anomaly detection 中文意思是什麼

anomaly detection 解釋
異常發現
  • anomaly : n. 1. 不規則，反常（現象），異常，破格。2. 畸形物。
  • detection : n. 1. 探知；發現，發覺；敗露。2. 【化學】檢定，檢查；【電訊】檢波。
  1. The ids of the paper is network - based anomaly detection system. with the help of data mining technology, we bring forward a measure to describe the normal state of the network traffic and user behavior and extracting the useful rule from large network data. so we can establish the knowledge warehouse which describe the normal state of the network traffic and user behavior. the knowledge warehouse can be the standard in order to judge the normal state. we can find the dubitable connections according to account the state and anomly instances of connections

    論文在描述網路應用和用戶行為時採用數據挖掘技術從海量的網路數據中提取有用的規則，構建了一個描述正常狀態下的網路應用和用戶行為的規則集，這個規則集是用來判斷網路應用和用戶行為是否正常的標準，論文根據這個標準分析當前網路連接的異常情況，將可疑的連接找出來。
  2. We do research on the transitions between states of network protocol, the protocol misusage detection model based on markov chain, the framework of the ids technology and protocol anormity after we discuss the current technology. the main research contents of this paper include : research on transitions between states of network protocol and session process, protocol misuage and the anomaly detection model based on markov chain, the research of intrusion detection framework, more accurately model based on the characteristic of the network traffic and so on

    在分析了現有入侵檢測系統的基礎上，本文圍繞典型網路協議狀態轉換、基於馬爾可夫鏈的檢測模型、入侵檢測技術框架、以及協議異常等幾個方面展開深入研究，主要工作內容包括:典型網路協議轉換狀態的分析和會話過程的研究;基於馬爾可夫鏈的網路異常檢測模型;分散式的檢測架構;針對網路流量特徵而提出了精確的檢測模型等。
  3. A new anomaly detection technology in mobile ad - hoc networks

    網路異常入侵檢測技術
  4. Real - time anomaly detection of network intrusions

    網路入侵異常檢測的實時方法
  5. A method for data flow anomaly detection in oo programs

    一種檢查面向對象程序中數據流異常的方法
  6. A new anomaly detection model based on system call macro was presented

    提出了一個基於系統調用宏的異常檢測模型。
  7. A new anomaly detection model based on system call classification was presented

    提出了一個基於系統調用分類的異常檢測模型。
  8. In the sixth chapter the application of sequence models to anomaly detection is studied

    第六章是序列模式在異常檢測中的應用。
  9. In the filed of intrusion detection, anomaly detection is an important branch

    在入侵監測這個領域內，異常檢測是一個重要分支。
  10. A new two - layer markov chains anomaly detection model that operated on system call traces was presented

    提出了一個兩層馬爾可夫鏈異常入侵檢測模型。
  11. The construction of network traffic usage profile is first important in anomaly detection

    異常檢測的難點在於怎樣準確的描述用戶行為模式輪廓（ profile ） 。
  12. Describing normal behaviors is one of the difficulties that an anomaly detection system faces

    對正常行為的描述是異常檢測系統必須要解決好的核心問題之一。
  13. The intrusion detection system employs negative selection algorithm to create detectors, optimizes them continuously and maintains efficient memory dete ctors. so it takes the advantages of anomaly detection and misuse detection, overcomes the natural shortcoming of them and can identify known intrusion and novel intrusion in computer systems

    它同時兼備了異常檢測法和誤用檢測法的優點，克服了兩者固有的缺陷，因此可以識別任何已知或未知的本地主機上的異常行為模式和網路系統中的異常通信模式。
  14. Naids is the first data mining based anomaly detection system, the first intrusion detection system which lower false positive rate by classification engineering, the first intrusion detection system which put forward sliding windows techniques to carry out incremental, on - line mining

