scholarly journals Privacy and Security Issues in Online Social Networks

2018 ◽  
Vol 10 (12) ◽  
pp. 114 ◽  
Author(s):  
Shaukat Ali ◽  
Naveed Islam ◽  
Azhar Rauf ◽  
Ikram Din ◽  
Mohsen Guizani ◽  
...  
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Virtual Communities ◽  
Service Providers ◽  
Security And Privacy ◽  
Security Issue ◽  
Sensitive Data ◽  
Privacy And Security ◽  
Security Issues ◽  
Social Sphere

The advent of online social networks (OSN) has transformed a common passive reader into a content contributor. It has allowed users to share information and exchange opinions, and also express themselves in online virtual communities to interact with other users of similar interests. However, OSN have turned the social sphere of users into the commercial sphere. This should create a privacy and security issue for OSN users. OSN service providers collect the private and sensitive data of their customers that can be misused by data collectors, third parties, or by unauthorized users. In this paper, common security and privacy issues are explained along with recommendations to OSN users to protect themselves from these issues whenever they use social media.

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 Artificial and Natural Topic Detection in Online Social Networks

2017 ◽  
Vol 10 (1) ◽  
pp. 80-98
Author(s):  
Sylvio Barbon Jr ◽  
Gabriel Marques Tavares ◽  
Guilherme Sakaji Kido
Keyword(s):  
Social Networks ◽  
Social Interactions ◽  
Online Social Networks ◽  
Topic Detection ◽  
Privacy And Security ◽  
Security Issues ◽  
Textual Content

Online Social Networks (OSNs), such as Twitter, offer attractive means of social interactions and communications, but also raise privacy and security issues. The OSNs provide valuable information to marketing and competitiveness based on users posts and opinions stored inside a huge volume of data from several themes, topics, and subjects. In order to mining the topics discussed on an OSN we present a novel application of Louvain method for TopicModeling based on communities detection in graphs by modularity. The proposed approach succeeded in finding topics in five different datasets composed of textual content from Twitter and Youtube. Another important contribution achieved was about the presence of texts posted by spammers. In this case, a particular behavior observed by graph community architecture (density and degree) allows the indication of a topic strength and the classification of it as natural or artificial. The later created by the spammers on OSNs.

scholarly journals Detecting misinformation in online social networks: A think-aloud study on user strategies

2019 ◽  
Vol 8 (4) ◽  
pp. 471-496
Author(s):  
Isabelle Freiling
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Ecological Validity ◽  
Qualitative Interviews ◽  
Think Aloud ◽  
False Information ◽  
User Perspective ◽  
Information Evaluation ◽  
Evaluation Strategies ◽  
Personal Accounts

Although online social networks (OSN) facilitate the distribution of misinformation, one way of reducing the spread of false information in OSN is for users to detect it. Building on the framework of how audiences act to authenticate information, this study provides a user perspective on which strategies people use in evaluating information in OSN. In 15 qualitative interviews, participants were asked to think aloud while evaluating whether the content of posts from their own newsfeeds and of interviewer-supplied posts was true or false. Their answers were analyzed to determine which evaluation strategies they used. Analyzing participants’ thoughts as they evaluate information is more reliable than directly asking participants which strategies they think they use. Results show that users’ strategies in information evaluation are searching for more information, knowledge of account or content carries the most weight, and every detail needs to fit. A comparison of strategy usage for posts from befriended versus unknown personal accounts as well as for posts from followed news outlets versus not followed news outlets shows that for posts from followed news outlets, knowledge of the account was the most-used strategy followed by knowledge of the content. For other types of posts, strategy usage varied more widely and depended on each post. This highlights the importance and possible higher ecological validity of research on posts from news outlets that users actually follow, as users’ experiences with previous posts seem to play a major role in how they go about evaluating information in new posts.

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.

Preventing Identity Disclosure in Social Networks Using Intersected Node

2016 ◽  
Vol 10 (3) ◽  
pp. 25-41 ◽  
Author(s):  
Amardeep Singh ◽  
Divya Bansal ◽  
Sanjeev Sofat
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Privacy And Security ◽  
Identity Disclosure ◽  
The Social ◽  
Confidential Data ◽  
Noise Nodes ◽  
Graphical Structure

Social networks like Facebook, Twitter, Pinterest etc. provide data of its users to the demanding organizations to better comprehend the quality of their potential clients. Publishing confidential data of social network users in its raw form raises several privacy and security concerns. Recently, some anonymization techniques have been developed to address these issues. In this paper, a technique to prevent identity disclosure through structure attacks has been proposed which not only prevents identity disclosure but also preserves utility of data published by online social networks. Algorithms have been developed by using noise nodes/edges with the consideration of introducing minimum change in the original graphical structure of social networks. The authors' work is unique in the sense that previous works are based on edge editing only but their proposed work protects against structure attacks using mutual nodes in the social network and the effectiveness of the proposed technique has been proved using APL (Average Path Length) and information loss as parameters.

Privacy and Security for Virtual Communities and Social Networks

2009 ◽  
Vol 1 (4) ◽  
pp. 21-32 ◽  
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.

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