A Fully Decentralized Data Usage Control Enforcement Infrastructure

Kelbert, Florian; Pretschner, Alexander

doi:10.1007/978-3-319-28166-7_20

Cited by 16 publications

(14 citation statements)

References 22 publications

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“…Another work [15] focuses on using data usage control in distributed systems, in particular, when having a data flow in-between different connected systems. Fully decentralised infrastructure for enforcement of global usage control is introduced in [16], where the data as well as the events for the data usage occur in multiple distributed systems. Our work is taking into account all the above issues, faced by the usage control literature, as it permits policies that represent permissions, denials, obligations and delegations of rights.…”

Section: Related Workmentioning

confidence: 99%

Enabling Data Sharing in Contextual Environments

Karafili

Lupu

2017

Proceedings of the 22nd ACM on Symposium on Access Control Models and Technologies

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Internet of Things environments enable us to capture more and more data about the physical environment we live in and about ourselves. The data enable us to optimise resources, personalise services and offer unprecedented insights into our lives. However, to achieve these insights data need to be shared (and sometimes sold) between organisations imposing rights and obligations upon the sharing parties and in accordance with multiple layers of sometimes conflicting legislation at international, national and organisational levels. In this work, we show how such rules can be captured in a formal representation called "Data Sharing Agreements". We introduce the use of abductive reasoning and argumentation based techniques to work with context dependent rules, detect inconsistencies between them, and resolve the inconsistencies by assigning priorities to the rules. We show how through the use of argumentation based techniques use-cases taken from real life application are handled flexibly addressing trade-offs between confidentiality, privacy, availability and safety.

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Section: Related Workmentioning

confidence: 99%

Enabling Data Sharing in Contextual Environments

Karafili

Lupu

2017

Proceedings of the 22nd ACM on Symposium on Access Control Models and Technologies

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“…While the monitors integrated into the PaaS take care about policy enforcement, they depend on an external Decision Engine from the literature [12,19] which is responsible for decision making and further management tasks. In order to keep the architecture modular, a Coordinator coordinates the interactions between components.…”

Section: A Overviewmentioning

confidence: 99%

“…Based on the history of events, the current mappings between data and containers, as well as the deployed policies, the Decision Engine decides about the event's compliance. While this decision process is detailed in [12,14,19], we describe its most relevant aspects.…”

Section: F Policy Decisions and Decision Enforcementmentioning

confidence: 99%

“…Once data is about to leave these system boundaries, e.g. if data is sent to a remote system, the infrastructure must either ensure that remote systems are equipped with a similar data protection infrastructure [12,13], or that sensitive data is not disclosed at all. Similarly, our approach is not able to prevent data misuse at software or hardware layers below the PaaS.…”

Section: Limitationsmentioning

confidence: 99%

“…Our solution works as follows: Data usage control technology [7,12,18,19] is integrated into the Software Execution Environment (SEE) (e.g., Java Runtime Environment (RTE), .NET CLR, PHP interpreter) which is then supposed to be provided in a Platform-as-a-Service (PaaS) manner by trustworthy entities. Such trustworthy entities might include the OSN operator herself, public universities, or consumer protection organizations (cf.…”

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confidence: 99%

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Compliance Monitoring of Third-Party Applications in Online Social Networks

Kelbert

Fromm

2016

2016 IEEE Security and Privacy Workshops (SPW)

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Abstract-With the widespread adoption of Online Social Networks (OSNs), users increasingly also use corresponding thirdparty applications (TPAs), such as social games and applications for collaboration. To improve their social experience, TPAs access users' personal data via an API provided by the OSN. Applications are then expected to comply with certain security and privacy policies when handling the users' data. However, in practice, they might store, use, and distribute that data in all kinds of unapproved ways. We present an approach that transparently enforces security and privacy policies on TPAs that integrate with OSNs. To this end, we integrate concepts and implementations from the research areas of data usage control and information flow control. We instantiate these results in the context of TPAs in OSNs in order to enforce compliance with security and privacy policies that are provided by the OSN operator. We perform a preliminary evaluation of our approach on the basis of a TPA that integrates with the Facebook API.

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