Biblio

A common way to characterize security enforcement mechanisms is based on the time at which they operate. Mechanisms operating before a program's execution are static mechanisms, and mechanisms operating during a program's execution are dynamic mechanisms. This paper introduces a different perspective and classifies mechanisms based on the granularity of program code that they monitor. Classifying mechanisms in this way provides a unified view of security mechanisms and shows that all security mechanisms can be encoded as dynamic mechanisms that operate at different levels of program code granularity. The practicality of the approach is demonstrated through a prototype implementation of a framework for enforcing security policies at various levels of code granularity on Java bytecode applications.

By migrating their data and operations to the cloud, enterprises are able to gain significant benefits in terms of cost savings, increased availability, agility and productivity. Yet, the shared and on-demand nature of the cloud paradigm introduces a new breed of security threats that generally deter stakeholders from relinquishing control of their critical assets to third-party cloud providers. One way to thwart these threats is to instill suitable access control policies into cloud services that protect these assets. Nevertheless, the dynamic nature of cloud environments calls for policies that are able to incorporate a potentially complex body of contextual knowledge. This complexity is further amplified by the interplay that inevitably occurs between the different policies, as well as by the dynamically-evolving nature of an organisation's business and security needs. We argue that one way to tame this complexity is to devise a generic framework that facilitates the governance of policies. This paper presents a particular aspect of such a framework, namely an approach to determining the repercussions that policy retirement actions have on the overall protection of critical assets in the cloud.

The cloud computing paradigm enables enterprises to realise significant cost savings whilst boosting their agility and productivity. However, security and privacy concerns generally deter enterprises from migrating their critical data to the cloud. One way to alleviate these concerns, hence bolster the adoption of cloud computing, is to devise adequate security policies that control the manner in which these data are stored and accessed in the cloud. Nevertheless, for enterprises to entrust these policies, a framework capable of providing assurances about their correctness is required. This work proposes such a framework. In particular, it proposes an approach that enables enterprises to define their own view of what constitutes a correct policy through the formulation of an appropriate set of well-formedness constraints. These constraints are expressed ontologically thus enabling–-by virtue of semantic inferencing–- automated reasoning about their satisfaction by the policies.

By embracing the cloud computing paradigm enterprises are able to boost their agility and productivity whilst realising significant cost savings. However, many enterprises are reluctant to adopt cloud services for supporting their critical operations due to security and privacy concerns. One way to alleviate these concerns is to devise policies that infuse suitable security controls in cloud services. This work proposes a class of ontologically-expressed rules, namely the so-called axiomatic rules, that aim at ensuring the correctness of these policies by harnessing the various knowledge artefacts that they embody. It also articulates an adequate framework for the expression of policies, one which provides ontological templates for modelling the knowledge artefacts encoded in the policies and which form the basis for the proposed axiomatic rules.