The recent growth in the demand for scalable applications from the consumers of the services has motivated the application development community to build and deploy the applications on cloud in the form of services. The deployed applications have significant dependency on the infrastructure available with the application providers. Bounded by the limitations of available resource pools on-premises, many application development companies have migrated the applications to third party cloud environments called data centers. The data center owners or the cloud service providers are entitled to ensure high performance and high availability of the applications and at the same time the desired scalability for the applications. Also, the cloud service providers are also challenging in terms of cost reduction and energy consumption reductions for better manageability of the data center without degrading the performance of the deployed applications. It is to be noted that the performance of the application does not only depend on the responsiveness of the applications rather also must be measured in terms of service level agreements. The violation of the service level agreements or SLA can easily disprove the purpose of application deployments on cloudbased data centers. Thus, the data center owners apply multiple load balancing strategies for maintaining the desired outcomes from the application owners at the minimized cost of data center maintainability. Hence, the demand of the research is to thoroughly study and identify the scopes for improvements in the parallel research outcomes. As the number of applications ranging from small data-centric applications coming with the demand of frequent updates with higher computational capabilities to the big data-centric application as big data analytics applications coming with efficient algorithms for data and computation load managements, the data center owners are forced to think for efficient algorithms for load managements. The algorithms presented by various research attempts have engrossed on application specific demands for load balancing using virtual machine migrations and the solution as the proposed algorithms have become application problem specific. Henceforth, the further demand of the research is a guideline for selecting the appropriate load balancing algorithm via virtual machine migration for characteristics-based specific applications. Hence, this paper presents a comprehensive survey on existing virtual machine migration and selection processes to understand the specific application-oriented capabilities of these strategies with the advantages and bottlenecks. Also, with the understanding of the existing measures for load balancing, it is also important to furnish the further improvement strategies, which can be made possible with a detailed understanding of the parallel research outcomes. Henceforth, this paper also equips the study with guidelines for improvements and for further study. Nonetheless, the study cannot be completed without the mathematical an...
The malicious insider can be an employees, user and/or third party business partner. The insiders can have legitimate access to their organization data centers. In organizations, the security related aspects are based on insider's behaviors, the malicious insiders may theft sensitive data and no protection mechanisms are addressed till now to completely defend against the attacks. Such that organizational data could be so vulnerable from insider threat attacks. The malicious insiders of an organization can perform stealing on sensitive data at cloud storage as well as at organizational level. The insiders can misuse their credentials in order to perform malicious tasks on sensitive information as they agreed with the competitors of that organization. By doing this, the insiders may get financial benefits from the competitors. The damages of insider threat are: IT sabotages, theft of confidential information, trade secrets and Intellectual properties (IP). It is very important for the nation to start upgrading it's IT infrastructure and keep up with the latest security guidelines and practices.
Maximizing spectrum usage and numerous applications of the wireless communication networks have forced to a high interest of vacant spectrum. Cognitive Radio influences its receiver and transmitter features accurately so that they can utilize the vacant approved spectrum without impacting the functionality of the principal licensed subscribers. The use of various channels assists to address interferences thereby improves the whole network efficiency. The MAC protocol in cognitive radio network explains the spectrum consumption by interacting the multiple channels among the subscribers. In this particular paper we studied traditional TDMA dependent MAC method with dynamically assigned slots. The majority of the MAC protocols suggested in the research operate Common-Control-Channel (CCC) to handle the services between Cognitive Radio end users. Traditional MAC protocol design and operations are implemented by using Multi-Channel-Collection method, a high rate multi-channel time schedule protocol for unbiased real-time data collection and their limitations are studied in Wireless mesh Networks. In this paper, an extensive study of Multi-Channel-Collection with sophisticated techniques for multiple band or frequency range channel allotment and continually synchronized TDMA scheduling are shown in summarized way.
The malicious insider can be an employees, user and/or third party business partner. In cloud environment, clients may store sensitive data about their organization in cloud data centers. The cloud service provider should ensure integrity, security, access control and confidentiality about the stored data at cloud data centers. The malicious insiders can perform stealing on sensitive data at cloud storage and at organizations. Most of the organizations ignoring the insider attack because it is harder to detect and mitigate. This is a major emerging problem at the cloud data centers as well as in organizations. In this paper, we proposed a method that ensures security, integrity, access control and confidentiality on sensitive data of cloud clients by employing multi cloud service providers. The organization should encrypt the sensitive data with their security policy and procedures and store the encrypted data in trusted cloud. The keys which are used during encryption process are again encrypted and stored in another cloud area. So that organization contains only keys for keys of encrypted data. The Administrator of organization also does not know what data kept in cloud area and if he accesses the data, easily caught during the auditing. Hence, the only authorized used can access the data and use it and we can mitigate insider attacks by providing restricted privileges.
Information security is a major problem faced by cloud computing around the world. Because of their adverse effects on organizational information systems, viruses, hackers, and attackers insiders can jeopardize organizations capabilities to pursue their undertaken effectively. Although technology based solutions help to mitigate some of the many problems of information security, even the preeminent technology can’t work successfully unless effective human computer communication occurs.IT experts, users and administrators all play crucial role to determine the behavior that occurs as people interact with information technology will support the maintenance of effective security or threaten it. In the present paper we try to apply behavioral science concepts and techniques to understanding problems of information security in organizations.
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