A Memory-Efficient Bit-Split Parallel String Matching Using Pattern Dividing for Intrusion Detection Systems

2011 ◽  
Vol 22 (11) ◽  
pp. 1904-1911 ◽  
Author(s):  
HyunJin Kim ◽  
Hong-Sik Kim ◽  
Sungho Kang
Keyword(s):  
Intrusion Detection ◽  
String Matching ◽  
Intrusion Detection Systems ◽  
Detection Systems ◽  
Parallel String Matching ◽  
Memory Efficient

Efficient String Matching Algorithm for Searching Large DNA and Binary Texts

2020 ◽  
pp. 298-324
Author(s):  
Abdulrakeeb M. Al-Ssulami ◽  
Hassan I. Mathkour ◽  
Mohammed Amer Arafah
Keyword(s):  
Intrusion Detection ◽  
Hybrid Algorithm ◽  
Binary Data ◽  
String Matching ◽  
The Other ◽  
Intrusion Detection Systems ◽  
Average Case ◽  
Matching Algorithm ◽  
Detection Systems ◽  
Maximal Shift

The exact string matching is essential in application areas such as Bioinformatics and Intrusion Detection Systems. Speeding-up the string matching algorithm will therefore result in accelerating the searching process in DNA and binary data. Previously, there are two types of fast algorithms exist, bit-parallel based algorithms and hashing algorithms. The bit-parallel based are efficient when dealing with patterns of short lengths, less than 64, but slow on long patterns. On the other hand, hashing algorithms have optimal sublinear average case on large alphabets and long patterns, but the efficiency not so good on small alphabet such as DNA and binary texts. In this paper, the authors present hybrid algorithm to overcome the shortcomings of those previous algorithms. The proposed algorithm is based on q-gram hashing with guaranteeing the maximal shift in advance. Experimental results on random and complete human genome confirm that the proposed algorithm is efficient on various pattern lengths and small alphabet.

Sign in / Sign up

Export Citation Format

Share Document