Comprehensive Life Cycle Support for Access Rules in Information Systems: The CEOSIS Project

The definition and management of access rules (e.g., to control access to business documents and business functions) is a fundamental task in any enterprise information system (EIS). While there exists considerable work on how to specify and represent access rules, only little research has been spent on access rule changes. Examples include the evolution of organizational models with need for subsequent adaptation of related access rules as well as direct access rule modifications (e.g., to state a previously defined rule more precisely). This paper presents a comprehensive change framework for the controlled evolution of role-based access rules in EIS. First, we consider changes of organizational models and elaborate how they affect existing access rules. Second, we define change operations which enable direct adaptations of access rules. In the latter context, we define the formal semantics of access rule changes based on operator trees. Particularly, this enables their unambiguous application; i.e., we can precisely determine which effects are caused by respective rule changes. This is important, for example, to be able to efficiently and correctly adapt user worklists in process-aware information systems. Altogether this paper contributes to comprehensive life cycle support for access rules in (adaptive) EIS

Improving the Policy Specification for Practical Access Control Systems

Access control systems play a crucial role in protecting the security of information systems by ensuring that only authorized users are granted access to sensitive resources, and the protection is only as good as the access control policies. For enabling a security administrator to express her desired policy conveniently, it is paramount that a policy specification is expressive, comprehensible, and free of inconsistencies. In this dissertation, we study the policy specifications for three practical access control systems (i.e., obligation systems, firewalls, and Security-Enhanced Linux in Android) and improve their expressiveness, comprehensibility, and consistency. First, we improve the expressiveness of obligation policies for handling different types of obligations. We propose a language for specifying obligations as well as an architecture for handling access control policies with these obligations, by extending XACML (i.e., the de facto standard for specifying access control policies). We also implement our design into a prototype system named ExtXACML to handle various obligations. Second, we improve the comprehensibility of firewall policies enabling administrators to better understand and manage the policies. We introduce the tri-modularized design of firewall policies for elevating them from monolithic to modular. To support legacy firewall policies, we also define a five-step process and present algorithms for converting them into their modularized form. Finally, we improve the consistency of Security-Enhanced Linux in Android (SEAndroid) policies for reducing the attack surface in Android systems. We propose a systematic approach as well as a semiautomatic tool for uncovering three classes of policy misconfigurations. We also analyze SEAndroid policies from four Android versions and seven Android phone vendors, and in all of them we observe examples of potential policy misconfigurations

Role recommender-RBAC: Optimizing user-role assignments in RBAC

In a rapidly changing IT environment, access to the resources involved in various projects might change randomly based on the role-based access control (RBAC) system. Hence, the security administrator needs to dynamically maintain the role assignments to users for optimizing user-role assignments. The manual updation of user-role assignments is prone to error and increases administrative workload. Therefore, a role recommendation model is introduced for the RBAC system to optimize user-role assignments based on user behaviour patterns. It is shown that the model automatically revokes and refurbishes the user-role assignments by observing user access behaviour. This model is used in the cloud for providing Role-Assignment-as-a-Service to optimize the cost of built-in roles. Several experiments are conducted to verify the proposed model using the Amazon access sample dataset. The experimental results show that the efficiency of the proposed model is 50% higher than the state-of-the-art

An Approach for Managing Access to Personal Information Using Ontology-Based Chains

The importance of electronic healthcare has caused numerous changes in both substantive and procedural aspects of healthcare processes. These changes have produced new challenges to patient privacy and information secrecy. Traditional privacy policies cannot respond to rapidly increased privacy needs of patients in electronic healthcare. Technically enforceable privacy policies are needed in order to protect patient privacy in modern healthcare with its cross organisational information sharing and decision making. This thesis proposes a personal information flow model that specifies a limited number of acts on this type of information. Ontology classified Chains of these acts can be used instead of the "intended/business purposes" used in privacy access control to seamlessly imbuing current healthcare applications and their supporting infrastructure with security and privacy functionality. In this thesis, we first introduce an integrated basic architecture, design principles, and implementation techniques for privacy-preserving data mining systems. We then discuss the key methods of privacypreserving data mining systems which include four main methods: Role based access control (RBAC), Hippocratic database, Chain method and eXtensible Access Control Markup Language (XACML). We found out that the traditional methods suffer from two main problems: complexity of privacy policy design and the lack of context flexibility that is needed while working in critical situations such as the one we find in hospitals. We present and compare strategies for realising these methods. Theoretical analysis and experimental evaluation show that our new method can generate accurate data mining models and safe data access management while protecting the privacy of the data being mined. The experiments followed comparative kind of experiments, to show the ease of the design first and then follow real scenarios to show the context flexibility in saving personal information privacy of our investigated method

