CPSFS: A Credible Personalized Spam Filtering Scheme by Crowdsourcing
Joint Authors
Liu, Xin
Zou, Pingjun
Zhang, Weishan
Zhou, Jiehan
Dai, Changying
Wang, Feng
Zhang, Xiaomiao
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-12-27
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Abstract EN
Email spam consumes a lot of network resources and threatens many systems because of its unwanted or malicious content.
Most existing spam filters only target complete-spam but ignore semispam.
This paper proposes a novel and comprehensive CPSFS scheme: Credible Personalized Spam Filtering Scheme, which classifies spam into two categories: complete-spam and semispam, and targets filtering both kinds of spam.
Complete-spam is always spam for all users; semispam is an email identified as spam by some users and as regular email by other users.
Most existing spam filters target complete-spam but ignore semispam.
In CPSFS, Bayesian filtering is deployed at email servers to identify complete-spam, while semispam is identified at client side by crowdsourcing.
An email user client can distinguish junk from legitimate emails according to spam reports from credible contacts with the similar interests.
Social trust and interest similarity between users and their contacts are calculated so that spam reports are more accurately targeted to similar users.
The experimental results show that the proposed CPSFS can improve the accuracy rate of distinguishing spam from legitimate emails compared with that of Bayesian filter alone.
American Psychological Association (APA)
Liu, Xin& Zou, Pingjun& Zhang, Weishan& Zhou, Jiehan& Dai, Changying& Wang, Feng…[et al.]. 2017. CPSFS: A Credible Personalized Spam Filtering Scheme by Crowdsourcing. Wireless Communications and Mobile Computing،Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1205621
Modern Language Association (MLA)
Liu, Xin…[et al.]. CPSFS: A Credible Personalized Spam Filtering Scheme by Crowdsourcing. Wireless Communications and Mobile Computing No. 2017 (2017), pp.1-9.
https://search.emarefa.net/detail/BIM-1205621
American Medical Association (AMA)
Liu, Xin& Zou, Pingjun& Zhang, Weishan& Zhou, Jiehan& Dai, Changying& Wang, Feng…[et al.]. CPSFS: A Credible Personalized Spam Filtering Scheme by Crowdsourcing. Wireless Communications and Mobile Computing. 2017. Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1205621
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1205621