通信学报2016，Vol.37Issue(9)：82-91,10.DOI:10.11959/j.issn.1000-436x.2016180
在线社交网络中Spam相册检测方案
Detecting Spam albums in online social network
摘要
Abstract
A supervised learning solution to detect Spam albums instead of spammers in Photo Spam was proposed. Spe-cifically, the characteristics of Photo Spam and the differences between Photo Spam and traditional Spam were analyzed. Then 12 features which were extracted easily and calculated efficiently were constructed based on the analysis. Next a classification model was built with a dataset of 2 356 labeled albums to identify Spam albums. The model provided ex-cellent performance with true positive rates of Spam albums and normal albums, reaching 100%and 98.2%respectively. Finally, the detection model were applied to 315 115 unlabeled albums and detected 89 163 spam albums with a true posi-tive rate of 97.2%.关键词
社交网络安全/Photo Spam/Spam检测/人人网Key words
social network security/Photo Spam/Spam detection/RenRen分类
信息技术与安全科学引用本文复制引用
吕少卿,张玉清,刘东航,张光华..在线社交网络中Spam相册检测方案[J].通信学报,2016,37(9):82-91,10.基金项目
国家自然科学基金资助项目（No.61572460, No.61272481, No.61303239）；物联网信息安全技术北京市重点实验室开放课题基金资助项目；中国博士后科学基金资助项目（No.2015M582622）Foundation Items:The National Natural Science Foundation of China (No.61572460, No.61272481, No.61303239), Open Fund of Beijing Key Laboratory of IOT Information Security Technology, China Postdoctoral Science Foundation (No.2015M582622) （No.61572460, No.61272481, No.61303239）
