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N-Combat: A Nuisance Call Combating Framework for Internet Telephony

  • CNRS SAMOVAR UMR 5157

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

Nuisance calls are not only irritating and annoying but also pose several security threats. Nuisance calls can be classified into live, recorded, scam and silent spam calls. Unlike traditional communication networks, users identities over the web cannot be asserted as they are created without any subscription contract or identification proof. To address this issue, we present N-Combat framework that effectively combats automated and manually generated nuisance calls over web communication services. In N-Combat the caller's reputation is computed using total call duration, out-degree, feedback received and the reliability of communicating participants. To address the dynamic behavior of callers, the concept of a dual time window is introduced. Furthermore, the framework uses a watchdog mechanism to combat whitewashing attacks that allows spammers to shed their bad reputation and reenter the network with a new identity.

Original languageEnglish
Title of host publicationProceedings - 17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications and 12th IEEE International Conference on Big Data Science and Engineering, Trustcom/BigDataSE 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages112-117
Number of pages6
ISBN (Print)9781538643877
DOIs
Publication statusPublished - 5 Sept 2018
Externally publishedYes
Event17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications and 12th IEEE International Conference on Big Data Science and Engineering, Trustcom/BigDataSE 2018 - New York, United States
Duration: 31 Jul 2018 → 3 Aug 2018

Publication series

NameProceedings - 17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications and 12th IEEE International Conference on Big Data Science and Engineering, Trustcom/BigDataSE 2018
ISSN (Electronic)2324-9013

Conference

Conference17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications and 12th IEEE International Conference on Big Data Science and Engineering, Trustcom/BigDataSE 2018
Country/TerritoryUnited States
CityNew York
Period31/07/18 → 3/08/18

Keywords

  • Behavioral Trust
  • Nuisance Call
  • Real-Time Web Communication
  • Reputation
  • SPAM
  • SPIT

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