N2TM

a new node to trust matrix method for spam worker defense in crowdsourcing environments

Bin Ye, Yan Wang*, Mehmet Orgun, Quan Z. Sheng

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

Abstract

To defend against spam workers in crowdsourcing environments, the existing solutions overlook the fact that a spam worker with guises can easily bypass the defense. To alleviate this problem, in this paper, we propose a Node to Trust Matrix method (N2TM) that represents a worker node in a crowdsourcing network as an un-manipulable Worker Trust Matrix (WTM) for identifying the worker’s identity. In particular, we first present a crowdsourcing trust network consisting of requester nodes, worker nodes, and transaction-based edges. Then, we construct WTMs for workers based on the trust network. A WTM consists of trust indicators measuring the extent to which a worker is trusted by different requesters in different sub-networks. Moreover, we show the un-manipulable property and the usable property of a WTM that are crucial for identifying a worker’s identity. Furthermore, we leverage deep learning techniques to predict a worker’s identity with its WTM as input. Finally, we demonstrate the superior performance of our proposed N2TM in identifying spam workers with extensive experiments.

Original languageEnglish
Title of host publicationService-Oriented Computing
Subtitle of host publication17th International Conference, ICSOC 2019, Proceedings
EditorsSami Yangui, Ismael Bouassida Rodriguez, Khalil Drira, Zahir Tari
Place of PublicationSwitzerland
PublisherSpringer
Pages119-134
Number of pages16
ISBN (Electronic)9783030337025
ISBN (Print)9783030337018
DOIs
Publication statusPublished - 2019
Event17th International Conference on Service-Oriented Computing, ICSOC 2019 - Toulouse, France
Duration: 28 Oct 201931 Oct 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11895 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th International Conference on Service-Oriented Computing, ICSOC 2019
CountryFrance
CityToulouse
Period28/10/1931/10/19

Keywords

  • Crowdsourcing
  • Spam worker identification
  • Trust

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  • Cite this

    Ye, B., Wang, Y., Orgun, M., & Sheng, Q. Z. (2019). N2TM: a new node to trust matrix method for spam worker defense in crowdsourcing environments. In S. Yangui, I. Bouassida Rodriguez, K. Drira, & Z. Tari (Eds.), Service-Oriented Computing: 17th International Conference, ICSOC 2019, Proceedings (pp. 119-134). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11895 LNCS). Switzerland: Springer. https://doi.org/10.1007/978-3-030-33702-5_10