A Collaborative Defending Scheme Based on Social Computing Against IM Malicious Codes

LIU Xin; JIA Chun-fu; SHI Le-yi; XIN Zhao-jun

doi:10.3969/j.issn.0372-2112.2013.06.014

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A Collaborative Defending Scheme Based on Social Computing Against IM Malicious Codes

更新时间：2025-07-16

- A Collaborative Defending Scheme Based on Social Computing Against IM Malicious Codes
- Acta Electronica Sinica Vol. 41, Issue 6, Pages: 1130-1139(2013)
- 作者机构：
  
  1. 南开大学信息技术科学学院,天津,300071
  2. 中国石油大学(华东)计算机与通信工程学院,山东,青岛,266580
  4. 南京大学计算机软件新技术国家重点实验室,江苏,南京,210093
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.60973141, No.61272423);National Key Basic Research Development Plan (No.2013CB834204);Research Fund for the Doctoral Program of Higher Education of China资助项目 (No.20100031110030);Fundamental Research Funds for the Central Universities (No.13CX02027A)
- DOI：10.3969/j.issn.0372-2112.2013.06.014
  CLC： TP393.08
- Published：2013
- 稿件说明：
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LIU Xin, JIA Chun-fu, SHI Le-yi, et al. A Collaborative Defending Scheme Based on Social Computing Against IM Malicious Codes[J]. Acta Electronica Sinica, 2013, 41(6): 1130-1139.
DOI：

LIU Xin, JIA Chun-fu, SHI Le-yi, et al. A Collaborative Defending Scheme Based on Social Computing Against IM Malicious Codes[J]. Acta Electronica Sinica, 2013, 41(6): 1130-1139. DOI： 10.3969/j.issn.0372-2112.2013.06.014.

摘要

即时通信(IM

Instant Messaging)网络已成为恶意代码传播的主要途径之一

本文提出了一种基于社会计算的IM恶意代码防御机制:利用用户与好友之间的社会信任关系

通过社会计算集成网络中多种反病毒软件的检测结果及用户的安全经验形成群体智慧

从而构成一个分布式协作防御机制.该机制利用即时通信网络平台

并依据好友间的交互行为计算动态信任

在IM客户端部署方案

用户之间实时相互协作抵御通过IM传播的恶意代码.实验结果表明

在大多数用户接受好友警告的情况下

即时通信网络中所有节点最终都被免疫

提高了整个社会网络防御IM恶意代码的能力.

Abstract

IM(Instant Messaging) is used widely

which is an avenue for the propagation of IM malicious codes.To restrain IM malicious codes

we proposed a collaborative defending scheme based on social computing.Users can obtain experience after they browse through web pages and run malicious codes.Based on the trust between a user and his friends

through social computing

the experience and the checking results about IM malicious codes from different antivirus softwares on hosts are collected to result in collective intelligence.The platform used in the scheme is the social network formed by IM tool.Dynamic trusts on friends are calculated according to massages from friends.The scheme is a distributed system which is implemented in clients.Users collaborate with their friends to slow down the propagation of IM malicious codes.The experiments show all nodes in the social network are immune at last in the case when most users accept the warning

and the defending capacity of the whole social network is enhanced.

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