scholarly journals An explainable assistant for multiuser privacy

2022 ◽  
Vol 36 (1) ◽  
Author(s):  
Francesca Mosca ◽  
Jose Such
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Personal Information ◽  
Moral Values ◽  
User Studies ◽  
Trade Off ◽  
Multiple Users ◽  
Extensive Evaluation ◽  
Personal Assistant

AbstractMultiuser Privacy (MP) concerns the protection of personal information in situations where such information is co-owned by multiple users. MP is particularly problematic in collaborative platforms such as online social networks (OSN). In fact, too often OSN users experience privacy violations due to conflicts generated by other users sharing content that involves them without their permission. Previous studies show that in most cases MP conflicts could be avoided, and are mainly due to the difficulty for the uploader to select appropriate sharing policies. For this reason, we present ELVIRA, the first fully explainable personal assistant that collaborates with other ELVIRA agents to identify the optimal sharing policy for a collectively owned content. An extensive evaluation of this agent through software simulations and two user studies suggests that ELVIRA, thanks to its properties of being role-agnostic, adaptive, explainable and both utility- and value-driven, would be more successful at supporting MP than other approaches presented in the literature in terms of (i) trade-off between generated utility and promotion of moral values, and (ii) users’ satisfaction of the explained recommended output.

Online Social Networks: Why We Disclose

2010 ◽  
Vol 25 (2) ◽  
pp. 109-125 ◽  
Author(s):  
Hanna Krasnova ◽  
Sarah Spiekermann ◽  
Ksenia Koroleva ◽  
Thomas Hildebrand
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Information Disclosure ◽  
Structural Equation ◽  
Personal Information ◽  
Equation Model ◽  
Self Disclosure ◽  
Network Provider ◽  
Privacy Calculus ◽  
Privacy Risks

On online social networks such as Facebook, massive self-disclosure by users has attracted the attention of Industry players and policymakers worldwide. Despite the Impressive scope of this phenomenon, very little Is understood about what motivates users to disclose personal Information. Integrating focus group results Into a theoretical privacy calculus framework, we develop and empirically test a Structural Equation Model of self-disclosure with 259 subjects. We find that users are primarily motivated to disclose Information because of the convenience of maintaining and developing relationships and platform enjoyment. Countervailing these benefits, privacy risks represent a critical barrier to information disclosure. However, users’ perception of risk can be mitigated by their trust in the network provider and availability of control options. Based on these findings, we offer recommendations for network providers.

Privacy and Security for Virtual Communities and Social Networks

2013 ◽  
pp. 19-31 ◽  
Author(s):  
Georgios Michaelides ◽  
Gábor Hosszú
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Virtual Communities ◽  
Personal Information ◽  
Rapid Development ◽  
Virtual Community ◽  
Privacy And Security ◽  
Internet Privacy ◽  
Large Audience ◽  
Privacy Risks

The importance of the virtual communities’ privacy and security problems comes into prominence by the rapid development of online social networks. This article presents the multiple threats currently plaguing the virtual world, Internet privacy risks, and recommendations and countermeasures to avoid such problems. New generations of users feel comfortable publishing their personal information and narrating their lives. They are often unaware how vulnerable the data in their public profiles are, which a large audience daily accesses. A so-called digital friendship is built among them. Such commercial and social pressures have led to a number of privacy and security risks for social network members. The article presents the most important vulnerabilities and suggests protection methods and solutions that can be utilized according to the threat. Lastly, the authors introduce the concept of a privacy-friendly virtual community site, named CWIW, where privacy methods have been implemented for better user protection.

scholarly journals Privacy study on images uploaded in social networks

2018 ◽  
Vol 7 (1.7) ◽  
pp. 142
Author(s):  
Hemalatha D ◽  
Almas Begum ◽  
Alex David S
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Mobile Devices ◽  
Public Interest ◽  
Online Social Networks ◽  
Personal Information ◽  
Personal Characteristics ◽  
The Social ◽  
Study Results ◽  
Privacy Settings

Presently, the growth of Social media is explosive among the users. Increasingly developed social websites like Flickr, Facebook, Google+, LinkedIn etc permits the users to create, share and view the post. Confidentiality is a leading factor required in Social Networks. The social users upload their photos to the social sites that intend to gain public interest for social purposes. The exposure of personal information leads to slipping process like identity stealing, morphing etc, which are against the privacy violations. Relied upon the personal characteristics of users, the privacy settings of each user should be defined. In this paper, a relational study about the privacy settings in Online Social structure is examined. Initiated by the importance of social networks among the social users and their behavior towards Online Social Networks, which is followed by the privacy techniques suggested by other researchers are explored. At last, an overview about the merits and demerits of privacy designs and schemes for the user-uploaded images are presented. The study results a new privacy system that controls the confidential information from being accessed from different devices, including mobile devices and computers.

A Graph-Based Approach to Model Privacy and Security Issues of Online Social Networks

2013 ◽  
pp. 184-205 ◽  
Author(s):  
Luca Caviglione ◽  
Mauro Coccoli ◽  
Alessio Merlo
Keyword(s):  
Social Networks ◽  
Social Organization ◽  
Online Social Networks ◽  
Personal Information ◽  
Security Policies ◽  
Privacy And Security ◽  
Web Based ◽  
Security Issues ◽  
Cultural Phenomenon ◽  
Usage Patterns

With millions of users, Online Social Networks (OSNs) are a huge cultural phenomenon. Put briefly, they are characterized by: i) an intrinsic sharing of personal information, ii) a rich set of features to publish, organize and retrieve contents, especially for emphasizing their social organization, iii) the interaction with a heterogeneous set of devices, e.g., ranging from desktops to mobile appliances, and iv) the mix of Web-based paradigms and sophisticated methodologies for processing data. However, if not properly implemented, or without effective security policies, i) – iv) could lead to severe risks in terms both of privacy and security. In this perspective, this chapter analyzes the major peculiarities of OSN platforms, the preferred development methodologies, and usage patterns, also by taking into account how personal information can be exploited to conduct malicious actions. Then, a graph-based modeling approach is introduced to reveal possible attacks, as well as to elaborate the needed countermeasures or (automated) checking procedures.

Evolving Cyber Threats, Combating Techniques, and Open Issues in Online Social Networks

2021 ◽  
pp. 219-235
Author(s):  
Sanjeev Rao ◽  
Anil Kumar Verma ◽  
Tarunpreet Bhatia
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Personal Information ◽  
Machine Learning Algorithms ◽  
Privacy And Security ◽  
Future Directions ◽  
Professional Groups ◽  
Cyber Threats ◽  
Common Interests ◽  
Cyber Crimes

Online social networks (OSNs) are renowned powerful web tools that allow worldwide users to connect with their friends, families, professional groups, and social circle through social interaction for sharing common interests. With the proliferation, ease, and efficacy of OSNs, these are becoming an essential tool for communication. But many OSN users innocently uncover their personal information such as their home address, phone numbers, email id, etc. that can be used by the malicious user to perform various kind for cyber-crimes like cyber-bullying, spamming, click-jacking, identity theft, phishing, distrust, fake profiles, spreading malicious content, etc. This chapter presents a review of various privacy and security threats/attacks associated with OSN users and recommended combating techniques based on data-mining and machine learning algorithms. Also, the future directions for upcoming researchers in this field are suggested.

Modeling Unintended Personal-Information Leakage from Multiple Online Social Networks

2011 ◽  
Vol 15 (3) ◽  
pp. 13-19 ◽  
Author(s):  
Danesh Irani ◽  
Steve Webb ◽  
Kang Li ◽  
Calton Pu
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Personal Information ◽  
Information Leakage
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