    Naids是第一個基於數據挖掘方法的異常檢測系統，是第一個通過分類引擎來降低誤報率的入侵檢測系統，是第一個提出滑動窗口技術實施在線增量式挖掘的入侵檢測系統。
  15. To detect both known and unknown intrusion patterns, the system introduces a blended frame that makes use of both misuse detection approach and anomaly detection approach. the one of the highlight of the architecture is introduction of data mining technique, and the other is introduction of genetic algorithms. the ids uses data mining algorithms to abstract key features of system runtime status from security audit data, and it uses genetic algorithm to select the feature subset to reduce the amount of data that must be obtained from running processes and classified

    本文陳述了所研究系統的主要特點和技術：將智能體（ agent ）技術應用於入侵檢測系統，解決了傳統入侵檢測系統的集中式解決方案的弊病，充分利用網路資源協同完成入侵檢測任務；利用基於主機和基於網路的數據源，形成一種完整的混合型的結構，從而能收集到更加全面的信息；使用了異常檢測技術和誤用檢測技術，採用一種混合型的結構，既能檢測已知的攻擊模式，又能發現新的攻擊模式。
  16. The first chapter surveys the state - of - the - art of intrusion detection and the related problems. the second chapter provides the details of intrusion detection techniques, in particularly, it introduces two concepts ( network - based ids ( nids ) and host - based ids ( hids ) ), and the distributed ids. besides, this chapter proposes three intrusion detection methods ( misuse detection, anomaly detection and integrality test ), and discusses the applications of the artificial neural network technology 、 expert system technology 、 and pattern reasoning technology in the ids

    第二章討論入侵檢測技術基礎，介紹了基於網路的入侵檢測系統（ ndis ）和基於主機的入侵檢測系統（ hdis ）的概念，對分散式入侵檢測系統也進行了相關介紹;討論了三種入侵檢測辦法，包括誤用檢測（ misusedetection ） 、異常檢測（ anomalydetection ）和完整性檢測，介紹了人工神經網路技術、專家系統技術以及模式推理技術在ids中的應用。
  17. First, realized a wegener - willie distribute based network traffic anomaly detection algorithm. we make use of wegener - willie distribute to analyze the inherent time - frequency distribution characteristics of the traffic flow signal. then according to the experience of analysis on historical flow, we construct a normal flow training sample aggregation and a abnormal flow training sample aggregation

    通過魏格納-威利分佈分析網路流量信號在時頻分佈上所反映出的內在特點，根據歷史流量的經驗構造正常流量和異常流量兩個訓練樣本空間，通過k最近鄰分類演算法將帶檢測流量信號的時頻分佈與訓練樣本進行比較，完成對檢測樣本的自動分類識別。
  18. Illuminated by human immune system, this paper presents a continuous learning model for intrusion defense that follows the principle of how bacterin stimulates the immune system to generate antibody. this model presents how to get the important “ bacterin ” to add to the database, which is used to do signature matching and anomaly detection, and thus protect system from unknown intrusion ( virus )

    受到疫苗和人體免疫系統工作方式的啟發，本文提出一種入侵預防系統模型，它模擬人體注射疫苗后免疫系統產生相應抗體抵抗抗原的機理:通過設置捕獲器捕獲最新的外部入侵病毒並將其加入病毒特徵庫，通過特徵匹配和異常檢測兩種方式檢測識別病毒並將其隔離消除。
  19. Band selection methods are more proper for hardware realization and the last method is chosen for dimensionality reduction of hyperspectral image processed by the hardware platform. secondly, rx, gmrf and sem, three representational algorithms of anomaly detection are studied

    其次，研究了具有代表性的三種奇異檢測演算法: rx演算法、基於高斯馬爾可夫隨機場模型（ gmrf ）的檢測演算法和基於隨機最大期望（ sem ）分類的檢測演算法。
  20. The person who constructs the system relies on their intuition and experience to choose the tolerance of a certain static to measure anomaly detection

    當前，建造一個有效的入侵檢測系統是個巨大的知識工程。系統構造員依賴他們直覺和經驗選擇某種統計標準度量異常檢測。
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