Privacy Concerns for Photo Sharing in Online Social Networks

2015 ◽  
Vol 19 (2) ◽  
pp. 58-63 ◽  
Author(s):  
Kaitai Liang ◽  
Joseph K. Liu ◽  
Rongxing Lu ◽  
Duncan S. Wong
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Privacy Concerns ◽  
Photo Sharing

scholarly journals The Dark Side of Using Online Social Networks

2021 ◽  
Vol 29 (6) ◽  
pp. 0-0
Keyword(s):  
Social Networks ◽  
Social Exchange ◽  
Online Social Networks ◽  
Dark Side ◽  
Future Research ◽  
Structured Interviews ◽  
Negative Effects ◽  
Privacy Concerns ◽  
Low Performance ◽  
Rich Spectrum

Research on online social networks (OSNs) has focused overwhelmingly on their benefits and potential, with their negative effects overlooked. This study builds on the limited existing work on the so-called ‘dark side’ of using OSNs. The authors conducted a systematic review of selected databases and identified 46 negative effects of using OSNs from the users’ perspective, which is a rich spectrum of users’ negative experiences. This article then proposed nomenclature and taxonomy for the dark side of using OSNs by grouping these negative effects into six themes: cost of social exchange, cyberbullying, low performance, annoying content, privacy concerns and security threats. This study then conducted structured interviews with experts to confirm the sense-making and validity of the proposed taxonomy. This study discusses the confirmed taxonomy and outlines directions for future research.

Control of photo sharing over Online Social Networks

2014 ◽  
Author(s):  
Kaihe Xu ◽  
Yuanxiong Guo ◽  
Linke Guo ◽  
Yuguang Fang ◽  
Xiaolin Li
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Photo Sharing

Energy Consumption of Photo Sharing in Online Social Networks

2014 ◽  
Author(s):  
Fatemeh Jalali ◽  
Chrispin Gray ◽  
Arun Vishwanath ◽  
Robert Ayre ◽  
Tansu Alpcan ◽  
...  
Keyword(s):  
Social Networks ◽  
Energy Consumption ◽  
Online Social Networks ◽  
Photo Sharing

scholarly journals Systematic Evaluation of LibreSocial—A Peer-to-Peer Framework for Online Social Networks

2020 ◽  
Vol 12 (9) ◽  
pp. 140 ◽  
Author(s):  
Newton Masinde ◽  
Liat Khitman ◽  
Iakov Dlikman ◽  
Kalman Graffi
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Peer To Peer ◽  
System Stability ◽  
Systematic Evaluation ◽  
P2p Networks ◽  
Privacy Concerns ◽  
Benchmark Tests ◽  
Random Behavior ◽  
Overall Performance

Peer-to-peer (P2P) networks have been under investigation for several years now, with many novel mechanisms proposed as is shown by available articles. Much of the research focused on showing how the proposed mechanism improves system performance. In addition, several applications were proposed to harness the benefits of the P2P networks. Of these applications, online social networks (OSNs) raised much interest particularly because of the scalability and privacy concerns with centralized OSNs, hence several proposals are in existence. However, accompanying studies on the overall performance of the P2P network under the weight of the OSN applications outside simulations are very few, if any. In this paper, the aim is to undertake a systematic evaluation of the performance of a P2P framework for online social networks called LibreSocial. Benchmark tests are designed, taking into account the random behavior of users, effects of churn on system stability and effect of replication factor. We manage to run benchmark tests for up to 2000 nodes and show the performance against costs of the system in general. From the results it is evident that LibreSocial’s performance is capable of meeting the needs of users.

Trust-Based Privacy-Preserving Photo Sharing in Online Social Networks

2019 ◽  
Vol 21 (3) ◽  
pp. 591-602 ◽  
Author(s):  
Lei Xu ◽  
Ting Bao ◽  
Liehuang Zhu ◽  
Yan Zhang
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Privacy Preserving ◽  
Photo Sharing

scholarly journals A Model of Perception of Privacy, Trust, and Self-Disclosure on Online Social Networks

Entropy ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. 772 ◽  
Author(s):  
Nemec Zlatolas ◽  
Welzer ◽  
Hölbl ◽  
Heričko ◽  
Kamišalić
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Structural Equation ◽  
Online Survey ◽  
Equation Modeling ◽  
Privacy Risk ◽  
Self Disclosure ◽  
Privacy Concerns ◽  
Significant Relationships ◽  
Privacy Issues

Online Social Networks are used widely, raising new issues in terms of privacy, trust, and self-disclosure. For a better understanding of these issues for Facebook users, a model was built that includes privacy value, privacy risk, trust, privacy control, privacy concerns, and self-disclosure. A total of 602 respondents participated in an online survey, and structural equation modeling was used to evaluate the model. The findings indicate significant relationships between the constructs in this study. The model from our study contributes new knowledge to privacy issues, trust and self-disclosure on Online Social Networks for other researchers or developers of online social networks.

A Secure and Privacy-Preserving Approach to Protect User Data across Cloud based Online Social Networks

2021 ◽  
pp. 560-585
Author(s):  
Neelu khare ◽  
Kumaran U.
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Data Access ◽  
Privacy Preserving ◽  
Security And Privacy ◽  
Sensitive Information ◽  
Privacy Concerns ◽  
Attribute Based Encryption ◽  
User Data ◽  
Trapdoor Function

The tremendous growth of social networking systems enables the active participation of a wide variety of users. This has led to an increased probability of security and privacy concerns. In order to solve the issue, the article defines a secure and privacy-preserving approach to protect user data across Cloud-based online social networks. The proposed approach models social networks as a directed graph, such that a user can share sensitive information with other users only if there exists a directed edge from one user to another. The connectivity between data users data is efficiently shared using an attribute-based encryption (ABE) with different data access levels. The proposed ABE technique makes use of a trapdoor function to re-encrypt the data without the use of proxy re-encryption techniques. Experimental evaluation states that the proposed approach provides comparatively better results than the existing techniques.

ASEAN users' privacy concerns and security in using online social networks

2017 ◽  
Vol 9 (1) ◽  
pp. 84
Author(s):  
Huy Le Quang ◽  
Avinash Shankaranarayanan ◽  
Quyen Ha Tran ◽  
Roger Epworth ◽  
Thanh Kim Cao ◽  
...  
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Privacy Concerns
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