Ariel M. Sison

Implementation of Improved DES Algorithm in Securing Smart Card Data

Although smart cards have already provided secure portable storage device, security is still a major concern to electronic data systems. There is a need to improve data security against accidental or unlawful destruction or alteration during transmission or while in storage. The Odd-Even substitution proved to have provided additional confusion technique to DES and was essential in providing adequate security. The limitation of DES to encrypt large data has also been addressed by this research without intensive processing. Unlike the 3DES or AES, the improved DES has lesser computational load.

An Improved Data Encryption Standard to Secure Data Using Smart Cards

This paper is directed towards the development of an improved DES to secure the data using smart cards. An improved Data Encryption Standard has been developed by incorporating an ODD/EVEN bit conversion to the existing DES algorithm. The proposed algorithm is expected to provide greater security to further protect the data in Smart Cards. The data is secured from any illegal retrieval and intended modification. The program simulation also provides a good start to explore for a more robust encryption technique that will not require so much mathematical computations.

Enhanced RC6 permutation-diffusion operation for image encryption

RC6 is considered one of the encryption strategies being utilized and modified to be suited for image protection. However, the RC6 encryption algorithm is still prone to statistical and differential attack which is one of the major concerns whenever open networks are to be used. In this paper, we proposed a modification of RC6 algorithm for image encryption. A new technique of permutation-diffusion architecture based on a modified concept of cyclic shift is integrated to increase the degree of permutation and diffusion mechanism of RC6 for image encryption. The security level, processing time and diffusion rate were tested using image evaluation metrics such as correlation coefficient test, number of pixel change rate (NPCR) test, unified average change intensity (UACI) test, and run-time analysis to measure its efficiency along with the simulation process. Results show that the proposed method illustrates a lower value of correlation among pixels and higher value of NPCR and UACI which makes the proposed method highly resistant to statistical and differential attacks. Increased security level with minimal time consumption is achieved in our approach.

Application of enhanced expectation maximization (EnEM) algorithm for image segmentation

An Enhanced EM (EnEM) algorithm was developed through the integration of the concept of firefly movement and light intensity of Firefly Algorithm in its initialization stage. The improved initial parameter selection technique of EnEM algorithm leads to a better clustering performance when applied to image segmentation. The procedure converts first the image from RGB to HSV color space. A saturation threshold function was used in labelling the pixel and performed median filter for post processing to eliminate the noisy pixel to produce the final segmented image. An image segmentation module was developed and different test images were used. Experiments show that the application of EnEM to image segmentation produces lower MSE and higher PSNR which leads to a better segmentation.

Data Extraction Using Preprocessing Compression Based on LZW to Improve DB Performance

The Lempel-Ziv-Welch (LZW) algorithm has provided attractive data compression for storage medium with limited space. This study is motivated to improve database performance by compressing some of its attributes using LZW compression algorithm. Simulation results show that LZW is useful for practical purposes. Data compression will speed up data transmittal since the amount of memory needed is reduced including the amount of data to be stored. Data compression provides additional level of data integrity and reliability.