Moritz Riesner

An Analysis of Implemented and Desirable Settings for Identity Management on Social Networking Sites

To address privacy threats stemming from interacting with other users on Social Networking Sites (SNS), effective Social Identity Management (SIdM) is a key requirement. SIdM refers to the deliberate and targeted disclosure of personal attribute values to a subset of ones contacts on SNS. While a variety of privacy-enhancing approaches have been proposed, these are often isolated solutions that lack integration into a reference framework that states the requirements for successfully managing ones identity. In this paper, a reference framework of existing and desired SIdM settings is derived from identity theory, literature analysis, and existing SNS. Based thereupon, we examine the SIdM capabilities of prevalent SNS and highlight possible improvements.

Analyzing settings for social identity management on Social Networking Sites: Classification, current state, and proposed developments

The rising prevalence of Social Networking Sites (SNS) and their usage in multiple contexts poses new privacy challenges and increasingly prompts users to manage their online identity. To address privacy threats stemming from interacting with other users on SNS, effective Social Identity Management (SIdM) is a key requirement. It refers to the deliberate and targeted disclosure of personal attribute values to a subset of ones contacts or other users on the SNS. Protection against other entities such as the site operator itself or advertisers and application programmers is not covered by SIdM, but could be incorporated in further refinement steps. Features and settings to perform SIdM have been proposed and subsequently implemented partly by some SNS. Yet, these are often isolated solutions that lack integration into a reference framework that states the requirements for successfully managing ones identity. In this article, such a reference framework of existing and desired SIdM settings is derived from identity theory, literature analysis, and existing SNS. Based thereupon, we examine the SIdM capabilities of prevalent SNS and highlight possible improvements. Lastly, we reason about developing a metric to objectively compare the capability of SNS in regards to their support for SIdM.

Provider-Independent Online Social Identity Management--Enhancing Privacy Consistently Across Multiple Social Networking Sites

The rising pervasiveness of social networking sites (SNS) poses new privacy risks and prompts adjusting ones online appearance to the current context of usage. This includes the deliberate and targeted disclosure of selected information to a subset of ones contacts, also known as social identity management (SIdM). Yet, when performing SIdM across multiple SNS, it is difficult to maintain a consistent representation of oneself. We introduce a global model to perform SIdM which is independent of particular SNS. Then we show how to apply modifications of the global model to particular sites. We evaluate the feasibility of the approach by surveying currently available settings and APIs in the most important SNS.

Taxonomy for Social Network Data Types from the Viewpoint of Privacy and User Control

The growing relevance and usage intensity of Online Social Networks (OSNs) along with the accumulation of a large amount of user data has led to privacy concerns among researchers and end users. Despite a large body of research addressing OSN privacy issues, little differentiation of data types on social network sites is made and a generally accepted classification and terminology for such data is missing, hence leading to confusion in related discussions. This paper proposes a taxonomy for data types on OSNs based on a thorough literature analysis and a conceptualization of typical OSN user activities. It aims at clarifying discussions among researchers, benefiting comparisons of data types within and across OSNs and at educating the end user about characteristics and implications of OSN data types. The taxonomy is evaluated by applying it to four major OSNs.

Maintaining a Consistent Representation of Self across Multiple Social Networking Sites -- A Data-centric Perspective

The rising pervasiveness and use of sensitive data on Social Networking Sites (SNS) requires careful consideration of ones privacy while using such sites. Also, users faced with a multitude of online contacts from various areas of life feel the need to create multiple representations of self and keeping them consistent. The difficulty of this task is compounded by the use of multiple SNS. We argue that for maintaining a consistent representation of self across multiple SNS, it needs to be carefully analyzed how personal attributes, which make up the online identity, are implemented and stored on each site. In this paper, we analyze criteria to classify how attributes and their values are implemented at SNS. Then, we present a structured approach to transform attribute values for use on multiple SNS. We evaluate the approach by applying it to selected attributes of major SNS.

Privacy in Social Networks: Existing Challenges and Proposals for Solutions

The significant change in our social lives and communication habits caused by the rise of Social Network Sites (SNSs) has not only brought along benefits but is also accompanied by privacy threats. In this paper we present our research efforts on SNS privacy and social identity management. First, we outline the results of an empirical study showing significant discrepancies between Facebook users’ actual privacy settings and their perception as well as their preferences. Based on this evident need for improving privacy, we present a novel conceptualization of privacy that serves as the basis for tackling the challenges. Finally, the paper provides an overview of solutions we developed as part of our research efforts on privacy in SNSs.