Authorization schema for electronic health-care records: for Uganda

This thesis discusses how to design an authorization schema focused on ensuring each patient's data privacy within a hospital information system

Sustainable Identity and Access Management

For today's enterprises, information technology (IT) evolved into a key success factor affecting nearly all areas of value chains. As a consequence, identity and access management (IAM) is established for centralized and structured management of digital identities together with their access to internal assets. During this effort, a centralized management platform is created, which serves as middle-ware among available software systems and human resource applications, thereby creating a unified view and enabling business-oriented management. This enables the implementation of an according level of IT-security, business process automation and the alignment to external compliance requirements. However, as IT-infrastructures evolve over time, thereby leading to continuous changes and varying demands, these developments need to be addressed within IAM in a constant manner. As IAM is designed as a cross-cutting topic between business and IT , business requirements such as restructurings need to be realized likewise. Additionally, more and more legal requirements are set in place by external authorities which affect the way digital information are to be managed. Bringing together requirements of these different stakeholders in a comprehensive way imposes high complexity for enterprises, thereby leading to high administrational effort. This leads to a situation where enterprises are in need to constantly evaluate and adapt their implemented IAM strategy and execution. Thus the dissertation at hand is devoted to provide means of aligning IAM to a more sustainable way of operation. Within information systems research, sustainability comprises the ability to meet the needs of today without hindering future developments. To achieve this, the two concepts IAM measurement and IAM policies are leveraged. Firstly, IAM measurement enables enterprises to achieve detailed information concerning the state of an IAM infrastructure. Secondly, this effort is fostered to shift IAM to a more dynamic way of operation and provide suitable recommendations concerning how to adjust different aspects of IAM in a long-term manner. During the research process, the presented approaches have been evaluated within real-world scenarios to outline their relevance and demonstrate practical applicability

Adaptive identity and access management—contextual data based policies

Due to compliance and IT security requirements, company-wide identity and access management within organizations has gained significant importance in research and practice over the last years. Companies aim at standardizing user management policies in order to reduce administrative overhead and strengthen IT security. These policies provide the foundation for every identity and access management system no matter if poured into IT systems or only located within responsible identity and access management (IAM) engineers’ mind. Despite its relevance, hardly any supportive means for the automated detection and refinement as well as management of policies are available. As a result, policies outdate over time, leading to security vulnerabilities and inefficiencies. Existing research mainly focuses on policy detection and enforcement without providing the required guidance for policy management nor necessary instruments to enable policy adaptibility for today’s dynamic IAM. This paper closes the existing gap by proposing a dynamic policy management process which structures the activities required for policy management in identity and access management environments. In contrast to current approaches, it utilizes the consideration of contextual user management data and key performance indicators for policy detection and refinement and offers result visualization techniques that foster human understanding. In order to underline its applicability, this paper provides an evaluation based on real-life data from a large industrial company

Scalable And Secure Provenance Querying For Scientific Workflows And Its Application In Autism Study

In the era of big data, scientific workflows have become essential to automate scientific experiments and guarantee repeatability. As both data and workflow increase in their scale, requirements for having a data lineage management system commensurate with the complexity of the workflow also become necessary, calling for new scalable storage, query, and analytics infrastructure. This system that manages and preserves the derivation history and morphosis of data, known as provenance system, is essential for maintaining quality and trustworthiness of data products and ensuring reproducibility of scientific discoveries. With a flurry of research and increased adoption of scientific workflows in processing sensitive data, i.e., health and medication domain, securing information flow and instrumenting access privileges in the system have become a fundamental precursor to deploying large-scale scientific workflows. That has become more important now since today team of scientists around the world can collaborate on experiments using globally distributed sensitive data sources. Hence, it has become imperative to augment scientific workflow systems as well as the underlying provenance management systems with data security protocols. Provenance systems, void of data security protocol, are susceptible to vulnerability. In this dissertation research, we delineate how scientific workflows can improve therapeutic practices in autism spectrum disorders. The data-intensive computation inherent in these workflows and sensitive nature of the data, necessitate support for scalable, parallel and robust provenance queries and secured view of data. With that in perspective, we propose $OPQL^{Pig}$, a parallel, robust, reliable and scalable provenance query language and introduce the concept of access privilege inheritance in the provenance systems. We characterize desirable properties of role-based access control protocol in scientific workflows and demonstrate how the qualities are integrated into the workflow provenance systems as well. Finally, we describe how these concepts fit within the DATAVIEW workflow management system