Biblio

Cloud Computing is an important term of modern technology. The usefulness of Cloud is increasing day by day and simultaneously more and more security problems are arising as well. Two of the major threats of Cloud are improper authentication and multi-tenancy. According to the specialists both pros and cons belong to multi-tenancy. There are security protocols available but it is difficult to claim these protocols are perfect and ensure complete protection. The purpose of this paper is to propose an integrated model to ensure better Cloud security for Authentication and multi-tenancy. Multi-tenancy means sharing of resources and virtualization among clients. Since multi-tenancy allows multiple users to access same resources simultaneously, there is high probability of accessing confidential data without proper privileges. Our model includes Kerberos authentication protocol to enhance authentication security. During our research on Kerberos we have found some flaws in terms of encryption method which have been mentioned in couple of IEEE conference papers. Pondering about this complication we have elected Elliptic Curve Cryptography. On the other hand, to attenuate arose risks due to multi-tenancy we are proposing a Resource Allocation Manager Unit, a Control Database and Resource Allocation Map. This part of the model will perpetuate resource allocation for the users.

Shared resources are an essential part of cloud computing. Virtualization and multi-tenancy provide a number of advantages for increasing resource utilization and for providing on demand elasticity. However, these cloud features also raise many security concerns related to cloud computing resources. In this paper, we propose an architecture and approach for leveraging the virtualization technology at the core of cloud computing to perform intrusion detection security using hypervisor performance metrics. Through the use of virtual machine performance metrics gathered from hypervisors, such as packets transmitted/received, block device read/write requests, and CPU utilization, we demonstrate and verify that suspicious activities can be profiled without detailed knowledge of the operating system running within the virtual machines. The proposed hypervisor-based cloud intrusion detection system does not require additional software installed in virtual machines and has many advantages compared to host-based and network based intrusion detection systems which can complement these traditional approaches to intrusion detection.