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Lookup NU author(s): Dr Samiran Bag, Professor Feng Hao
This is the authors' accepted manuscript of an article that has been published in its final definitive form by IEEE, 2020.
For re-use rights please refer to the publisher's terms and conditions.
IEEE Nuisance or unsolicited calls and instant messages come at any time in a variety of different ways. These calls would not only exasperate recipients with the unwanted ringing, impacting their productivity, but also lead to a direct financial loss to users and service providers. Telecommunication Service Providers (TSPs) often employ standalone detection systems to classify call originators as spammers or non-spammers using their behavioral patterns. These approaches perform well when spammers target a large number of recipients of one service provider. However, professional spammers try to evade the standalone systems by intelligently reducing the number of spam calls sent to one service provider, and instead distribute calls to the recipients of many service providers. Naturally, collaboration among service providers could provide an effective defense, but it brings the challenge of privacy protection and system resources required for the collaboration process. In this paper, we propose a novel decentralized collaborative system named privy for the effective blocking of spammers who target multiple TSPs. More specifically, we develop a system that aggregates the feedback scores reported by the collaborating TSPs without employing any trusted third party system, while preserving the privacy of users and collaborators.
Author(s): Ajmal M, Bag S, Tabassum S, Hao F
Publication type: Article
Publication status: Published
Journal: IEEE Transactions on Emerging Topics in Computing
Year: 2020
Volume: 8
Issue: 2
Pages: 313-327
Print publication date: 01/04/2020
Online publication date: 10/11/2017
Acceptance date: 10/10/2017
Date deposited: 18/12/2017
ISSN (electronic): 2168-6750
Publisher: IEEE
URL: https://doi.org/10.1109/TETC.2017.2771251
DOI: 10.1109/TETC.2017.2771251
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