Collaboration among organizations or individuals is common.While these participants are often unwilling to share all their information with each other, some information sharing is unavoidable when achieving a common goal. The need to share information and the desire to keep it confidential are two competing notions which affect the outcome of a collaboration. This paper proposes a formal model of collaboration which addresses confidentiality concerns. We draw on the notion of a plan which originates in the AI literature. We use data confidentiality policies to assess confidentiality in transition systems whose actions have an equal number of predicates in their pre-and post-conditions. Under two natural notions of policy compliance, we show that it is PSPACE-complete to schedule a plan leading from a 390 M. Kanovich et al.given initial state to a desired goal state while simultaneously deciding compliance with respect to the agents' policies.

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When collaborating agents share sensitive information to achieve a common goal it would be helpful to them to decide whether doing so will lead to an unwanted release of confidential data. These decisions are based on which other agents are involved, what those agents can do in the given context, and the individual confidentiality preferences of each agent. In this paper we consider a model of collaboration in which each agent has an explicit confidentiality policy. We offer three ways to interpret policy compliance (system compliance, plan compliance and weak plan compliance) corresponding to different levels of trust among the agents. We show it is EXPSPACE-complete to determine whether a given system is compliant and whether the agents can collaboratively reach a given common goal. On the other hand, we show it is undecidable to determine whether a given system has either a compliant plan or a weakly compliant plan leading to a common goal. The undecidability results are, in part, a consequence of the flexibility of the model, which allows interpretations of policy compliance that depend on current configurations.

Systems designed with measurement and attestation in mind are often layered, with the lower layers measuring the layers above them. Attestations of such systems, which we call layered attestations, must bundle together the results of a diverse set of application-specific measurements of various parts of the system. Some methods of layered attestation are more trustworthy than others, so it is important for system designers to understand the trust consequences of different system configurations. This paper presents a formal framework for reasoning about layered attestations, and provides generic reusable principles for achieving trustworthy results.

We present Copland, a language for specifying layered attestations. Layered attestations provide a remote appraiser with structured evidence of the integrity of a target system to support a trust decision. The language is designed to bridge the gap between formal analysis of attestation security guarantees and concrete implementations. We therefore provide two semantic interpretations of terms in our language. The first is a denotational semantics in terms of partially ordered sets of events. This directly connects Copland to prior work on layered attestation. The second is an operational semantics detailing how the data and control flow are executed. This gives explicit implementation guidance for attestation frameworks. We show a formal connection between the two semantics ensuring that any execution according to the operational semantics is consistent with the denotational event semantics. This ensures that formal guarantees resulting from analyzing the event semantics will hold for executions respecting the operational semantics. All results have been formally verified with the Coq proof assistant.