In this research, we propose a fast pattern matching algorithm: The Two Sliding Windows (TSW) algorithm. The algorithm makes use of two sliding windows, each window has a size that is equal to the pattern length. Both windows slide in parallel over the text until the first occurrence of the pattern is found or until both windows reach the middle of the text. The experimental results show that TSW algorithm is superior to other algorithms especially when the pattern occurs at the end of the text

Pattern matching is a very important topic in computer science. It has been used in various applications such as information retrieval, virus scanning, DNA sequence analysis, data mining, machine learning, network security and pattern recognition. This paper has presented a new pattern matching algorithm-Enhanced ERS-A, which is an improvement over ERS-S algorithm. In ERS-A, two sliding windows are used to scan the text from the left and the right simultaneously. The proposed algorithm also scans the text from the left and the right simultaneously as well as making comparisons with the pattern from both sides simultaneously. The comparisons done between the text and the pattern are done from both sides in parallel. The shift technique used in the Enhanced ERS-A is the four consecutive characters in the text immediately following the pattern window. The experimental results show that the Enhanced ERS-A has enhanced the process of pattern matching by reducing the number of comparisons performed.

This paper presents an efficient pattern matching algorithm (FSW). FSW improves the searching process for a pattern in a text. It scans the text with the help of four sliding windows. The windows are equal to the length of the pattern, allowing multiple alignments in the searching process. The text is divided into two parts; each part is scanned from both sides simultaneously using two sliding windows. The four windows slide in parallel in both parts of the text. The comparisons done between the text and the pattern are done from both of the pattern sides in parallel. The conducted experiments show that FSW achieves the best overall results in the number of attempts and the number of character comparisons compared to the pattern matching algorithms: Two Sliding Windows (TSW), Enhanced Two Sliding Windows algorithm (ETSW) and Berry-Ravindran

Visual cryptography (VC) is one of the best techniques used to secure information. It uses the human vision to decrypt the encrypted images without any cryptographic computations. The basic concept of visual cryptography is splitting the secret image into shares such that when the shares are stacked, the secret image is revealed. In this paper we proposed a method that is based on the concept of visual cryptography for color images and without any pixel expansion which requires less space. The proposed method is used to encrypt halftone color images by generating two shares, random and key shares which are the same size as the secret color image. The two shares are generated based on a private key. At the receiving side, the secret color image is revealed by stacking the two shares and exploiting the human vision system. In this paper, we produce an enhanced form of the proposed method by modifying the encryption technique used to generate the random and the key shares. Experimental results have shown that the proposed and the enhanced methods suggest an efficient way to encrypt a secret color image with better level of security, less storage space, less time of computation and with a better value of PSNR.