Towards a Formal Model of Privacy-Sensitive Dynamic Coalitions

The concept of dynamic coalitions (also virtual organizations) describes the temporary interconnection of autonomous agents, who share information or resources in order to achieve a common goal. Through modern technologies these coalitions may form across company, organization and system borders. Therefor questions of access control and security are of vital significance for the architectures supporting these coalitions. In this paper, we present our first steps to reach a formal framework for modeling and verifying the design of privacy-sensitive dynamic coalition infrastructures and their processes. In order to do so we extend existing dynamic coalition modeling approaches with an access-control-concept, which manages access to information through policies. Furthermore we regard the processes underlying these coalitions and present first works in formalizing these processes. As a result of the present paper we illustrate the usefulness of the Abstract State Machine (ASM) method for this task. We demonstrate a formal treatment of privacy-sensitive dynamic coalitions by two example ASMs which model certain access control situations. A logical consideration of these ASMs can lead to a better understanding and a verification of the ASMs according to the aspired specification.Comment: In Proceedings FAVO 2011, arXiv:1204.579

AI for the Common Good?! Pitfalls, challenges, and Ethics Pen-Testing

Recently, many AI researchers and practitioners have embarked on research visions that involve doing AI for "Good". This is part of a general drive towards infusing AI research and practice with ethical thinking. One frequent theme in current ethical guidelines is the requirement that AI be good for all, or: contribute to the Common Good. But what is the Common Good, and is it enough to want to be good? Via four lead questions, I will illustrate challenges and pitfalls when determining, from an AI point of view, what the Common Good is and how it can be enhanced by AI. The questions are: What is the problem / What is a problem?, Who defines the problem?, What is the role of knowledge?, and What are important side effects and dynamics? The illustration will use an example from the domain of "AI for Social Good", more specifically "Data Science for Social Good". Even if the importance of these questions may be known at an abstract level, they do not get asked sufficiently in practice, as shown by an exploratory study of 99 contributions to recent conferences in the field. Turning these challenges and pitfalls into a positive recommendation, as a conclusion I will draw on another characteristic of computer-science thinking and practice to make these impediments visible and attenuate them: "attacks" as a method for improving design. This results in the proposal of ethics pen-testing as a method for helping AI designs to better contribute to the Common Good.Comment: to appear in Paladyn. Journal of Behavioral Robotics; accepted on 27-10-201

Assessing Security Risk and Requirements for Systems of Systems

A System of Systems (SoS) is a term used to describe independent systems converging for a purpose that could only be carried out through this interdependent collaboration. Many examples of SoSs exist, but the term has become a source of confusion across domains. Moreover, there are few illustrative SoS examples demonstrating their initial classification and structure. While there are many approaches for engineering of systems, less exist for SoS engineering. More specifically, there is a research gap towards approaches addressing SoS security risk assessment for engineering and operational needs, with a need for tool-support to assist modelling and visualising security risk and requirements in an interconnected SoS. From this, security requirements can provide a systematic means to identify constraints and related risks of the SoS, mitigated by human-user and system requirements. This work investigates specific challenges and current approaches for SoS security and risk, and aims to identify the alignment of SoS factors and concepts suitable for eliciting, analysing, validating risks with use of a tool-support for assessing security risk in the SoS context

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Secure data sharing and processing in heterogeneous clouds

The extensive cloud adoption among the European Public Sector Players empowered them to own and operate a range of cloud infrastructures. These deployments vary both in the size and capabilities, as well as in the range of employed technologies and processes. The public sector, however, lacks the necessary technology to enable effective, interoperable and secure integration of a multitude of its computing clouds and services. In this work we focus on the federation of private clouds and the approaches that enable secure data sharing and processing among the collaborating infrastructures and services of public entities. We investigate the aspects of access control, data and security policy languages, as well as cryptographic approaches that enable fine-grained security and data processing in semi-trusted environments. We identify the main challenges and frame the future work that serve as an enabler of interoperability among heterogeneous infrastructures and services. Our goal is to enable both security and legal conformance as well as to facilitate transparency, privacy and effectivity of private cloud federations for the public sector needs. © 2015 The Authors