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dc.contributor.authorAzad, Muhammad
dc.contributor.authorPerera, Charith
dc.contributor.authorBag, Samiran
dc.contributor.authorBarhamgi, Mahmoud
dc.contributor.authorHao, Feng
dc.date.accessioned2020-07-06T14:05:47Z
dc.date.available2020-07-06T14:05:47Z
dc.date.issued2020
dc.identifier.citationAzad, M., Perera, C., Bag, S., Barhamgi, M., and Hao, F. (2020). 'Privacy-preserving crowd-sensed trust aggregation in the user-centeric internet of people networks'. ACM Transactions on Cyber-Physical Systems, 5(1).en_US
dc.identifier.issn2378-962X
dc.identifier.doi10.1145/3446431
dc.identifier.urihttp://hdl.handle.net/10545/624948
dc.description.abstractToday we are relying on the Internet technologies for various types of services ranging from personal communication to the entertainment. The online social networks (Facebook, twitter, youtube) has seen an increase in subscribers in recent years developing a social network among people termed as the Internet of People. In such a network, subscribers use the content disseminated by other subscribers. The malicious users can also utilize such platforms for spreading the malicious and fake content that would bring catastrophic consequences to a social network if not identified on time. People crowd-sensing on the Internet of people system has seen a prospective solution for the large scale data collection by leveraging the feedback collections from the people of the internet that would not only help in identifying malicious subscribers of the network but would also help in defining better services. However, the human involvement in crowd-sensing would have challenges of privacy-preservation, intentional spread of false high score about certain user/content undermining the services, and assigning different trust scores to the peoples of the network without disclosing their trust weights. Therefore, having a privacy-preserving system for computing trust of people and their content in the network would play a crucial role in collecting high-quality data from the people. In this paper, a novel trust model is proposed for evaluating the trust of the people in the social network without compromising the privacy of the participating people. The proposed systems have inherent properties of the trust weight assignment to a different class of user i.e. it can assign different weights to different users of the network, has decentralized setup, and ensures privacy properties under the malicious and honest but curious adversarial model. We evaluated the performance of the system by developing a prototype and applying it to different online social network dataset.en_US
dc.description.sponsorshipN/Aen_US
dc.language.isoenen_US
dc.publisherACMen_US
dc.relation.urlhttps://dl.acm.org/doi/abs/10.1145/3390860en_US
dc.subjectprivacy-preservationen_US
dc.subjectcrowdsourcingen_US
dc.subjectsecurityen_US
dc.titlePrivacy-preserving crowd-sensed trust aggregation in the user-centeric internet of people networksen_US
dc.typeArticleen_US
dc.identifier.eissn2378-9638
dc.contributor.departmentUniversity of Derbyen_US
dc.contributor.departmentCardiff Universityen_US
dc.contributor.departmentUniversity of Warwicken_US
dc.contributor.departmentUniversite Claude Bernard Lyonen_US
dc.identifier.journalACM Transactions on Cyber-Physical Systemsen_US
dcterms.dateAccepted2020-03-01
dc.author.detail786678en_US


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