Paper Title
Identify the Same Family of Malware by using Pattern Matching Technique

Abstract
The evolution of computing technology in the past decade until now has been raised threats against users, especially in the malware form, because the most cybersecurity threat in now day’s world is malware applications, and the new malware is introduced every day. But most of that malware is not created exactly from scratch. This paper analyzes the Methods for matching the string to identify the same family of malware, through researching and comparing the effectiveness of five algorithms of pattern matching which are Naïve, Rabin-Karp, Brute-Force, Knuth-Morris-Pratt, and Boyer Moore Algorithms, while after searching these algorithms proven effective in detecting chain similarity between malware. Keywords - Malware Analysis, Static and Dynamic Analysis, String Matching Algorithms, Naïve- algorithm, Rabin-Karp Algorithm, Brute-Force Algorithm, Knuth-Morris-Pratt Algorithm, Boyer Moore Algorithm, Similarity string.