期刊文献+

短信木马病毒检测模型的创建

Establishment of Trojan Virus Detection Model for SMS
下载PDF
导出
摘要 随着经济水平、科技水平的提高,智能设备日益普及。智能手机、平板电脑等智能终端应用程序丰富多彩,一方面方便了人们交流、生活,另一方面提高了学习、工作效率。随之而来的是数据安全受到威胁。手机中木马病毒给用户带来诸如经济、隐私等方面损失的事件屡见不鲜。为了更好保护用户利益防止中毒,需要搭建一个木马病毒检测体系,防患于未然。笔者重点介绍了移动终端短信木马病毒检测模型的创建。 With the improvement of the economic level and the level of science and technology,the popularization of intelligent equipment is becoming more and more widespread.Smart phone applications such as smart phones and tablet computers are colorful,on the one hand,convenient for people to communicate and live,and on the other hand,improve their learning and working efficiency.It follows that the threat of data security is threatened.The Trojan virus in the mobile phone brings the loss to the user such as the economy,the privacy and so on.In order to better protect the interests of the users to prevent poisoning,we need to build a Trojan virus detection system to prevent it.The author focuses on the creation of a mobile terminal SMS trojan virus detection model.
作者 王东 王峥 Wang Dong;Wang Zheng(School of Information Engineering,Nanjing Xiaozhuang University,Nanjing Jiangsu 211171,China)
出处 《信息与电脑》 2018年第5期220-221,共2页 Information & Computer
基金 江苏省高等学校大学生实践创新训练计划项目"移动端数据安全算法研究"(项目编号:201611460061X)
关键词 短信 木马病毒 分类器 SMS Trojan virus:classifier
  • 相关文献

参考文献3

二级参考文献14

  • 1张爱丽,刘广利,刘长宇.基于SVM的多类文本分类研究[J].情报杂志,2004,23(9):6-7. 被引量:7
  • 2中华人民共和国工业与信息化部.2014年通信运营业统计公报[OL],2015,01.
  • 3D.D.Lewis.Naive(Bayes)at forty:The Independence Assumption in Information Retrieval.In Proceedings ofthe 10th European Conference on Machine Learning.New York,1998,4-15.
  • 4T.Joachims.Text categorization with support vector machines:Learning With Many Relevant Features.In Proceedings of 10th European Conference Off Machine Learning,1998,137-142.
  • 5Y.yang.An evaluation ofstatistical approaches to text categorization.Information Retrieval,1999,l(1):76-88.
  • 6Van G,David P,Reisslein M.Traffic characteristicsof H.264/AVC variable bit rate video[J].IEEE Communications Magazine,2008,46(11):164-174.
  • 7W.Lee,S.Stolfo.A Framework for Constructing Features and Modelsfor Intrusion Detection Systems[J].ACM Transactions on Informationand System Security.2000(4):227-261.
  • 8Trappey Amy J C,Lin Simon C I,Wang Albert C L.Using neural network categorization method to develop an innovative knowledge management technology for patent document classification[C].Proceedings of the9th International Conference on Computer Supported Cooperative Work in Design.Coventry,United Kingdom,2005,2:830-835.
  • 9Cover T M,Hart P E.Nearest neighbor pattern classification[J].IEEE Transactions on Information Theory.1968,IT-13(1):21-27.
  • 10柴春梅,李翔,林祥.基于改进KNN算法实现网络媒体信息智能分类[J].计算机技术与发展,2009,19(1):1-4. 被引量:7

共引文献4

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部