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Decentralized privacy-aware collaborative filtering of smart spammers in a telecommunication network

Lookup NU author(s): Dr Muhammad Azad, Dr Samiran Bag

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Abstract

© 2017 ACM. Smart spammers and telemarketers circumvent the standalone spam detection systems by making low rate spamming activity to a large number of recipients distributed across many telecommunication operators. The collaboration among multiple telecommunication operators (OPs) will allow operators to get rid of unwanted callers at the early stage of their spamming activity. The challenge in the design of collaborative spam detection system is that OPs are not willing to share certain information about behaviour of their users/customers because of privacy concerns. Ideally, operators agree to share certain aggregated statistical information if collaboration process ensures complete privacy protection of users and their network data. To address this challenge and convince OPs for the collaboration, this paper proposes a decentralized reputation aggregation protocol that enables OPs to take part in a collaboration process without use of a trusted third party centralized system and without developing a predefined trust relationship with other OPs. To this extent, the collaboration among operators is achieved through the exchange of cryptographic reputation scores among OPs thus fully protects relationship network and reputation scores of users even in the presence of colluders. We evaluate the performance of proposed protocol over the simulated data consisting of five collaborators. Experimental results revealed that proposed approach outperforms standalone systems in terms of true positive rate and false positive rate.


Publication metadata

Author(s): Azad MA, Bag S

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: SAC '17: Proceedings of the Symposium on Applied Computing

Year of Conference: 2017

Pages: 1711-1717

Online publication date: 03/04/2017

Acceptance date: 02/04/2016

Publisher: ACM

DOI: 10.1145/3019612.3019792

Library holdings: Search Newcastle University Library for this item

ISBN: 9781450344869


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