隨著網際網路用戶數量快速增長的步伐，各類網際網路應用變得越來越多樣化。為了因應持續變化的網際網路與應用，終端用戶要求在網絡設備內新增越來越多的進階功能以便於能夠有效率地監控和管理網路。因此，現代的網路設備都配備了DPI（深度包檢測）技術去掃描數據封包的內容以實現增值的功能，如應用軟體等級的管理。深度包檢測技術的核心為多樣式字串匹配演算法，用來掃描數據封包的內容去比對預先定義的特徵數據庫。深度包檢測技術主要應用於 AV
（反病毒），IDP（入侵偵測和防禦）和App ID（應用軟體流量識別）等技術的研發，並且實作在IPS（入侵防禦系統），UTM（統一威脅管理），NG Firewall（下一世代防火牆）等系統。這些系統的性能不僅取決於採用的多樣式比對演算法，比對結果處理的演算法也有很大的影響。本論文提出一個基於獨特樣式的規則前級比對過濾方法，並且實作在兩個多核心平台上以展示其效率和性能。本論文提出的基於獨特樣式的規則前級比對過濾方法獨立於樣式比對演算法和比對結果處理演算法之外。在使用樣式比對演算法掃描數據封包的內容後，將所有比對結果送給比對結果處裡演算法檢視前，絕大部分無效的比對結果可以先被此方法快速地過濾掉。在記憶體方面的消耗，每條規則僅只需增加一點點記憶體使用量。性能測試結果表明，在使用此方法過濾絕大部分無效的比對結果後，系統性能幾乎可以增加一倍。並且，系統性能的提升約與使用的CPU 核心數量成正比，
存在著接近線型成長的關係。

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