Asian Journal of Research in Computer Science

Recently, social networks have received dramatic interest. The speed of the development and expansion of the Internet has created a new topic of research called social networks or online virtual communities on the Internet. Today, social networking sites such as Facebook, Twitter, Instagram and so forth are dramatically used by many people. Since people publish a lot of information about themselves on these networks, this information may be attacked by the intruders, so the need of preserving privacy is necessary on these networks. One of the approaches for preserving privacy is the K-anonymity. Anonymization always faces the challenge of data lost, therefore, an approach is required for anonymization of data and meanwhile maintaining the usefulness of the data. In this research, by combining the k-anonymity priority clustering method and Cuckoo optimization algorithm, an appropriate model is developed to maintain the privacy of the data and its usefulness. The average path length, average clustering coefficient and the transitivity criteria have been used to evaluate the proposed algorithm. The results of the experiments show that the proposed method in most cases has 1 unit superiority in terms of k-anonymity and 2 units superiority in terms of usefulness in comparison with similar methods.

The research, design and implementation of students file encryption and decryption system using one-time pad algorithm seeks to improve the security of student records in tertiary institutions by using trusted techniques as given in the research. The purpose is to develop an automated student’s data protection application in order to consolidate existing security measures as it pertains to data integrity and privacy. The software design methodology adopted for the research is the waterfall model due to the fact that is does not allow overlapping of processes. For the system design and implementation. Pelles C programming for windows version 9.00.9 for code generation and startUML was used for user interface design all in a bid to actualize the objectives of the research.

This research, securing computer based testing (CBT), systems for tertiary institutions provides an improved means for protecting examination question against unauthorized access. The research focuses on developing an independent and secure computer base testing system with an improved level of integrity, authenticity and confidentiality of exam questions. The methodology employed for the research design include studying writing materials on security aspect of CBT such articles and lecture notes as well as physically inspecting how the CBT system works with a view to finding leakages and vulnerabilities. Modeling tools such as UML use cases, Flowchart and entity relationship (E-R) diagrams were used to model the design. The overall design was implemented using HTML, PHP, MySQL and JavaScript platforms in order to actualize the objectives of the design. The system was tested locally using WAMP and found to be effective in reducing the problem of authenticity (especially with the Fingerprint Mechanism embedded) confidentiality and integrity of exam questions.

The first integrals of second order ordinary differential equations are considered. The necessary conditions of the existence of analytical first integrals for the equation are presented. Then, the first integrals of the equation are obtained using Lie symmetry method. The results of the first integrals are applied to certain classes of partial differential equations, the conditions of nonexistence of the traveling wave solutions of the partial differential equations are obtained, and traveling wave solutions of the equations under the certain parametric conditions are also obtained.

Data size minimization is the focus of data compression procedures by altering representation and reducing redundancy of information to a more effective kind. In general, lossless approach is favoured by a number of compression methods for the purpose of maintaining the content integrity of the file afterwards. The benefits of compression include saving storage space, speed up of data transmission and high quality of data. This paper observes the effectiveness of Chinese Remainder Theorem (CRT) enhancement in the implementation of Lempel-Ziv-Welch (LZW) and Huffman coding algorithms for the purpose of compressing large size images. Ten images of Yale database was used for testing. The outcomes revealed that CRT-LZW compression saved more space and speedy compression (or redundancy removal) of original images to CRT-Huffman coding by 29.78% to 14.00% respectively. In terms of compression time, CRT-LZW approach outperformed CRT-Huffman approach by 9.95 sec. to 19.15 sec. For compression ratio, CRT-LZW also outperformed CRT-Huffman coding by 0.39 db to 4.38 db, which is connected to low quality and imperceptibility of the former. Similarly, CRT-Huffman coding (28.13db) offered better quality Peak-Signal-to-Noise-Ratio (PSNR) for the reconstructed images when compared to CRT-LZW (3.54db) and (25.59db) obtained in other investigated paper.