Christina Michailidou

Topic: 
Risk aware data usage control
Research work: 

The objective of this research is to define a set of techniques and tools for the specification and monitoring of allowed data sharing in distributed organizations. The usage control policies can be related to the risk level computed by means of several factors. The tools developed will be also used for information sharing techniques related to cyber-crime prevention and forensics aspects of data management aligned to the European cyber-security directive and associated EU policies and regulatory requirements and recommendations.

ESRs Publications

Description:

Modern interconnected systems of systems, such as the Internet of Things (IoT), demand the presence of access and usage control mechanisms which will be able to manage the right of access to the corresponding services, and the plethora of information being generated in a daily basis. The Usage Control (UCON) model offers the means for fine-grained dynamic control of access to specific resources, by monitoring and evaluating the attributes defined within a dedicated security policy. However, a number of improvements can be introduced to the standard model regarding the simplification of the policy writing, but also the improvement of run-time efficiency and scalability. In this article, we discuss the limitations of the original UCON, and propose suitable enhancements for their remediation. Specifically, a risk aggregation framework is proposed to be added to the existing architecture, for dynamic role allocation and service grouping management, in order to improve the scalability, and run-time efficiency of the existing model.

Description:

The distributiveness and heterogeneity of today’s systems of systems, such as the Internet of Things (IoT), on-line banking systems, and contemporary emergency information systems, require the integration of access and usage control mechanisms, for managing the right of access both to the corresponding services, and the plethora of information that is generated in a daily basis. Usage Control (UCON) is such a mechanism, allowing the fine-grained policy based management of system resources, based on dynamic monitoring and evaluation of object, subject, and environmental attributes. Yet, as we presented in an earlier article, a number of improvements can be introduced to the standard model regarding its resilience on active attacks, the simplification of the policy writing, but also in terms of run-time efficiency and scalability. In this article, we present an enhanced usage control architecture, that was developed for tackling the aforementioned issues. In order to achieve that, a dynamic role allocation system will be added to the existing architecture, alongside with a service grouping functionality which will be based on attribute aggregation. This is structured in accordance to a risk-based framework, which has been developed in order to aggregate the risk values that the individual attributes encapsulate into a unified risk value. These architectural enhancements are utilized in order to improve the resilience, scalability, and run-time efficiency of the existing model.

Description:

Distributed environments such as Internet of Things, have an increasing need of introducing access and usage control mechanisms, to manage the rights to perform specific operations and regulate the access to the plethora of information daily generated by these devices. Defining policies which are specific to these distributed environments could be a challenging and tedious task, mainly due to the large set of attributes that should be considered, hence the upcoming of unforeseen conflicts or unconsidered conditions. In this paper we propose a qualitative risk-based usage control model, aimed at enabling a framework where is possible to define and enforce policies at different levels of granularity. In particular, the proposed framework exploits the Analytic Hierarchy Process (AHP) to coalesce the risk value assigned to different attributes in relation to a specific operation, in a single risk value, to be used as unique attribute of usage control policies. Two sets of experiments that show the benefits both in policy definition and in performance, validate the proposed model, demonstrating the equivalence of enforcement among standard policies and the derived single-attributed policies.