Malware Detection Of Cloud Computing In Business Field - Samples

Question: Discuss about the Malware Detection Of Cloud Computing In Business Field. Answer: Introduction Identifying malicious software is a complicated issue. There is an ever increasing ecosystem of malicious software along with tools that represents daunting challenge for the network operators and information technology administrator. It is important to develop proper technique for malware detection in a business organization dealing with cloud computing. In this perspective, antivirus software is considered as used tools in order to detect and stop malicious and unwanted software (Klein 2017). The study deals with problem domain and research questions arise in the business. In order to solve the issue, impact of malware detection is analyzed in the present paper. In addition, project requirements analysis as well as specification is discussed in the study. Problem domain and research questions Even though cloud computing provides several advantages in a business organization, there are several issues involved with cloud computing (Dinh et al. 2013). As most of the organizations like to move to adopt cloud computing, it has been the first choice for attacker on internet. There are several types of attacks such as denial of service attacks, side channel attacks, cloud malware injection attack occurred at present day. The malware attack needs adversary creating own malicious service deployment module or virtual machine instance (Yan et al. 2016). It results attacker controlling the cloud system of the business and exploits its privileged accessing the capabilities to the instances of service for attacking instance security domains of the service. Thus, it is important to identify the type of attack and develop appropriate measures that could be helpful to minimize the issues caused for malware in cloud computing (Hatem and El-Khouly 2014). The research questions can be described as followed. What are the processes of attacking in cloud computing by malware in cloud computing of the business organization? How malware detection methods help to minimize the security threats in cloud computing? What are the challenges might be faced for malware detection method implication in the business organization? How the challenges can be overcome? Background and project objective Ferrara, Pistoia and Tripp (2015) stated that it is important to have appropriate malware detection method in order to identify the malware attack and protect cloud computing of the business organization. Malware detection methods are different types. As a network service of malware detection, the capabilities are provided by host-based anti-virus software that can efficiently and effectively provide as in-cloud network service. On the other hand, multi-detection technique has an important role for malicious as well as unwanted software that need to determine (Ko Choo, 2015). Hence, it becomes crucial to identify the appropriate malware detection method that can be helpful for the business organization. Project Requirements Analysis and Specification The project aims to identify the malware detection method suitable and appropriate for the business in order to secure cloud computing (Mollah et al. 2017). Along with this, the project objectives can be listed as followed. To find out the procedures of attacking in cloud computing by malware in cloud computing To identify the malware detection minimizing security threats in cloud computing To analyze the challenges might be faced while implementing malware detection methods in the business organization To recommend solutions for overcoming the issues For the detection of malware in a system there is no requirement of hardware specification. Any system can be used to run the anti-malware softwares. The top five anti-malware softwares in the market has been reviewed below: Bitfender Norton Kaspersky Lab Avira Avast Best Feature Secure Delete 100% Guarantee Safe Banking Gaming Mode DNS Redirecting Loss in Computer Resource 97% 97% 93% 100% 88% False Positives 96% 95% 99% 99% 96% Compatibility Windows 10 Windows 8 Windows 7 Mac Windows 10 Windows 8 Windows 7 Mac Windows 10 Windows 8 Windows 7 Mac Windows 10 Windows 8 Windows 7 Windows 10 Windows 8 Windows 7 Mac Vulnerable Software Detection Yes Yes NA Yes Yes Minimum Number of Licenses 1 1 3 1 1 These are generally known as antivirus softwares. These softwares are able to monitor a computer system for 24x7. They will do periodic scanning of malicious elements in the system and remove them permanently from the system. Choosing of an antivirus is up to the decision of oneself. It is the duty of the owner of the system owner to install a good anti-malware software to safeguard them from harm. These softwares would work similarly on a cloud system. They differ in versions and their capacity to stop the malware from harming the system (Hussein et al. 2017). Conclusion From the discussion, it concludes that it is important for a business organization keeping the business safe and secured. In order to achieve this, business needs to identify appropriate detection technique. Signature based malware detection; Heuristic based malware detection and Specification based detection is the major types of prevention technique through which the business organization can develop malware prevention method. However, several challenges might be faced while implication that requires to eradicate by the professionals of the business organization. References Dinh, H. T., Lee, C., Niyato, D., Wang, P. (2013). A survey of mobile cloud computing: architecture, applications, and approaches.Wireless communications and mobile computing,13(18), 1587-1611. Ferrara, P., Pistoia, M., Tripp, O. (2015).U.S. Patent Application No. 14/954,338. Hatem, S. S., El-Khouly, M. M. (2014). Malware detection in Cloud computing.International Journal of Advanced Computer Science and Applications (IJACSA),5. Hussein, R. K., Alenezi, A., Atlam, H. F., Mohammed, M. Q., Walters, R. J., Wills, G. B. (2017). Toward confirming a framework for securing the virtual machine image in cloud computing.Advances in Science, Technology and Engineering Systems Journal,2(4), 44-50. Klein, A. (2017).U.S. Patent No. 9,723,014. Washington, DC: U.S. Patent and Trademark Office. Ko, R., Choo, R. (2015).The Cloud Security Ecosystem: Technical, Legal, Business and Management Issues. Syngress. Mollah, M. B., Azad, M. A. K., Vasilakos, A. (2017). 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