Secure and Privacy-Preserving Execution Model for Data Services

Barhamgi, Mahmoud; Benslimane, Djamal; Oulmakhzoune, Said; Cuppens-Boulahia, Nora; Cuppens, Frédéric; Mrissa, Michaël; Taktak, Hajer

doi:10.1007/978-3-642-38709-8_3

Cited by 11 publications

(10 citation statements)

References 17 publications

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“…We have evaluated our composition-based approach in the healthcare and the bioinformatics domains. The obtained results [5,9,7,14,8,16,6] are promising.…”

Section: Resultsmentioning

confidence: 98%

“…When a data service is invoked, our model rewrites its corresponding RDF view to take into account applicable security and privacy rules from the service's associated policies, which are expressed using the OrBAC and PrivOrBAC models over domain ontologies and take into account the data recipient (i.e., service consumer), his purpose for requesting the data, and the consents of data subjects [16]. The soundness and correctness of our algorithm are demonstrated in [16,8].…”

Section: Privacy-preserving Service Execution Modelmentioning

confidence: 99%

“…Security and privacy preservation : The conducted experiments in [8] showed that our secure and privacy preserving service execution model added only a small increase to the service execution time. In all experiments, the cost incurred in the enforcement of security and privacy constraints did not exceed 10% of the time required to execute the service with ignoring these security and privacy constraints altogether.…”

Section: Implementation and Evaluationmentioning

confidence: 99%

“…• Privacy preservation: We proposed a privacy preserving composition model [5,8,16]. Our model allows services providers to locally enforce their privacy and security policies when their services are invoked.…”

Section: Introductionmentioning

confidence: 99%

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Pairse

et al. 2013

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Privacy is among the key challenges to data integration in many sectors, including healthcare, e-government, etc. The PAIRSE project aims at providing a flexible, looselycoupled and privacy-preserving data integration system in P2P environments. The project exploits recent Web standards and technologies such as Web services and ontologies to export data from autonomous data providers as reusable services, and proposes the use of service composition as a viable solution to answer data integration needs on the fly. The project proposed new composition algorithms and service/composition execution models that preserve privacy of data manipulated by services and compositions. The proposed integration system was demonstrated at EDBT 2013 and VLDB 2011.

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“…We have evaluated our composition-based approach in the healthcare and the bioinformatics domains. The obtained results [5,9,7,14,8,16,6] are promising.…”

Section: Resultsmentioning

confidence: 98%

Section: Privacy-preserving Service Execution Modelmentioning

confidence: 99%

Section: Implementation and Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Pairse

et al. 2013

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“…Risk aware information disclosure in [9] can be used for Hadoop Data lake. Secure information access model via data services [11] can be applied for Hadoop data services. HDFS can use data access protection using data distribution and swapping in [16].…”

Section: Related Workmentioning

confidence: 99%

Object-Tagged RBAC Model for the Hadoop Ecosystem

Gupta

Patwa

Sandhu

2017

Data and Applications Security and Privacy XXXI

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Hadoop ecosystem provides a highly scalable, fault-tolerant and cost-effective platform for storing and analyzing variety of data formats. Apache Ranger and Apache Sentry are two predominant frameworks used to provide authorization capabilities in Hadoop ecosystem. In this paper we present a formal multi-layer access control model (called HeAC) for Hadoop ecosystem, as an academic-style abstraction of Ranger, Sentry and native Apache Hadoop access-control capabilities. We further extend HeAC base model to provide a cohesive object-tagged role-based access control (OT-RBAC) model, consistent with generally accepted academic concepts of RBAC. Besides inheriting advantages of RBAC, OT-RBAC offers a novel method for combining RBAC with attributes (beyond NIST proposed strategies). Additionally, a proposed implementation approach for OT-RBAC in Apache Ranger, is presented. We further outline attribute-based extensions to OT-RBAC.

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FACTS: A Framework for Anonymity towards Comparability, Transparency, and Sharing

Heidinger

Böhm

Buchmann

et al. 2014

Advanced Information Systems Engineering

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In past years, many anonymization schemes, anonymity notions, and anonymity measures have been proposed. When designing information systems that feature anonymity, choosing a good approach is a very important design choice. While experiments comparing such approaches are enlightening, carrying out such experiments is a complex task and is labor-intensive. To address this issue, we propose the framework FACTS for the experimental evaluation of anonymization schemes. It lets researchers implement their approaches against interfaces and other standardizations that we have devised. Users can then define benchmark suites that refer to those implementations. FACTS gives way to comparability, and it includes many useful features, e.g., easy sharing and reproduction of experiments. We evaluate FACTS (a) by specifying and executing a comprehensive benchmark suite for data publishing and (b) by means of a user study. Core results are that FACTS is useful for a broad range of scenarios, that it allows to compare approaches with ease, and that it lets users share and reproduce experiments.

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Secure and Privacy-Preserving Execution Model for Data Services

Cited by 11 publications

References 17 publications

Pairse

Pairse

Object-Tagged RBAC Model for the Hadoop Ecosystem

FACTS: A Framework for Anonymity towards Comparability, Transparency, and Sharing

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