Cloud Providers Viability: How to Address it from an IT and Legal Perspective?

in Economics of Grids, Clouds, Systems, and Services (2015, September 16)

A major part of the commercial Internet is moving towards a cloud paradigm. This phenomenon has a drastic impact on the organizational structures of enterprises and introduces new challenges that must be ... [more ▼]

A major part of the commercial Internet is moving towards a cloud paradigm. This phenomenon has a drastic impact on the organizational structures of enterprises and introduces new challenges that must be properly addressed to avoid major setbacks. One such challenge is that of cloud provider viability, that is, the reasonable certainty that the Cloud Service Provider (CSP) will not go out of business, either by filing for bankruptcy or by simply shutting down operations, thus leaving its customers stranded without an infrastructure and, depending on the type of cloud service used, even without their applications or data. This article attempts to address the issue of cloud provider viability, proposing some ways of mitigating the problem both from a technical and from a legal perspective. [less ▲]

BALANCING NON-FUNCTIONAL REQUIREMENTS IN CLOUD-BASED SOFTWARE: AN APPROACH BASED ON SECURITY-AWARE DESIGN AND MULTI-OBJECTIVE SOFTWARE DYNAMIC MANAGEMENT

Doctoral thesis (2015)

Beyond its functional requirements, architectural design, the quality of a software system is also defined by the degree to which it meets its non-functional requirements. The complexity of managing these ... [more ▼]

Beyond its functional requirements, architectural design, the quality of a software system is also defined by the degree to which it meets its non-functional requirements. The complexity of managing these non-functional requirements is exacerbated by the fact that they are potentially conflicting with one another. For cloud-based software, i.e., software whose service is delivered through a cloud infrastructure, other constraints related to the features of the hosting data center, such as cost, security and performance, have to be considered by system and software designers. For instance, the evaluation of requests to access sensitive resources results in performance overhead introduced by policy rules evaluation and message exchange between the different geographically distributed components of the authorization system. Duplicating policy rule evaluation engines traditionally solves such performance issues, however such a decision has an impact on security since it introduces additional potential private data leakage points. Taking into account all the aforementioned features is a key factor to enhance the perceived quality of service (QoS) of the cloud as a whole. Maximizing users and software developers satisfaction with cloud-based software is a challenging task since trade-off decisions have to be dynamically taken between these conflicting quality attributes to adapt to system requirements evolution. In this thesis, we tackle the challenges of building a decision support method to optimize software deployment in a cloud environment. Our proposed holistic method operates both at the level of 1) Platform as a service (PaaS) by handling software components deployment to achieve an efficient runtime optimization to satisfy cloud providers and customers objectives 2) Guest applications by making inroads into the design of applications to enable the design of secure systems that also meet flexibility, performance and cost requirements. To thoroughly investigate these challenges, we identify three main objectives that we address as follows: The first objective is to achieve a runtime optimization of cloud-based software deployment at the Platform as a service (PaaS) layer, by considering both cloud customers and providers constraints. To fulfill this objective, we leverage the models@run.time paradigm to build an abstraction layer to model a cloud infrastructure. In a second step, we model the software placement problem as a multi-objective optimization problem and we use multi-objective evolutionary algorithms (MOEAs) to identify a set of possible cloud optimal configurations that exhibit best trade-offs between conflicting objectives. The approach is validated through a case study that we defined with EBRC1, a cloud provider in Luxembourg, as a representative of a software component placement problem in heterogeneous distributed cloud nodes. The second objective is to ameliorate the convergence speed of MOEAs that we have used to achieve a run-time optimization of cloud-based software. To cope with elasticity requirements of cloud-based applications, we improve the way the search strategy operates by proposing a hyper-heuristic that operates on top of MOEAs. Our hyper-heuristic uses the history of mutation effect on fitness functions to select the most relevant mutation operators. Our evaluation shows that MOEAs in conjunction with our hyper-heuristic has a significant performance improvement in terms of resolution time over the original MOEAs. The third objective aims at optimizing cloud-based software trade-offs by exploring applications design as a complementary step to the optimization at the level of the cloud infrastructure, tackled in the first and second objectives. We aimed at achieving security trade-offs at the level of guest applications by revisiting current practices in software methods. We focus on access control as a main security concern and we opt for guest applications that manage resources regulated by access control policies specified in XACML2. This focus is mainly motivated by two key factors: 1) Access control is the pillar of computer security as it allows to protect sensitive resources in a given system from unauthorized accesses 2) XACML is the de facto standard language to specify access control policies and proposes an access control architectural model that supports several advanced access requirements such as interoperability and portability. To attain this objective, we advocate the design of applications based on XACML architectural model to achieve a trade-off between security and flexibility and we adopt a three-step approach: First, we identify a lack in the literature in XACML with obligation handling support. Obligations enable to specify user actions that have to be performed before/during/after the access to resources. We propose an extension of the XACML reference model and language to use the history of obligations states at the decision making time. In this step, we extend XACML access control architecture to support a wider range of usage control scenarios. Second, in order to avoid degrading performance while using a secure architecture based on XACML, we propose a refactoring technique applied on access control policies to enhance request evaluation time. Our approach, evaluated on three Java policy-based systems, enables to substantially reduce request evaluation time. Finally, to achieve a trade-off between a safe security policy evolution and regression testing costs, we develop a regression-test-selection approach for selecting test cases that reveal faults caused by policy changes. To sum up, in all aforementioned objectives, we pursue the goal of analysing and improving the current landscape in the development of cloud-based software. Our focus on security quality attributes is driven by its crucial role in widening the adoption of cloud computing. Our approach brings to light a security-aware design of guest applications that is based on XACML architecture. We provide useful guidelines, methods with underlying algorithms and tools for developers and cloud solution designers to enhance tomorrow’s cloud-based software design. Keywords: XACML-policy based systems, Cloud Computing, Trade-offs, Multi-Objective Optimization [less ▲]

Similarity testing for access control

in Information and Software Technology (2015), 58

Context: Access control is among the most important security mechanisms, and XACML is the de facto standard for specifying, storing and deploying access control policies. Since it is critical that ... [more ▼]

Context: Access control is among the most important security mechanisms, and XACML is the de facto standard for specifying, storing and deploying access control policies. Since it is critical that enforced policies are correct, policy testing must be performed in an effective way to identify potential security flaws and bugs. In practice, exhaustive testing is impossible due to budget constraints. Therefore the tests need to be prioritized so that resources are focused on their most relevant subset. Objective: This paper tackles the issue of access control test prioritization. It proposes a new approach for access control test prioritization that relies on similarity. Method: The approach has been applied to several policies and the results have been compared to random prioritization (as a baseline). To assess the different prioritization criteria, we use mutation analysis and compute the mutation scores reached by each criterion. This helps assessing the rate of fault detection. Results: The empirical results indicate that our proposed approach is effective and its rate of fault detection is higher than that of random prioritization. Conclusion: We conclude that prioritization of access control test cases can be usefully based on similarity criteria. © 2014 Elsevier B.V. All rights reserved. [less ▲]

Optimizing Multi-Objective Evolutionary Algorithms to Enable Quality-Aware Software Provisioning

Scientific Conference (2014, October)

Generic Cloud Platform Multi-objective Optimization Leveraging Models@run.time

Scientific Conference (2014, March)

Towards a Full Support of Obligations In XACML

Scientific Conference (2014)

Selection of Regression System Tests for Security Policy Evolution

Scientific Conference (2012, September)

Refactoring access control policies for performance improvement

in Proceedings of the 3rd ACM/SPEC International Conference on Performance Engineering (2012, April)