Advanced API Security 會使用採用 Google 機器學習演算法建構的模型，偵測 API 的安全威脅。這些模型會在包含已知安全威脅的實際 API 流量資料集 (包括啟用時的目前流量資料) 上預先訓練。因此，模型會學習辨識異常的 API 流量模式 (例如 API 刮除和異常)，並根據類似模式將事件分組。
[[["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：2025-06-28 (世界標準時間)。"],[[["This page provides information about Advanced API Security features in Apigee and Apigee hybrid."],["Advanced API Security uses detection rules, including machine learning models and descriptive rules, to identify unusual patterns in API traffic that might indicate malicious activity."],["The 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."],["Other detection rules include \"Brute Guessor,\" \"Flooder,\" \"OAuth Abuser,\" \"Robot Abuser,\" \"Static Content Scraper,\" and \"TorListRule\", each targeting specific types of potential API abuse."],["Security incidents, which are groups of similar events representing security threats, can be triggered by one or multiple detection rules."]]],[]]
