false negative rate meaning in Chinese
假阴性率
Examples
- False negative rate
假阴性率漏诊率 - I have been using spamassassin for several months , and i am happy to report that in my experience , the false positive and false negative rates are extremely low
我使用spamassassin已经有一段时间了，所以我很高兴地说，根据我的体验，弄错正、负的几率极其低。 - The essence of edid is to set up a normal behavior fuzzy sub collection a on the basis of watching the normal system transfer of the privilege process , and set up a fuzzy sub collection b with real time transfer array , then detect with the principle of minimum distance in fuzzy discern method the innovation point of this paper is : put forward the method of edid , can not only reduce efficiently false positive rate and false negative rate , also make real time intrusion detection to become possibility ; have independent and complete character database , according to the classification of monitoring program , design normal behavior and anomaly behavior etc . , have raised the strongness of ids ; use tree type structure to preservation the character database , have saved greatly stock space ; in detection invade , carry out frequency prior principle , prior analysis and handling the behavior feature of high frequency in information table , have raised efficiency and the speed of detection , make real time intrusion detection to become possibility ; have at the same time realized anomaly intrusion detection and misuse intrusion detection , have remedied deficiency of unitary detection method
这种方法的实质是在监控特权进程的正常系统调用基础上建立正常行为模糊子集a ，用检测到的实时调用序列建立模糊子集b ，然后用模糊识别方法中的最小距离原则进行检测。本文的创新点是：通过对特权进程的系统调用及参数序列的研究，提出了基于euclidean距离的入侵检测方法edid ，不仅能有效降低漏报率和误报率，而且使实时入侵检测成为可能；设计有独立而完整的特征数据库，根据被监控程序的类别，分别设计正常行为、异常行为等，提高了检测系统的强健性和可伸缩性；特征数据库按树型结构存储，大大节省了存储空间；在检测入侵时，实行频度优先原则，优先分析和处理信息表中的高频度行为特征，提高检测的速度和效率，使实时入侵检测成为可能；同时实现了异常入侵检测和误用入侵检测，弥补了单一检测方法的不足。 - In order to withstand more and more frequent compound network attacks and hacker commitment of distribution , multiobjective , multistage nowadays , improve intrusion detection efficiency under the circumstance of high band width and large - scale network , decrease false negative rate and shorten detection time , incorporating advanced machine learning techniques into ids is already a well - known thought
为了对付目前越来越频繁出现的分布式、多目标、多阶段的组合式网络攻击和黑客行为,提高在高带宽、大规模网络环境下入侵检测的效率、降低漏报率和缩短检测时间,把先进的机器学习方法引入到ids中来已成为一种共识。