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Social Computing and Incentivized Sharing

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Page 1: Social Computing and Incentivized Sharing. Group Members UT Dallas Murat Kantarcioglu Alain Bensoussan (UT Dallas) Nathan Berg Bhavani Thuraisingham University

Social Computing and Incentivized Sharing

Page 2: Social Computing and Incentivized Sharing. Group Members UT Dallas Murat Kantarcioglu Alain Bensoussan (UT Dallas) Nathan Berg Bhavani Thuraisingham University

Group Members

• UT Dallas• Murat Kantarcioglu• Alain Bensoussan (UT Dallas)• Nathan Berg • Bhavani Thuraisingham

• University of Michigan• Lada Adamic

• UMBC• Yelena Yesha• Joel Sachs• Anupam Joshi • Tim Finin

• UTSA• Shouhuai Xu • Ravi Sandhu

• Purdue• Elisa Bertino • Chris Clifton• Gabriel Ghinita• Ningui Li

Page 3: Social Computing and Incentivized Sharing. Group Members UT Dallas Murat Kantarcioglu Alain Bensoussan (UT Dallas) Nathan Berg Bhavani Thuraisingham University

social networks & the AISL

SOCIALNETWORKS

UT Dallas

privacy and securityprivacy and security

incentivized sharing

incentivized sharing

information dissemination and filtering

information dissemination and filtering

Page 4: Social Computing and Incentivized Sharing. Group Members UT Dallas Murat Kantarcioglu Alain Bensoussan (UT Dallas) Nathan Berg Bhavani Thuraisingham University

social networks and information sharing

• distributing information• determining who should receive information

• pulling information• information filtering (e.g. digg, FriendFeed)

• securing information• propagation of trust and distrust (reputation management)• enhance trustworthiness of cryptographic key infrastructure

• incentivizing sharing• individuals more or less likely to share with close contacts

Page 5: Social Computing and Incentivized Sharing. Group Members UT Dallas Murat Kantarcioglu Alain Bensoussan (UT Dallas) Nathan Berg Bhavani Thuraisingham University

acquiring: novelty and community structure

• data quality/provenance• identify circular intelligence through

proximity in social networks

• temporal & source information can be mapped onto social network

relevancetrustincentive for sharing

novelty

information flow path

individual receiving information

Page 6: Social Computing and Incentivized Sharing. Group Members UT Dallas Murat Kantarcioglu Alain Bensoussan (UT Dallas) Nathan Berg Bhavani Thuraisingham University

sharing & acquiring: open participation

Knows

Knowledge iN

Page 7: Social Computing and Incentivized Sharing. Group Members UT Dallas Murat Kantarcioglu Alain Bensoussan (UT Dallas) Nathan Berg Bhavani Thuraisingham University

open participation: information or noise?

Knowledge In ``Knowledge search is like oozing out knowledge in human brains to the Internet. People who know something better than others can present their know-how, skills or knowledge''

NHN CEO Chae Hwi-young

“(It is) the next generation of search… (it) is a kind of collective brain -- a searchable database of everything everyone knows. It's a culture of generosity. The fundamental belief is that everyone knows something.”

-- Eckart Walther (Yahoo Research)

Page 8: Social Computing and Incentivized Sharing. Group Members UT Dallas Murat Kantarcioglu Alain Bensoussan (UT Dallas) Nathan Berg Bhavani Thuraisingham University
Page 9: Social Computing and Incentivized Sharing. Group Members UT Dallas Murat Kantarcioglu Alain Bensoussan (UT Dallas) Nathan Berg Bhavani Thuraisingham University

Network analysis can be used to determine expertise

Preferred Helper: ‘just better’

Preferred Helper: ‘best available’

