Industrial web application customization mechanism to improve software quality and productivity

Competition in the software market for industrial use is very challenging.Quality and productivity of software is very important to the software industry to remain competitive.Most of the commercial and industrial web applications are complex, hard to implement, risky to maintain and customization requires deep understanding of the requirements.Research showed that customization and reusability may increase the productivity and quality of the software and also decrease the development time.Unfortunately, implementing systematic reuse and customize existing system has proven to be a difficult process.While software engineers continue to struggle with cost and time, reuse has emerged as a good engineering principles and practice in various fields.However, technology to completely integrate user interface, reuse design, customization and implementation is still immature.The aim of this study is to provide a novel visual object sharing technique for designing, customizing, reusing and visualizing web elements to provide a breakthrough solution for the given problems. This technique support and provide rapid development of web-based business application where all of these underlying data and application codes are defined by meta-data, tag library and XSLT schema.This study contributes mainly in the field of reusability and customization for the web application.This study also demonstrated empirical data from two commercial projects and the results indicated that proposed object-oriented application framework (OOAF) is consistently better than traditional methods.By using OOAF, software industries are able to reduce development time, increase the quality and productivity of web application.

Feature extraction using active appearance model algorithm with Bayesian classification approach

Face recognition is one of the most important and rapidly advanced active research areas of computer science.In spite of the large number of developed algorithms, real-world performance of face recognition has been disappointing. This study enhances invariant recognition of human faces and analysis to improve face verification and identification performance using Active Appearance Model (AAM) for feature extraction with Bayesian classification approach. This paper addressed some of these issues to bring face recognition more closely to being useful for real-life applications. It directed towards the illumination-invariant automatic recognition of faces and analysis to improve face verification and identification performance.To compare with other feature extraction at the end of the study, an evaluation has been done with an existing face recognition system using AAM algorithm. The experiments performed on part of the FERET color dataset. The result was satisfied with the acceptance rate more than 96%

Performance evaluation of secured versus non-secured EIGRP routing protocol

Routing is the process of forwarding data across an inter-network from a designated source to a final destination.Along the way from source to destination, at least one intermediate node is considered. Due to the major role that routing protocols play in computer network infrastructures, special cares have been given to routing protocols with built-in security constraints.In this paper, we evaluate the performance of EIGRP routing protocol in the case of secured and non-secured routing traffic.This is done through studying and analyzing EIGRP routing traffic with and without security rules.A network model of four Cisco routers, from both software and hardware perspectives, has been employed and a traffic generation and analysis tools have been developed and used to generate traffic data and to measure the delay for performance evaluation.The results show that the average delay in the secured case can become significantly larger than the unsecured case even in steady state conditions.The differences between the delays are exponential and reach a steady state towards the end of the experiment

An Evaluation of Page Token in OpenID Single Sign on (SSO) to Thwart Phishing Attack

Single Sign-on (SSO) was introduced to overcome the issue of password memorability among users as researches have shown that users struggle to cope with too many sets of password as number of account increases. This is due to SSO relies on the usage of single authentication that allows users to access to multiple websites or services. As much as it has managed to solve the memorability issue to certain extend, users were found to have skeptical in its adoption due to security concerns. Among common issues of SSO is that it is prone to several attacks like spam, link manipulation, session hacking and particularly phishing. Despite of many efforts been placed to overcome phishing attack with regards to SSO, the effectiveness of the proposed solutions are yet to be proven by conducting extensive evaluation. Thus, this study intends to conduct an evaluation on a particular solution of phishing attack call page token. Page token was proposed recently which was claimed to be able to mitigate the issue of phishing attack with regards to SSO application. The evaluation involved a control laboratory experiment with participants being recruited to experience the usage of page token as a protection mechanism against phishing attack. The results showed are promising along with several suggestions given for further enhancement