Application of Intelligent Data Mining Approach in Securing the Cloud Computing
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2016, Vol 7, Issue 9
Abstract
Cloud computing is a modern term refers to a model for emerging computing, where it is possible to use machines in large data centers for delivering services in a scalable manner, so corporations has become in need for large scale inexpensive computing. Recently, several governments have begun to utilize cloud computing architectures, applications and platforms for meeting the needs of their constituents and delivering services. Security occupies the first rank of obstacles that face cloud computing for governmental agencies and businesses. Cloud computing is surrounded by many risks that may have major effects on services and information supported via this technology. Also, Cloud Computing is one of the promising technology in which the scientific community has recently encountered. Cloud computing is related to other research areas such as distributed and grid computing, Service-Oriented Architecture, and virtualization, as cloud computing inherited their limitations and advancements. It is possible to exploit new opportunities for security. This paper aim is to discuss and analyze how achieve mitigation for cloud computing security risks as a basic step towards obtaining secure and safe environment for cloud computing. The results showed that, Using a simple decision tree model Chaid algorithm security rating for classifying approach is a robust technique that enables the decision-maker to measure the extent of cloud securing, and the provided services. It was proved throughout this paper that policies, standards, and controls are critical in management process to safeguard and protect the systems as well as data. The management process should analyze and understand cloud computing risks for protecting systems and data from security exploits
Authors and Affiliations
Hanna Said, Ibrahim El Emary, Bader Alyoubi, Adel Alyoubi
Keywords
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- EP ID EP101844
- DOI 10.14569/IJACSA.2016.070921
- Views 97
- Downloads 0
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