Page 10: Social Computing and Incentivized Sharing. Group Members UT Dallas Murat Kantarcioglu Alain Bensoussan (UT Dallas) Nathan Berg Bhavani Thuraisingham University

and study competitive information sharing

• Java Forum: asker -> replier• Task CN: submitter -> winner

Page 11: Social Computing and Incentivized Sharing. Group Members UT Dallas Murat Kantarcioglu Alain Bensoussan (UT Dallas) Nathan Berg Bhavani Thuraisingham University

structure of complex networks• heterogeneous

connectivity and participation

• robustness• connectivity• propagation of

misinformation from compromised nodes

Page 12: Social Computing and Incentivized Sharing. Group Members UT Dallas Murat Kantarcioglu Alain Bensoussan (UT Dallas) Nathan Berg Bhavani Thuraisingham University

Secure social networks: research goal

• We ask and address the following two questions:• How should we exploit social computing/networks for security

purposes (e.g., assured information sharing)?

• How should we secure social computing/networks?

Page 13: Social Computing and Incentivized Sharing. Group Members UT Dallas Murat Kantarcioglu Alain Bensoussan (UT Dallas) Nathan Berg Bhavani Thuraisingham University

Security by social computing

• protect cryptographic security

• detect and deter malicious players

• trustworthy and survivable storage

• reputation management

• reliable and secure information dissemination

Page 14: Social Computing and Incentivized Sharing. Group Members UT Dallas Murat Kantarcioglu Alain Bensoussan (UT Dallas) Nathan Berg Bhavani Thuraisingham University

Security for social computing

• anonymous & accountable social computing

• privacy-preserving social computing

• inferring private data from social connections

• secure incentive mechanisms

• manipulation-resistant social computing

• data quality/provenance

• obscuring identity and connections

Page 15: Social Computing and Incentivized Sharing. Group Members UT Dallas Murat Kantarcioglu Alain Bensoussan (UT Dallas) Nathan Berg Bhavani Thuraisingham University

prior work

• Secure social networks & privacy:• Network robustness: (poster: Xu et al. “Generalized Epidemic Threshold, with Applications”)• Key signing: “Exploiting social networks for threshold signing” (AsiaCCS'08)• Privacy and trust in information sharing (Kantarcioglu UTDCS-21-08 )

• Information sharing & filtering:• Inferring expertise in Q&A forums (Adamic et al. WWW07&08)• Using social networks to detect conflicts of interest (Joshi et. al: WWW2006, ACM Tweb,

2008)• online information sharing structure (blogs,twitter)

• Adamic (WI 2005,ICWSM07&08)• Finin, Joshi (WebKDD,ICWSM07&08,+ many more)

• data quality and providence (detecting spam blogs) (AAAI 2006,ICWSM07,TREC2006)

• Social and semantic computing:• blending the social & semantic (Sachs AAAI 07 workshop)

Page 16: Social Computing and Incentivized Sharing. Group Members UT Dallas Murat Kantarcioglu Alain Bensoussan (UT Dallas) Nathan Berg Bhavani Thuraisingham University

current research

• social networks as a filtering & aggregation tool• Yelena Yesha, Lada Adamic, Anupam Joshi, Tim Finin

• understand the role of social networks (e.g. FriendFeed, blogs) in information diffusion

• sentiment analysis and network structure

• security for and from social networks• Shouhuai Xu, Ravi Sandhu

• Understanding properties of social networks under attack

• Using insights to make social computing more robust and secure

• incentivized sharing in social networks• Murat Kantarcioglu, Lada Adamic

• Experiments: effect of social connections on information sharing (peer recognition) and ability to recognize poor information sources

• Social engineering (phishing, etc.)

Page 17: Social Computing and Incentivized Sharing. Group Members UT Dallas Murat Kantarcioglu Alain Bensoussan (UT Dallas) Nathan Berg Bhavani Thuraisingham University

social networks & the AISL

SOCIALNETWORKS

UT Dallas

privacy and securityprivacy and security

incentivized sharing

incentivized sharing

information dissemination and filtering

information dissemination and filtering