# defense-in-depth
標記為「defense-in-depth」的 18 篇文章
Defense Fundamentals Assessment
Test your understanding of AI defense mechanisms including input/output filtering, guardrails, sandboxing, and defense-in-depth strategies with 9 intermediate-level questions.
Defense-in-Depth for LLM Applications
Implementing layered defense architectures for production LLM applications.
Defense-in-Depth for LLM Apps
Layered defense strategy for AI applications covering network, application, model, and output layers, how each layer contributes, and why single-layer defense always fails.
Defense-in-Depth Reference Architecture
Complete reference architecture for defense-in-depth LLM application security with implementation blueprints.
Layered Defense Strategy
Implementing defense in depth for AI applications: designing independent defense layers, ensuring orthogonal coverage, and managing the complexity of multi-layer security.
Simulation: Defense in Depth
Expert-level defense simulation implementing a full defense stack including input filter, output monitor, rate limiter, anomaly detector, and circuit breaker, then measuring effectiveness against automated attacks.
Defense-in-Depth Architecture for LLM Apps
Design and implement a complete defense-in-depth architecture for production LLM applications.
Dual LLM Architecture Setup
Step-by-step walkthrough for implementing a dual LLM pattern where one model generates responses and a second model validates them, covering architecture design, validator prompt engineering, latency optimization, and failure handling.
Multi-Layer Input Validation
Step-by-step walkthrough for building a defense-in-depth input validation pipeline that combines regex matching, semantic similarity, ML classification, and rate limiting into a unified validation system for LLM applications.
建構生產 AI 防禦堆疊
如何為生產部署建構分層 AI 防禦堆疊——涵蓋輸入過濾、輸出監控、護欄、異常偵測與事件應變整合。
防禦-in-Depth for LLM Applications
Implementing layered defense architectures for production LLM applications.
LLM 應用之縱深防禦
AI 應用之分層防禦策略，涵蓋網路、應用、模型與輸出層，各層的貢獻，以及為何單層防禦必然失敗。
防禦-in-Depth Reference Architecture
Complete reference architecture for defense-in-depth LLM application security with implementation blueprints.
Layered 防禦 Strategy
Implementing defense in depth for AI applications: designing independent defense layers, ensuring orthogonal coverage, and managing the complexity of multi-layer security.
Simulation: 防禦 in Depth
專家-level defense simulation implementing a full defense stack including input filter, output monitor, rate limiter, anomaly detector, and circuit breaker, then measuring effectiveness against automated attacks.
防禦-in-Depth Architecture for LLM Apps
Design and implement a complete defense-in-depth architecture for production LLM applications.
雙 LLM 架構設置
實作雙 LLM 模式之逐步流程——一個模型產生回應、第二個模型驗證之，涵蓋架構設計、驗證者提示工程、延遲最佳化與失敗處理。
Multi-Layer Input Validation
Step-by-step walkthrough for building a defense-in-depth input validation pipeline that combines regex matching, semantic similarity, ML classification, and rate limiting into a unified validation system for LLM applications.