<p>Use of the same application by multiple users through internet as a service is supported by cloud computing system. Both the user and attacker stay in the same machine as both of them are users of the same application creating an in-secure environment. Service must ensure secrecy both at the application and data layer level. Data isolation and Application isolation are two basic aspects that must be ensured to cater for security as desired by the clients that accesses the service. In this paper a more secured mechanism has been presented that help ensuring data isolation and security when Multi-tenancy of the users to the same service has been implemented.</p>

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.

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Many developers have designed their own architecture for installing the cloud computing infrastructure. The existing cloud computing architectures differs in many ways. Security has been the serious issue as client related data and processing is undertaken using the infrastructure provided by third party service providers varies greatly. It is necessary to know the extent of inclusion of security into the cloud computing system and then find the best architecture that includes best and tight security system. In this paper, a comparison of existing architectures from the perspective of inclusion of security infrastructure within cloud computing system is presented along with a comprehensive architecture that is included with every aspect of security taking into account the most of the vulnerabilities.

Many cloud computing systems are in place for providing different kinds of services, which include AWS, AZURE, Google Cloud, etc. which are proprietary. These clouds help the users implement their own IT requirements, but the users cannot configure or customize the cloud computing processes as per their needs, especially to handle the issue of security from the perspectives of authentication, access control, and data security.Open source cloud computing systems, which include Eucalyptus, Open Nebula, open stack, etc. allows the changes carried to the cloud computing systems primarily through configuration, the addition of API, the addition of processes, etc. Users can make changes to affect the system such that it works as per the user requirements, especially to improve the security system built into the cloud computing system, which sometimes found to be vulnerable for attack. Users are concerned about the security of their software data hosted on third-party IT infrastructure. Open Stack cloud computing platform is being used by many for implementing private clouds. Users can customize open stack as per their requirements.Open stack suffers from many security-related vulnerabilities that can be exploited by the users for attacking the user software and data. A review of the Open stack systems is required to find the gaps that are existing to plug the same. In this paper, a review of the Open stack presented, bringing out different kinds of vulnerabilities that exist in authenticating the users and a federation method using JSON tokens showed that help eliminating the Vulnerabilities existing in the open stack for enforcing security within the Keystone module of Open stack.

In this position paper, we discuss the problem of specifying privacy requirements for machine learning based systems, in an interpretable yet operational way. Explaining privacy-improving technology is a challenging problem, especially when the goal is to construct a system which at the same time is interpretable and has a high performance. In order to address this challenge, we propose to specify privacy requirements as constraints, leaving several options for the concrete implementation of the system open, followed by a constraint optimization approach to achieve an efficient implementation also, next to the interpretable privacy guarantees.