Securing SaaS Cloud Infrastructure using TPM based provisioning

In the era of technology, cloud computing is the vast developing technology. The research indicates that as cloud elements are becoming more extensive in IT industry, more enterprises are depending on cloud computing for their business needs such as storage, business disaster recovery and security. Thus, cloud computing is almost accepted as a default part of IT landscape with the indicators of this strong usage and strong market. Software as a service (SaaS) is software model the users can access the applications that is owned, delivered and managed remotely by providers. The key advantage to SaaS in the enterprise is in cost savings in personnel, in hardware and in physical storage space. However, based on data sharing properties, these may be vulnerable to malicious attacks. Thus, with the user credentials it can be easily compromised and the services of SaaS are accessed. The services can be acquired even by the URLs when compromised. In order to overcome this issue we propose a novel technique, Securing SaaS Cloud Infrastructure using TPM based provisioning. A portable TPM is used for accessing SaaS which provides better security. A cryptographic protocol that enables the remote authentication which preserves the privacy of the user is modelled as Trusted Platform Module (TPM). TPM is used for strong user authentication framework apart from user credentials which proves the secure data access control in the cloud storage by providing additional security. Also, our system is constructed based on the cloud MVC architecture. MVC is significant, which allow fast & agile development and provide full control over mark-up. Hence it is finest for establishing interactive web application. The scripts in this model are run only when it is required, thus reducing the overall computation. Using this approach, services are provided to the user in an efficient and secured way. Finally, we demonstrate the secured services and efficiency of the proposed schemes through extensive experimental evaluation on the live Microsoft Windows Azure platform.