Privacy Breach Analysis in Social Networks

2013 ◽  
pp. 63-77 ◽  
Author(s):  
Frank Nagle
Keyword(s):  
Social Networks ◽  
Privacy Breach

Centralized to Decentralized Social Networks

2016 ◽  
pp. 37-54
Author(s):  
Maryam Qamar ◽  
Mehwish Malik ◽  
Saadia Batool ◽  
Sidra Mehmood ◽  
Asad W. Malik ◽  
...  
Keyword(s):  
Social Networks ◽  
Traffic Flow ◽  
Network Traffic ◽  
Online Social Networks ◽  
Research Work ◽  
Central Authority ◽  
Potential Threat ◽  
Privacy Breach ◽  
Natural Solution

This work covers the research work on decentralization of Online Social Networks (OSNs), issues with centralized design are studied with possible decentralized solutions. Centralized architecture is prone to privacy breach, p2p architecture for data and thus authority decentralization with encryption seems a possible solution. OSNs' users grow exponentially causing scalability issue, a natural solution is decentralization where users bring resources with them via personal machines or paid services. Also centralized services are not available unremittingly, to this end decentralization proposes replication. Decentralized solutions are also proposed for reliability issues arising in centralized systems and the potential threat of a central authority. Yet key to all problems isn't found, metadata may be enough for inferences about data and network traffic flow can lead to information on users' relationships. First issue can be mitigated by data padding or splitting in uniform blocks. Caching, dummy traffic or routing through a mix of nodes can be some possible solutions to the second.

scholarly journals Preventing malicious accounts based on mining with steganography in online

2018 ◽  
Vol 7 (3.3) ◽  
pp. 615
Author(s):  
Ms K. Karpaga Priyaa ◽  
Keerthipati Lahari ◽  
V Vasundhara ◽  
C Saranya
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Personal Information ◽  
Experimental Results ◽  
Virtual Identity ◽  
Privacy Threats ◽  
Privacy Breach ◽  
On Line ◽  
The Creation ◽  
The Way

On-line Social Networks (OSNs) are progressively exerting consequences on the way communication takes place among people through sites such as Twitter, Facebook, Google+ and LinkedIn, possessing millions of users. The Online Social Networks’ (OSN) users face security-privacy threats such as Profile cloning, privacy breach and malware attacks. By these attacks, the fake user steals the virtual identity of the original user which they use to interact with other online users. To prevent these attacks, the proposed system uses Steganography which is the process of hiding information within other non-secret text or data. Our proposed system utilizes Steganography by implementing Watermarking technique which hides a secret text inside an image invisibly. Moreover the system avoids the leakage of personal information and prevents the creation of fake accounts. Experimental results show that the proposed technique can effectively detect and prevent creating malicious accounts in comparison with the techniques reported previously.  

Multilayer Social Networks

2016 ◽  
Author(s):  
Mark E. Dickison ◽  
Matteo Magnani ◽  
Luca Rossi
Keyword(s):  
Social Networks ◽  
Multilayer Social Networks

Hostility and Perceptions of Support in Ambiguous Social Interactions

2006 ◽  
Vol 27 (2) ◽  
pp. 108-115 ◽  
Author(s):  
Ana-Maria Vranceanu ◽  
Linda C. Gallo ◽  
Laura M. Bogart
Keyword(s):  
Social Support ◽  
Social Networks ◽  
Information Processing ◽  
Social Interactions ◽  
Social Information Processing ◽  
Perceived Social Support ◽  
Social Information ◽  
Inverse Association ◽  
Processing Bias ◽  
Information Processing Bias

The present study investigated whether a social information processing bias contributes to the inverse association between trait hostility and perceived social support. A sample of 104 undergraduates (50 men) completed a measure of hostility and rated videotaped interactions in which a speaker disclosed a problem while a listener reacted ambiguously. Results showed that hostile persons rated listeners as less friendly and socially supportive across six conversations, although the nature of the hostility effect varied by sex, target rated, and manner in which support was assessed. Hostility and target interactively impacted ratings of support and affiliation only for men. At least in part, a social information processing bias could contribute to hostile persons' perceptions of their social networks.

Sign in / Sign up

Export Citation Format

Share Document