates Lockr's design and implementation and shows how we integrate it with Flickr, a centralized OSN, and BitTorrent, a decentralized one. Our implementation demonstrates Lockr's critical primary benefits for privacy as well as its secondary benefits for simplifying site management and accelerating content delivery. These benefits were achieved with negligible performance cost and overhead.