Advanced API Security 會使用 Google 機器學習演算法建構的模型，偵測 API 的安全威脅。這些模型會預先使用真實的 API 流量資料集 (包括您目前的流量資料，如果已啟用) 進行訓練，其中包含已知的安全威脅。因此，模型會學習辨識異常的 API 流量模式 (例如 API 網頁擷取和異常狀況)，並根據類似模式將事件歸類在一起。
[[["容易理解","easyToUnderstand","thumb-up"],["確實解決了我的問題","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["難以理解","hardToUnderstand","thumb-down"],["資訊或程式碼範例有誤","incorrectInformationOrSampleCode","thumb-down"],["缺少我需要的資訊/範例","missingTheInformationSamplesINeed","thumb-down"],["翻譯問題","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["上次更新時間：2025-08-21 (世界標準時間)。"],[[["\u003cp\u003eThis page provides information about Advanced API Security features in Apigee and Apigee hybrid.\u003c/p\u003e\n"],["\u003cp\u003eAdvanced API Security uses detection rules, including machine learning models and descriptive rules, to identify unusual patterns in API traffic that might indicate malicious activity.\u003c/p\u003e\n"],["\u003cp\u003eThe detection rules include machine learning models like "Advanced API Scraper" and "Advanced Anomaly Detection," which are trained on real API traffic data to identify patterns indicative of security threats.\u003c/p\u003e\n"],["\u003cp\u003eOther detection rules include "Brute Guessor," "Flooder," "OAuth Abuser," "Robot Abuser," "Static Content Scraper," and "TorListRule", each targeting specific types of potential API abuse.\u003c/p\u003e\n"],["\u003cp\u003eSecurity incidents, which are groups of similar events representing security threats, can be triggered by one or multiple detection rules.\u003c/p\u003e\n"]]],[],null,[]]
