Asian Journal of Research in Computer Science <p style="text-align: justify;"><strong>Asian Journal of Research in Computer Science (ISSN: 2581-8260 )&nbsp;</strong>aims to publish high-quality papers in all areas of 'computer science, information technology,&nbsp;and related subjects'. The journal also encourages the submission of useful reports of negative results. This is a quality controlled,&nbsp;OPEN&nbsp;peer-reviewed, open access INTERNATIONAL journal.</p> en-US (Asian Journal of Research in Computer Science) (Asian Journal of Research in Computer Science) Fri, 24 Jan 2020 07:06:33 +0000 OJS 60 A Hybrid Cryptosystem and Watermarking for Secure Medical Image Transmission <p>Advances in computing and communication technologies have provided new methods to store and access medical data electronically and distribute them over open communication networks. Today, patients themselves can access their medical information themselves and medical information can be transmitted among medical institutions as well as stakeholders in the health sector.&nbsp; Accompanying these benefits are concomitant risks for patient medical records in electronic formats and strictly personal medical documentations being transmitted and accessible over open communication channels such as the Internet. Thus it is common knowledge that there should be in place network-level security measures and protocols in medical information systems. Many security schemes that were based on cryptography, watermarking and steganography have been proposed and implemented to secure medical data. However, an apt review of relevant literature revealed that in many implementations robustness against attacks is not guaranteed. Issues bordering on low embedding capacity, low robustness, low imperceptibility and bad trade tradeoff between robustness and capacity are evident in many implementations. In this paper, a hybrid Rivest-Shamir-Adleman (RSA) algorithm, Rivest Cipher 4 (RC4) algorithm and Spread Spectrum techniques were proposed for securing medical image data over open communication networks. The performance of the proposed scheme was evaluated using Peak Signal to Noise Ratio (PSNR), Signal to Noise Ratio (SNR), Mean Square Error (MSE) and Bit Error Rate (BER). For the five sample medical images used to test the scheme, the BER value is zero while the PNSR and SNR are consistent and they returned desirable high values. The MSE values for the images were low. The average values of the PSNR, SNR and MSE are 51.88 dB, 43.38 dB and 0.113 respectively. Hence, the proposed scheme is utterly revertible, robust and highly imperceptible; the original images can be retrieved by the recipient without any deformation or alteration.</p> Oladotun O. Okediran ##submission.copyrightStatement## Fri, 24 Jan 2020 00:00:00 +0000 A Systematic Review of Health Care Ontology <p><strong>Objective:</strong> The study sought to extracts information about the steps, methods, techniques, initiatives and strategies that is use in establishing ontology in the medical sector.</p> <p><strong>Methods:</strong> The guideline that was employed for conducting the systematic review in this research work is that which was proposed by Kitchenham. The Google Scholar, Scopus and Web of science were searched for proceedings from conferences and journal papers between 2009 and 2018. Articles focusing on health care and ontology, health ontology and diagnosis system were selected. The AND operator was used in the Boolean language construction for the article search to limit articles presented to those that actually apply Ontology in the Health care. Selected articles were considered eligible based on their studies appropriately fitting into providing answers for the research questions that were presented in this research work within the last 10 years.</p> <p><strong>Results:</strong> Twenty (20) research articles were included in the review; of the initiatives of the research works considered, Seven (7) were of Methodology, Two (2) were Technique based, Three (3) were Framework based, Two (2) were Process based while Six (6) were extensions of those in existence.</p> <p><strong>Conclusions:</strong> The approaches considered were ontology based in terms of the use of Protégé-owl editor tool, SPARQL, Protégé 4, OWL 2, OWL, RDF, SNOMED CT. The main contributions include but not limited to Modelling of knowledge representation using Protégé for relating data and concepts with references to diabetes diseases, mobile based health care ontology, classification of diseases based on phenotypes, improvement in service delivery and availability of reliable health data. This Ontology heath care review which was carried out shows the need for Ontology based models to improve health service delivery for both the users (patients) and the care providers.</p> F. M. Okikiola, A. M. Ikotun, A. P. Adelokun, P. E. Ishola ##submission.copyrightStatement## Sat, 15 Feb 2020 00:00:00 +0000