International Journal of Computer Networks and Communications Security

Volume 4, Issue 7, July 2015

 

 

 

Usability Evaluation Methods and Principles for the Web

Pages: 165-171 (7) | [Full Text] PDF (591 KB)
J Mvungi, T Tossy
Computer Science Studies Department, Mzumbe University, Morogoro, Tanzania

Abstract -
In order to determine the quality of any web application in the world, Usability is the one of the most important tool that one can use. Web analysis perform several inspections on the websites and software and use usability criteria to determine some faults on the systems. Usability engineering has being important tool for the companies as well, this is due to the fact that through usability engineering companies can improve their market level by making their products and services more accessible. Know days there some web application and software products which are complex and very sophisticated, hence usability can be able to determine their success or failure. However currently usability has been among the important goal for the Web engineering research and much attention is given to usability by the industry due to recognition of the importance of adopting usability evolution methods before and after deployment. Moreover several literature has proposed several techniques and methods for evaluating web usability. And however there is no agreement yet in the software on which usability evolution method is better than the other. Extensive usability evaluation is usually not feasible for the case of web development process. In other words unusable website increases the total cost of ownership, and therefore this paper introduces principles and evaluation methods to be used during the whole application lifecycle, so as to enhance usability of web applications.
 
Index Terms - Evolution Methods, Web Usability, Web Usability Principles, Development Process

Citation - J Mvungi, T Tossy. "Usability Evaluation Methods and Principles for the Web." International Journal of Computer Science and Software Engineering 4, no. 7 (2015): 165-171.

 

Multimedia System Security Using Access Control Policy Based on Role Based Access Control

Pages: 172-177 (6) | [Full Text] PDF (433 KB)
Roslina, Hartono, M Zarlis
Politeknik Negeri Medan., Department of Computer Science, University of Sumatera Utara, Medan, 20155
Department of Computer Science, University of Sumatera Utara, Medan, 20155

Abstract -
Multimedia data and information systems manage, communicate, and present multimedia data including text, images, audio and video. We need to ensure that the data is protected from unauthorized access as well as malicious corruption. Digital watermarking techniques that insert hidden copyright messages into the multimedia data are needed. Furthermore, since multimedia data is being used for security applications such as surveillance and monitoring, protecting privacy of the individual is crucial. This paper will discuss the security of multimedia systems using access control policies. An access control space represents the permission assignment state of a subject or role. Nowadays, three kinds of access control, discretionary access control (DAC) mandatory access control (MAC) and role-based access control (RBAC) have been proposed. In RBAC, there are role hierarchies in which a senior role can perform the permission of a junior role. Role Based Access Control (RBAC) is a popular model for access control policy and is used widely as it provides a convenient way to specify entitlements corresponding to specific meaning. One of the biggest issue in RBAC is authentication is for ensuring secure exchange of information and preventing illegal modification. In this paper, the description of an access control algorithm and a system architecture for a secure multimedia system are presented and also the method for securing information exchange in multimedia system.
 
Index Terms - Access Control, Role Based Access Control (RBAC), Multimedia System

Citation - Roslina, Hartono, M Zarlis. "Multimedia System Security Using Access Control Policy Based on Role Based Access Control." International Journal of Computer Science and Software Engineering 4, no. 7 (2015): 172-177.

 

PreSS#, A Web-Based Educational System to Predict Programming Performance

Pages: 178-189 (12) | [Full Text] PDF (837 KB)
K Quille, S Bergin, A Mooney
Department of Computer Science, Maynooth University, Maynooth, Co Kildare, Ireland

Abstract -
PreSS# (Predict Student Success #) is a web based educational system developed during the academic year 2013/14. This paper describes the design and development, highlighting the methodologies and architecture of the system. The system builds upon the findings of a previous study undertaken by Bergin [1], who successfully developed a semi-automated computational model named PreSS that could predict a students academic performance in programming with an accuracy of over 80% after only 4-6 teaching hours. PreSS used a paper based data collection method and the analysis of the collected data required manual data entry thus making PreSS administratively heavy. PreSS# is a system that accurately replicates the performance of PreSS with 95% confidence (P (value) = 1.0 and a T (value) = 0.0), is fully functional and can compute predictions in real time with cross-browser (mobile and desktop) compatibility. PreSS# is scalable, secure and robust allowing it to be employed across different institutions, ultimately leading to an increase in progression rates by identifying both struggling and gifted (students in danger of becoming disengaged) students earlier than had been previously feasible.
 
Index Terms - Web Based Application, Education, Learning, Prediction, performance

Citation - K Quille, S Bergin, A Mooney. "PreSS#, A Web-Based Educational System to Predict Programming Performance ." International Journal of Computer Science and Software Engineering 4, no. 7 (2015): 178-189.

 

Classification of Complex UCI Datasets Using Machine Learning Algorithms Using Hadoop

Pages: 190-198 (9) | [Full Text] PDF (599 KB)
Mohit, RR Verma, S Katoch, A Vanjare, SN Omkar
Computer Science department, NIT Srinagar Srinagar, Jammu and Kashmir, INDIA
Information Technology ,NIT Srinagar Srinagar, Jammu and Kashmir, INDIA
Electronic and communication department, NIT Srinagar Srinagar, Jammu and Kashmir, INDIA
Aerospace Engineering Department, IISc Bangalore, Karnataka, INDIA

Abstract -
Classification is one of the most researched questions in machine learning and data mining. Classification is a gradual practice for allocating a given piece of input into any of the known category. The Data Mining refers to extracting or mining knowledge from huge volume of data. In this paper different classification techniques of Data Mining are compared using diverse datasets from University of California, Irvine (UCI) Machine Learning Repository. Accuracy and time complexity for execution by each classifier is observed. Finally different classifiers are also compared and accordingly which classifier is best for respective datasets is observed.
 
Index Terms - Data Mining, J48, Decision Table, Naive Bayes, OneR, Random Forest, Hadoop, HDFS, R Environment

Citation - Mohit, RR Verma, S Katoch, A Vanjare, SN Omkar. "Classification of Complex UCI Datasets Using Machine Learning Algorithms Using Hadoop." International Journal of Computer Science and Software Engineering 4, no. 7 (2015): 190-198.