Towards the design of secure and privacy-oriented Information systems in the cloud: Identifying the major concepts

Cloud computing is without a doubt one of the most significant innovations presented in the global technological map. This new generation of technology has the potential to positively change our lives since on the one hand it provides capabilities that make our digital lives much easier, than before, while on the other hand it assists developers in creating services that can be disseminated easier and faster, than before, and with significantly less cost. However, one of the major research challenges for the successful deployment of cloud services is a clear understanding of security and privacy issues on a cloud environment, since the cloud architecture has dissimilarities comparing to the traditional distributed systems. Such differences might introduce new threats and require different treatment of security and privacy issues. Nevertheless, current security and privacy requirements engineering techniques and methodologies have not been developed with cloud computing in mind and fail to capture the unique characteristics of such domain. It is therefore important to understand security and privacy within the context of cloud computing and identify relevant security and privacy properties and threats that will support techniques and methodologies aimed to analyze and design secure cloud based systems. The contribution of this paper to the literature is two-fold. Firstly, it provides a clear linkage between a set of critical cloud computing areas with security and privacy threats and properties. Secondly, it introduces a number of requirements for analysis and design methodologies to consider for security and privacy concerns in the cloud

Client-side encryption and key management: enforcing data confidentiality in the cloud.

Master of Science in Computer Science. University of KwaZulu-Natal, Durban 2016.Cloud computing brings flexible, scalable and cost effective services. This is a computing paradigm whose services are driven by the concept of virtualization and multi-tenancy. These concepts bring various attractive benefits to the cloud. Among the benefits is reduction in capital costs, pay-per-use model, enormous storage capacity etc. However, there are overwhelming concerns over data confidentiality on the cloud. These concerns arise from various attacks that are directed towards compromising data confidentiality in virtual machines (VMs). The attacks may include inter-VM and VM sprawls. Moreover, weaknesses or lack of data encryption make such attacks to thrive. Hence, this dissertation presents a novel client-side cryptosystem derived from evolutionary computing concepts. The proposed solution makes use of chaotic random noise to generate a fitness function. The fitness function is used to generate strong symmetric keys. The strength of the encryption key is derived from the chaotic and randomness properties of the input noise. Such properties increase the strength of the key without necessarily increasing its length. However, having the strongest key does not guarantee confidentiality if the key management system is flawed. For example, encryption has little value if key management processes are not vigorously enforced. Hence, one of the challenges of cloud-based encryption is key management. Therefore, this dissertation also makes an attempt to address the prevalent key management problem. It uses a counter propagation neural network (CPNN) to perform key provision and revocation. Neural networks are used to design ciphers. Using both supervised and unsupervised machine learning processes, the solution incorporates a CPNN to learn a crypto key. Using this technique there is no need for users to store or retain a key which could be compromised. Furthermore, in a multi-tenant and distributed environment such as the cloud, data can be shared among multiple cloud users or even systems. Based on Shamir's secret sharing algorithm, this research proposes a secret sharing scheme to ensure a seamless and convenient sharing environment. The proposed solution is implemented on a live openNebula cloud infrastructure to demonstrate and illustrate is practicability