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RISS 인기검색어
- 검색키워드
- 저자 : Abdelrafe Elzamly (검색결과 4 건)
- 무료
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Abdelrafe Elzamly,Burairah Hussin 보안공학연구지원센터(IJSEIA) 2016 International Journal of Software Engineering and Vol.10 No.2
Techniques and models for mitigating risk in software development projects classified into three categories–namely, qualitative, quantitative, and intelligent approaches. This paper is to review the quantitative and intelligent risk models in software risk management for software development projects. Indeed, this area needs more effort from scholars and researchers in quantitative and intelligent risk models to mitigate risks. As future work, we will use these hybrid models of quantitative and intelligent for mitigating software risks in cloud computing such as neural network, genetic algorithm and others artificial intelligence techniques.
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Abdelrafe Elzamly,Burairah Hussin,Norhaziah Md Salleh 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.6
The concern of this study is to identify software risks and controls in the software development lifecycle. The aim of this study is to rank the software risks factors according to their importance and occurrence frequency based on the data source. The survey questionnaire is used to collect data and method of sample selection referred to as ‘snowball’ and distribution personal regular sampling was used. The seventy six software project managers have participated in this study who works in the Palestinian software development. Fifty software risk factors in all phases SDLC and thirty risk management techniques were presented to respondents. The results show that all risks in software projects were significant and important in software project manager's perspective. However, the ranking of the importance of the risks is assigned according to it: Analysis, planning, maintenance, design, and implementation. In addition, the top ten software risk factors in software development are selected and used for further analysis such as: Risk13, Risk 14, Risk15, Risk16, Risk11, Risk18, Risk12, Risk50, Risk19, and Risk 9. The concern of this paper the top ten controls are used to model its relationship with the risk, such as: C29, C30, C20, C27, C21, C19, C28, C25, C26, and C23. Software risks can be modelled empirically with risk management control techniques. We recommended applying more studies in software risk management practices with real world companies and building tools to identification and analysis software risks based on quantitative and intelligent techniques.
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A New Conceptual Framework Modelling for Cloud Computing Risk Management in Banking Organizations
Abdelrafe Elzamly,Burairah Hussin,Samy Abu Naser,Khalid Khanfar,Mohamed Doheir,Ali Selamat,Abdullah Rashed 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.9
Despite much research and progress in the areas of cloud computing project, many cloud computing projects have a very high failure rate when it comes to the banking organizations. The aim of this study is to propose a new conceptual framework modelling for cloud computing risk management in banking organizations. There are the main five stages for a successful cloud computing framework in a banking organization as described in Figure 1: Cloud mobility and cloud banking applications, cloud service models, cloud deployment models, cloud risk management models, and cloud security models. As a future work, we will apply the framework in the real banking world to mitigate and control the security issues. A successful framework modelling for cloud computing risk management will greatly improve the probability of cloud computing success in banking organizations.
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Abdelrafe Elzamly,Burairah Hussin,Abd Samad Hasan Basari 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.8
The aim of this study is to classify critical security issues in cloud banking organizations, according to the cloud service models (CSM), and the cloud deployment models (CDM). We classified and ranked the critical cloud security issues for banking organizations based on secondary and primary data. In this regard the cloud Delphi study is modified into three phases like identifying, analysis, and evaluating security issues. In this study, the samples of 40 panelists were selected from inside and outside Malaysian banking organizations based on their experienced in the banking environment to set the insight of the cloud issues. The study starts with a list of cloud security issues based on secondary data and interview. In addition, we illustrated the level of risk for all the cloud security issues in banking organizations as small, medium, and large risk. We also indicated that the highest risk of “Trusted cloud” in 3rd party (providers) and policies security issues and the highest risk of “Availability and Mobility” in application and program (software) security, etc. The study has been conducted on groups of cloud IT managers and cloud banking developers. As a future work, we will control and mitigate the critical security issues by using artificial intelligence techniques (ANN). A successful classification of critical cloud security issues will greatly improve the probability of cloud banking success rate.
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