首页> 外文会议>Recent Advances in Computing and Software Systems (RACSS), 2012 International Conference on >Theft detection of computers using MAC address by map-reduce programming model on a cluster
【24h】

Theft detection of computers using MAC address by map-reduce programming model on a cluster

机译:通过群集上的映射减少编程模型使用MAC地址对计算机进行盗窃检测

获取原文
获取原文并翻译 | 示例

摘要

Users of mobile devices face the problem of guarding their gadgets every time they are outdoors. Theft of laptops is the 3rd most frequent computer crime after virus and hacking. The really scary part is that according to FBI, 1 in 10 laptops purchased today will be stolen within the next 12 months. Sadly, only 3 percent will be returned. Occasionally, laptops and mobile devices are also lost due to accidents. It is a herculean task to manually locate the whereabouts of stolen or lost laptops. In this paper, we are proposing an automatic method of detecting stolen or lost hand-helds where the processing is carried out in a clustered network. The method is suitable only when the lost or stolen hand-held accesses monitored network from any location and perhaps under a new owner. The method involves logging network activity and searching through the logged information. Searching for lost hand-held in logged data will take substantial amount of time if processed in a single system. We propose a Map-Reduce based cluster processing for speedy processing of the logged data. The system is developed and will be setup in Manipal University Campus with an efficient identification method for the satisfaction of stolen or lost laptop users and network administrators.
机译:移动设备的用户每次在户外时都面临着保护其小工具的问题。笔记本电脑盗窃是继病毒和黑客之后第三大最常见的计算机犯罪。根据FBI的说法,真正令人恐惧的是,在未来12个月内,今天购买的笔记本电脑中有十分之一会被盗。可悲的是,将只退还3%。有时,笔记本电脑和移动设备也会由于事故而丢失。手动查找笔记本电脑被盗或丢失的下落是一项艰巨的任务。在本文中,我们提出了一种自动检测被盗或丢失的手持设备的方法,其中处理是在群集网络中进行的。该方法仅在丢失或被盗的手持设备从任何位置(可能是在新所有者下)访问受监视网络时才适用。该方法涉及记录网络活动并搜索记录的信息。如果在单个系统中进行处理,则搜索丢失的已记录数据中的手持设备将花费大量时间。我们提出了一种基于Map-Reduce的集群处理方法,用于快速处理记录的数据。该系统已开发,并将在马尼帕尔大学校园中进行设置,并采用一种有效的识别方法来满足被盗或丢失的笔记本电脑用户和网络管理员的需求。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号