Derin Paket İncelemesi için Önerilen Yeni Bir Örüntü Eşleştirme Algoritması

Abstract

Derin Paket İnceleme (Deep Packet Inspection-DPI), hem paket başlığı hem de paket yükü üzerinde ayrıntılı analizler gerçekleştirerek ağ trafiğinin tam görünürlüğünü sağlayan teknolojidir. DPI ile iyi bilinen kötü amaçlı yazılım imzaları ve saldırı sırası, saldırganın izlediği yol ve kullandığı tekniklerin birleşimi olarak tanımlanan saldırı deseninin tespiti yapılabilmektedir. Bu doğrultuda, ağ güvenliği veya devlet gözetimi gibi uygulamalarda kullanılabilmesi yönüyle DPI, kritik bir öneme sahiptir. Bu çalışmada, tek seferde taranan bayt sayısını artırarak DPI sürecini hızlandırmayı amaçlayan blok tabanlı bir örüntü eşleştirme algoritması önerilmiştir. Farklı sayıda örüntü içeren veri kümeleri kullanılarak Aho-Corasick (AC), Rabin-Karp (RK), Wu-Manber (WM) ve bu çalışmada önerilen algoritma üzerinde örüntü eşleştirme testleri gerçekleştirilmiş ve bu algoritmaların performansları karşılaştırılmıştır. AC, WU ve RK algoritmalarına kıyasla bu çalışmada önerilen algoritma, daha yüksek bir performans göstermiştir.

Keywords

• Derin paket inceleme
• Örüntü eşleştirme
• Ağ güvenliği
• Ağ trafiği analizi

A New Pattern Matching Algorithm for Deep Packet Inspection

Abstract

Deep Packet Inspection (DPI) is a technology that provides full visibility into network traffic by performing detailed analysis on both packet header and packet payload. DPI technique is used to detect well-known malware signatures. Additionally, the attack pattern which includes the attack order, the path followed by the attacker and the techniques used by the attacker can be detected. Accordingly, DPI has a critical importance as it can be used in applications i.e network security or government surveillance. In this study, a block-based pattern matching algorithm is proposed, which aims to speed up the DPI process by increasing the number of bytes scanned at once. Pattern matching tests are performed on Aho-Corasick (AC), Wu-Manber (WM), Rabin-Karp (RK) algorithms and the algorithm in this study by using datasets containing different numbers of patterns, and the performances of these algorithms are compared. Compared to the AC, RK and WM algorithms, the proposed algorithm in this study has a higher performance.

Keywords

• Deep packet inspection
• Pattern matching
• Network security
• Network traffic analysis

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