dc.contributor.author |
Danny, MN
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|
dc.contributor.author |
Kogeda, OP
|
|
dc.contributor.author |
Mtsweni, Jabu S
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|
dc.date.accessioned |
2017-07-28T09:02:16Z |
|
dc.date.available |
2017-07-28T09:02:16Z |
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dc.date.issued |
2016-11 |
|
dc.identifier.citation |
Danny, M.N., Kogeda, O.P. and Mtsweni, J.S. 2016. A context-sensitive trust model for online social networking. 3rd IEEE International Conference on Advances in Computing, Communications & Engineering (ICACCE-2016), 28-29 November 2016, Durban, South Africa, p. 337-342 |
en_US |
dc.identifier.isbn |
978-1-5090-2576-3 |
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dc.identifier.uri |
http://hdl.handle.net/10204/9339
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|
dc.description |
Copyright: 2016 IEEE. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, kindly consult the publisher's website |
en_US |
dc.description.abstract |
In Social Networking Sites (SNSs), users tend to accept friend requests and share their personal information based on intuitive trust levels. Mistakenly trusting and sharing private information with malicious users may lead to a wide variety of privacy attacks. In the quest to address this problem, this paper proposes a context-sensitive trust model. The proposed trust model was designed using fuzzy logic theory and implemented using MATLAB. Contrary to existing trust models, the context-sensitive trust model does not rely on the transitive relationship but rather addresses the subjectivity aspect of trust in SNSs. Furthermore, the proposed trust model allows social network users to evaluate the degree of trustworthiness of an unknown user based on their own trust rules and contextual parameters found on the user’s profile. The context-sensitive trust model shows an accuracy of 80% in evaluating the trustworthiness of an unknown user. As a result, the presented trust model could help social network users to evaluate the trustworthiness of an unknown user before mistakenly trusting and sharing private information with malicious users. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
IEEE |
en_US |
dc.relation.ispartofseries |
Worklist;18154 |
|
dc.subject |
Context-sensitive |
en_US |
dc.subject |
Social networking sites |
en_US |
dc.subject |
Fuzzy logic |
en_US |
dc.subject |
Trustor |
en_US |
dc.subject |
Trustee |
en_US |
dc.subject |
Trust model |
en_US |
dc.title |
A context-sensitive trust model for online social networking |
en_US |
dc.type |
Conference Presentation |
en_US |
dc.identifier.apacitation |
Danny, M., Kogeda, O., & Mtsweni, J. S. (2016). A context-sensitive trust model for online social networking. IEEE. http://hdl.handle.net/10204/9339 |
en_ZA |
dc.identifier.chicagocitation |
Danny, MN, OP Kogeda, and Jabu S Mtsweni. "A context-sensitive trust model for online social networking." (2016): http://hdl.handle.net/10204/9339 |
en_ZA |
dc.identifier.vancouvercitation |
Danny M, Kogeda O, Mtsweni JS, A context-sensitive trust model for online social networking; IEEE; 2016. http://hdl.handle.net/10204/9339 . |
en_ZA |
dc.identifier.ris |
TY - Conference Presentation
AU - Danny, MN
AU - Kogeda, OP
AU - Mtsweni, Jabu S
AB - In Social Networking Sites (SNSs), users tend to accept friend requests and share their personal information based on intuitive trust levels. Mistakenly trusting and sharing private information with malicious users may lead to a wide variety of privacy attacks. In the quest to address this problem, this paper proposes a context-sensitive trust model. The proposed trust model was designed using fuzzy logic theory and implemented using MATLAB. Contrary to existing trust models, the context-sensitive trust model does not rely on the transitive relationship but rather addresses the subjectivity aspect of trust in SNSs. Furthermore, the proposed trust model allows social network users to evaluate the degree of trustworthiness of an unknown user based on their own trust rules and contextual parameters found on the user’s profile. The context-sensitive trust model shows an accuracy of 80% in evaluating the trustworthiness of an unknown user. As a result, the presented trust model could help social network users to evaluate the trustworthiness of an unknown user before mistakenly trusting and sharing private information with malicious users.
DA - 2016-11
DB - ResearchSpace
DP - CSIR
KW - Context-sensitive
KW - Social networking sites
KW - Fuzzy logic
KW - Trustor
KW - Trustee
KW - Trust model
LK - https://researchspace.csir.co.za
PY - 2016
SM - 978-1-5090-2576-3
T1 - A context-sensitive trust model for online social networking
TI - A context-sensitive trust model for online social networking
UR - http://hdl.handle.net/10204/9339
ER -
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en_ZA |