Toward an optimal social network defense against Sybil attacks

2007 ◽  
Author(s):  
Haifeng Yu ◽  
Phillip B. Gibbons ◽  
Michael Kaminsky
Keyword(s):  
Social Network ◽  
Network Defense ◽  
Sybil Attacks

scholarly journals SybilLimit: A Near-Optimal Social Network Defense Against Sybil Attacks

2010 ◽  
Vol 18 (3) ◽  
pp. 885-898 ◽  
Author(s):  
Haifeng Yu ◽  
Phillip B. Gibbons ◽  
Michael Kaminsky ◽  
Feng Xiao
Keyword(s):  
Social Network ◽  
Network Defense ◽  
Sybil Attacks

scholarly journals SybilLimit: A Near-Optimal Social Network Defense against Sybil Attacks

2008 ◽  
Author(s):  
Haifeng Yu ◽  
Phillip B. Gibbons ◽  
Michael Kaminsky ◽  
Feng Xiao
Keyword(s):  
Social Network ◽  
Network Defense ◽  
Sybil Attacks

scholarly journals Sybil-proof Answer Querying Mechanism

2020 ◽  
Author(s):  
Yao Zhang ◽  
Xiuzhen Zhang ◽  
Dengji Zhao
Keyword(s):  
Social Network ◽  
Question Answering ◽  
Cost Minimization ◽  
Impossibility Results ◽  
Reward Mechanisms ◽  
Sybil Attacks

We study a question answering problem on a social network, where a requester is seeking an answer from the agents on the network. The goal is to design reward mechanisms to incentivize the agents to propagate the requester's query to their neighbours if they don't have the answer. Existing mechanisms are vulnerable to Sybil-attacks, i.e., an agent may get more reward by creating fake identities. Hence, we combat this problem by first proving some impossibility results to resolve Sybil-attacks and then characterizing a class of mechanisms which satisfy Sybil-proofness (prevents Sybil-attacks) as well as other desirable properties. Except for Sybil-proofness, we also consider cost minimization for the requester and agents' collusions.

scholarly journals Salmon: Robust Proxy Distribution for Censorship Circumvention

2016 ◽  
Vol 2016 (4) ◽  
pp. 4-20
Author(s):  
Frederick Douglas ◽  
Weiyang Pan ◽  
Matthew Caesar ◽  
Keyword(s):  
Social Network ◽  
Streaming Video ◽  
Internet Usage ◽  
The Internet ◽  
Covert Channels ◽  
Proxy Servers ◽  
The Public ◽  
Low Performance ◽  
Censorship Circumvention ◽  
Sybil Attacks

Abstract Many governments block their citizens’ access to much of the Internet. Simple workarounds are unreliable; censors quickly discover and patch them. Previously proposed robust approaches either have non-trivial obstacles to deployment, or rely on low-performance covert channels that cannot support typical Internet usage such as streaming video. We present Salmon, an incrementally deployable system designed to resist a censor with the resources of the “Great Firewall” of China. Salmon relies on a network of volunteers in uncensored countries to run proxy servers. Although any member of the public can become a user, Salmon protects the bulk of its servers from being discovered and blocked by the censor via an algorithm for quickly identifying malicious users. The algorithm entails identifying some users as especially trustworthy or suspicious, based on their actions. We impede Sybil attacks by requiring either an unobtrusive check of a social network account, or a referral from a trustworthy user.

The social network

2013 ◽  
Vol 44 (2) ◽  
pp. 22
Author(s):  
ALAN ROCKOFF
Keyword(s):  
Social Network ◽  
The Social

Abstract #1249: Novel Use of Physician Social Network Data to Map the Gap in the Endocrinology Workforce

2015 ◽  
Vol 21 ◽  
pp. 301
Author(s):  
Armand Krikorian ◽  
Lily Peng ◽  
Zubair Ilyas ◽  
Joumana Chaiban
Keyword(s):  
Social Network ◽  
Network Data ◽  
Social Network Data

Correlating Personality and Actual Phone Usage

2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  
Keyword(s):  
Big Data ◽  
Social Network ◽  
Mobile Phone ◽  
Mobile Phones ◽  
Self Report ◽  
Psychological Variables ◽  
New Approach ◽  
Report Data ◽  
Self Report Data ◽  
Voice Calls

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.

Extraverts Have Larger Social Network Layers

2011 ◽  
Vol 32 (3) ◽  
pp. 161-169 ◽  
Author(s):  
Thomas V. Pollet ◽  
Sam G. B. Roberts ◽  
Robin I. M. Dunbar
Keyword(s):  
Social Network ◽  
Social Relationships ◽  
Outer Layer ◽  
Network Size ◽  
Emotional Intensity ◽  
Emotional Closeness ◽  
Network Layer ◽  
Network Layers ◽  
Social Network Size

Previous studies showed that extraversion influences social network size. However, it is unclear how extraversion affects the size of different layers of the network, and how extraversion relates to the emotional intensity of social relationships. We examined the relationships between extraversion, network size, and emotional closeness for 117 individuals. The results demonstrated that extraverts had larger networks at every layer (support clique, sympathy group, outer layer). The results were robust and were not attributable to potential confounds such as sex, though they were modest in size (raw correlations between extraversion and size of network layer, .20 < r < .23). However, extraverts were not emotionally closer to individuals in their network, even after controlling for network size. These results highlight the importance of considering not just social network size in relation to personality, but also the quality of relationships with network members.

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