The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Le problème du SPAM IM (Instant Messaging), également connu sous le nom de SPIM, est devenu un défi ces dernières années. Les méthodes anti-SPAM actuelles ne sont pas tout à fait adaptées au SPIM en raison des différences d'infrastructures système et de caractéristiques entre la messagerie instantanée et le service de messagerie. Afin d’éliminer efficacement le SPIM, nous proposons dans cet article une méthode de classement de confiance. Le mécanisme permettant de créer un réseau de réputation, les algorithmes de réputation mondiale et de classement de confiance locale, la gestion de la réputation et les méthodes de filtrage SPIM sont présentés. Les expériences sous cinq modes de traitement et l'amélioration des algorithmes sont également présentées. L'expérience montre que la méthode proposée est résiliente pour faire face aux attaques SPIM sous plusieurs modèles de menace.
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Jun BI, "A Trust Ranking Method to Prevent IM Spam" in IEICE TRANSACTIONS on Information,
vol. E92-D, no. 5, pp. 937-944, May 2009, doi: 10.1587/transinf.E92.D.937.
Abstract: The problem of IM (Instant Messaging) SPAM, also known as SPIM, has become a challenge in recent years. The current anti-SPAM methods are not quite suitable for SPIM because of the differences in system infrastructures and characteristics between IM and email service. In order to effectively eliminate SPIM, we propose a trust ranking method in this paper. The mechanism to build up reputation network, global reputation and local trust ranking algorithms, reputation management, and SPIM filtering methods are presented. The experiments under five treat modes and algorithms enhancement are also introduced. The experiment shows that the proposed method is resilient to deal with SPIM attacks under several threat models.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E92.D.937/_p
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@ARTICLE{e92-d_5_937,
author={Jun BI, },
journal={IEICE TRANSACTIONS on Information},
title={A Trust Ranking Method to Prevent IM Spam},
year={2009},
volume={E92-D},
number={5},
pages={937-944},
abstract={The problem of IM (Instant Messaging) SPAM, also known as SPIM, has become a challenge in recent years. The current anti-SPAM methods are not quite suitable for SPIM because of the differences in system infrastructures and characteristics between IM and email service. In order to effectively eliminate SPIM, we propose a trust ranking method in this paper. The mechanism to build up reputation network, global reputation and local trust ranking algorithms, reputation management, and SPIM filtering methods are presented. The experiments under five treat modes and algorithms enhancement are also introduced. The experiment shows that the proposed method is resilient to deal with SPIM attacks under several threat models.},
keywords={},
doi={10.1587/transinf.E92.D.937},
ISSN={1745-1361},
month={May},}
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TY - JOUR
TI - A Trust Ranking Method to Prevent IM Spam
T2 - IEICE TRANSACTIONS on Information
SP - 937
EP - 944
AU - Jun BI
PY - 2009
DO - 10.1587/transinf.E92.D.937
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E92-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2009
AB - The problem of IM (Instant Messaging) SPAM, also known as SPIM, has become a challenge in recent years. The current anti-SPAM methods are not quite suitable for SPIM because of the differences in system infrastructures and characteristics between IM and email service. In order to effectively eliminate SPIM, we propose a trust ranking method in this paper. The mechanism to build up reputation network, global reputation and local trust ranking algorithms, reputation management, and SPIM filtering methods are presented. The experiments under five treat modes and algorithms enhancement are also introduced. The experiment shows that the proposed method is resilient to deal with SPIM attacks under several threat models.
ER -