Authors:
Payam Shojaeian Zanjani,Saeed Ebrahimi Nejad Motlagh Tehrani,DOI NO:
https://doi.org/10.26782/jmcms.2019.12.00016Keywords:
abnormal behavior,security,cloud computing,evolutionary algorithm,imperialist competitive algorithm,Abstract
In the present era, we have a new method called cloud computing, in which the services are shared over the Internet. There are many organizations that provide cloud processing services. Cloud processing allows users and developers to use these services without interfering with the technical knowledge or control of the technology they require, but on the other hand, day to day, more information of individuals and companies is stored inside clouds, which puts the challenge of data security ahead of users. Information security in virtual environments and new area of cloud computing has always been emphasized as one of the basic infrastructures and essential requirements for ICT-intensive use. Although absolute security is unattainable both in the real environment and in the virtual environment, it is possible to create a level of security that is sufficiently adequate in almost all environmental conditions. In cloud computing, there are many security challenges that must be addressed by cloud service providers to convince users to use this technology. One of the most important issues is ensuring the user's data is inaccurate and unavailable. For the user, the security process used to store data in the cloud is very obscure, long, and vague. In this research, a security approach based on abnormal behavior is designed to detect events that are unusual and abnormal in relation to other system behaviors. The focus of this paper is the use of evolutionary algorithms such as genetics or other new algorithms such as an imperialist competitive algorithm to detect these abnormal behaviors with intelligence agents. In similar studies, various optimization methods such as genetic algorithms, pso have been used. The proposed algorithm can be compared and evaluated with previous methods.Refference:
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