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Subject: Computer Science (provided by Thomson Reuters)
Title:
基于复合分类模型的社交网络恶意用户识别方法
Alternative Title: malicious users identification in social network based on composite classification model
Author: 谈磊 ; 连一峰 ; 陈恺
Keyword: 新浪微博 ; 社交网络 ; 自动分类 ; 特征选择 ; 恶意用户
Source: 计算机应用与软件
Issued Date: 2012
Volume: 29, Issue:12, Pages:1-5,17
Indexed Type: CNKI ; CSCD ; WANFANG
Department: 中国科学院软件研究所信息安全国家重点实验室;中国科学院研究生院信息安全国家重点实验室;信息安全共性技术国家工程研究中心;信息网络安全公安部重点实验室(公安部第三研究所);
Sponsorship: 国家自然科学基金项目(61100226)|国家高技术研究发展计划项目(2011AA01A023)|北京市自然科学基金项目(4122085)|公安部三所开放基金课题(C10606)
Abstract: 社交网络近年发展迅速,微博类社交网络的用户数目及规模急剧增大的同时也带来了诸多安全问题,为了保护用户的隐私和个人、集体的利益,需要针对这些恶意行为进行识别并对恶意用户进行处理。提出一种采用复合分类模型对用户进行分类的方法,并开发了一个对微博类社交网络用户进行分类的系统。通过研究用户的属性和行为特点,比较属性间的相关性,从两方面兼顾了分类的准确性和效率。
English Abstract: While having sharp increase in users and network size as in social network of microblogging,the rapid development of social network in recent years also brings lots of security problems. To protect user privacy,personal and collective interest against violations of these security issues,it is necessary to identify malicious behaviours and deal with malicious users. This paper presents a new method for classifying social network users on composite classification model and develops a system to classify users in social network of microblogging.The system analyses many features of the properties and behaviours of users and compares the correlation between the properties,and is able to take the account of both accuracy and efficiency.
Language: 中文
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Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/15354
Appears in Collections:软件所图书馆_期刊论文

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Recommended Citation:
谈磊,连一峰,陈恺. 基于复合分类模型的社交网络恶意用户识别方法[J]. 计算机应用与软件,2012-01-01,29(12):1-5,17.
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