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".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Masalah SPAM IM (Instant Messaging) yang juga dikenali sebagai SPIM menjadi cabaran sejak beberapa tahun kebelakangan ini. Kaedah anti-SPAM semasa tidak begitu sesuai untuk SPIM kerana perbezaan dalam infrastruktur sistem dan ciri-ciri antara IM dan perkhidmatan e-mel. Untuk menghapuskan SPIM dengan berkesan, kami mencadangkan kaedah kedudukan amanah dalam kertas ini. Mekanisme untuk membina rangkaian reputasi, reputasi global dan algoritma kedudukan amanah tempatan, pengurusan reputasi dan kaedah penapisan SPIM dibentangkan. Eksperimen di bawah lima mod rawatan dan peningkatan algoritma juga diperkenalkan. Eksperimen menunjukkan bahawa kaedah yang dicadangkan adalah berdaya tahan untuk menangani serangan SPIM di bawah beberapa model ancaman.
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Salinan
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
Salinan
@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},}
Salinan
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 -