intrusion error 中文意思是什麼
intrusion error
解釋
侵擾誤差-
The developing trend of intrusion detection technique is also summarized in the first part of the thesis. the intrusion detection system supporting ipv4, ipv6 and transition mechanism is designed. by analyzing the capture procedure and bottleneck of linux operating system we point out that using technology of napi 、 memory mapping can increase the capturing efficiency and detection accuracy which result in the low rate of error report, lose report
論文在綜合使用入侵檢測技術的基礎上，開展了以下幾個方面的研究工作: 1 、簡明扼要地介紹了入侵檢測技術的概念、基本模型、歷史和分類，總結了現有入侵檢測技術的發展趨勢，設計了支持ipv4 、 ipv6以及其過渡機制下的入侵檢測系統，並對linux系統中的捕包過程和瓶頸進行了分析，通過使用napi 、內存映射等技術提高了捕包效率和檢測的準確度，降低了誤報、漏報率。 -
The experimental results show that the method can effectively enhance the intrusion detection system detection rates and reduce their error rate, strengthen their immune system to resist the invasion
實驗表明該方法能有效提高入侵檢測系統的檢測率，降低其誤報率，增強計算機系統抵禦入侵及自身免疫能力。 -
Due to the some normal ids ' s low efficiency, high error report rate, bad self - security, this thesis has given out a new - type hybrid intrusion detection system ( hsids ) design with high efficiently, good self - security, combining the distrubited information gathering with the centralized managerment, and combining the nid and the hid. the detailed design scheme also has been presented. the hsids adopts the " black hole " hidden setting, greatly decreasing the posiblity for hacker to discover and attack the hsids
在hsids中，採用「黑洞」式隱形設置，可以大大減少hsids系統被黑客發現並攻擊的可能；系統採用的將nid與hid相結合的方式可降低入侵信息的漏報與誤報率；改進的檢測演算法提高了檢測引擎的速度；採用開放的檢測規則方便了系統的升級，提升了檢測能力； web方式的安全管理可以很好地控制整個監控網路的安全情況；被動防禦與主動防禦相結合更有效的防止了入侵者對系統的入侵。 -
The individual svm is prone to fail in the intrusion detection for the fragility of being attacked. this paper addresses a method using a support vector machines ensemble approach based on negative correlation learning for intrusion detection. using a correlation penalty term in the error function, the aggregate members can be accurate and diverse. and the evolutionary strategy is considered as the best way to automatically determine the individ. ual svms hyperparameters. at last we combine the results of all individual svms using ensemble technique. this distributed parallel detection can strengthen the robustness of the system. simulation results show the effectiveness of the method presented in this paper
在入侵檢測中使用單個的支持向量機容易因"單點失效"而危害系統安全.提出一種基於支持向量機集成的方法來進行入侵檢測.它採用負相關學習技術，在誤差項中使用相關性懲罰因子使得生成的分類器有更好的多樣性和精度;演算法採用進化策略來自動地確定個體支持向量機的超參數，避免了需要了解問題的先驗知識;最後，採用集成技術來組合個體支持向量機的檢測結果.模擬實驗表明這一方法有更好的檢測性能，並且這種分散式并行檢測方法有利於增加入侵檢測系統的魯棒性
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