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  • 标题:Using Unobtrusive Techniques for Detecting Leakage of Data
  • 本地全文:下载
  • 作者:Shailaja B. Jadhav ; Prachi Joshi
  • 期刊名称:International Journal of Computer Science and Network
  • 印刷版ISSN:2277-5420
  • 出版年度:2013
  • 卷号:2
  • 期号:3
  • 页码:91-95
  • 出版社:IJCSN publisher
  • 摘要:While doing business, there are situations when someimportant information or data should be handed over tosome third parties. The data important to organization mustbe secured but the third parties are not that careful aboutthe data. So there is possibility that the data gets leaked.Here in this paper we are considering the chances that thethird party is responsible for the leakage. We propose dataallocation strategies (across the agents) that improvethe probability of identifying leakages. There are someavailable techniques like watermarking, perturbation used toidentifying data leakage, but those are having fewdrawbacks. So we are trying to detect the leakage by using atechnique called unobtrusive. This technique will give usresults in many prospective to find out leakage of theimportant data
  • 关键词:Guilty agent; Data Allocation Problem; Agent;Guilt Model; Fake Object; Optimization
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