Michael Mrissa

Claude Bernard University Lyon 1, Villeurbanne, Rhône-Alpes, France

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Publications (41)7.02 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: Data as a Service (DaaS) builds on service-oriented technologies to enable fast access to data resources on the Web. However, this paradigm raises several new privacy concerns that traditional privacy models do not handle. In addition, DaaS composition may reveal privacy-sensitive information. In this paper, we propose a formal privacy model in order to extend DaaS descriptions with privacy capabilities. The privacy model allows a service to define a privacy policy and a set of privacy requirements. We also propose a privacy-preserving DaaS composition approach allowing to verify the compatibility between privacy requirements and policies in DaaS composition. We propose a negotiation mechanism that makes it possible to dynamically reconcile the privacy capabilities of services when incompatibilities arise in a composition. We validate the applicability of our proposal through a prototype implementation and a set of experiments.
    IEEE Transactions on Services Computing 01/2014; 7(2):210-222. · 2.46 Impact Factor
  • International Journal of Autonomous and Adaptive Communications Systems 01/2014;
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    ABSTRACT: Data services have almost become a standard way for data publishing and sharing on top of the Web. In this paper, we present a secure and privacy-preserving execution model for data services. Our model controls the information returned during service execution based on the identity of the data consumer and the purpose of the invocation. We implemented and evaluated the proposed model in the healthcare application domain. The obtained results are promising.
    Proceedings of the 25th international conference on Advanced Information Systems Engineering; 06/2013
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    ABSTRACT: Service composition is a major advance service-oriented computing brings to enable the development of distributed applications. However, the distributed nature of services hampers their composition with data heterogeneity problems. In this paper, we address these problems with a decentralized Mediation-as-a-Service architecture that solves data inconsistencies occurring during the composition of business services. As a particular data heterogeneity, we focus on the data interpretation problem and introduce conflictual aspect mediation services and conflictual aspect ontologies to solve data interpretation inconsistencies. We demonstrate how our architecture enables decentralized publication and discovery of mediation services. We motivate our work with a concrete scenario and validate our proposal with experiments.
    Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), 2013 IEEE 22nd International Workshop on; 01/2013
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    ABSTRACT: The composition of data-as-a-service (DaaS) services is a powerful solution for building value-added applications on top of existing ones. However, privacy concerns are still among the key challenges that keep hampering DaaS composition. Indeed, services may follow different, conflicting privacy specifications with respect to the data they use and provide. In this paper, we propose an approach for the privacy-aware composition of DaaS services. Our approach allows us to specify privacy requirements and policies and verify the compatibility of services involved in a composition. We propose an adaptation protocol that makes it possible to reconcile the privacy specifications of services when incompatibilities arise in a composition. We validate the applicability of our proposal through a set of experiments.
    IEEE Systems Journal 01/2013; 7(3):442-454. · 1.27 Impact Factor
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    ABSTRACT: Background and Motivation. The past few years have seen important advances in the domain of Semantic Web Services (SWS), especially in data mediation. Most work in the area has focused on the semantic alignement of input/output concepts at design time, and on schema-level integration [1]. Correct communication is not guaranteed even when two services are connected to each other with compatible input/output concepts. Indeed, conceptually compatible data may not be usable when data representation and scaling conflicts occur. To address this problem, which we refered to as the contextual heterogeneity problem, we rely on the Minimal Service Model [2] and operate with Linked Services as SWS that offer explicit semantics. In this paper, we present our Mediation as a Service (MaaS) architecture and demonstrate its applicability with a running scenario and a prototype.
    Proceedings of the First European conference on Service-Oriented and Cloud Computing; 09/2012
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    ABSTRACT: In this paper, we present a formal model for preserving privacy in Web services. We define a Web service-aware privacy model that deals with the privacy of input data, output data, and operation usage. We introduce a matching protocol that caters for partial and total privacy compatibility. We propose also a negotiation model to reconcile clients' requirements with providers' policies in case of incompatibility.
    01/2012;
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    [Show abstract] [Hide abstract]
    ABSTRACT: Semantic Web Services (SWS) aim at the automated discovery, selection and orchestration of Web services on the basis of comprehensive, machine-interpretable semantic descriptions. However, heterogeneities between distinct SWS representations pose strong limitations w.r.t. interoperability and reusability. Hence, semantic-level mediation, i.e. mediation between concurrent semantic representations of services, is a key requirement to allow SWS matchmaking algorithms to compare capabilities of distinct SWS. In that, semantic-level mediation requires to identify similarities across distinct SWS representations. Since current approaches to mediate between distinct service annotations rely either on manual one-to-one mappings or on semiautomatic mappings based on the exploitation of linguistic or structural similarities, these are perceived to be costly and error-prone. We propose a mediation approach enabling the implicit representation of similarities across distinct SWS by grounding these in so-called Mediation Spaces (MS). Given a set of SWS and their respective MS grounding, a general-purpose mediator automatically computes similarities to identify the most appropriate SWS for a given request. A prototypical application illustrates our approach.
    01/2011;
  • [Show abstract] [Hide abstract]
    ABSTRACT: Data as a Service (DaaS) builds on service-oriented technologies to enable fast access to data resources on the Web. However, this paradigm raises several new privacy concerns that traditional privacy models do not handle since they only focus on the service interface without taking into account privacy constraints related to the data exchanged with a DaaS during its invocation. In addition, DaaSs compositions may reveal also privacy-sensitive information. In this paper we propose a privacy formal model in order to extend DaaS descriptions with privacy capabilities. The privacy model allows a service to define a privacy policy and a set of privacy requirements. We propose also a privacy-preserving DaaS composition approach allowing to verify the compatibility between privacy requirements and policies in DaaS composition. We validate the applicability of our proposal with some experiments.
    Database and Expert Systems Applications - 22nd International Conference, DEXA 2011, Toulouse, France, August 29 - September 2, 2011. Proceedings, Part I; 01/2011
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    ABSTRACT: In the domain of DaaS {DaaS: Data-as-a-Service or information-providing service), completing a query means calling many services which are heterogeneous and built independently from the context in which they will be used. This heterogeneity leads to several compatibility problems during DaaS composition. In order to solve them, we propose a semantic description model which allows context characterization. The proposed model enables data mediation in the composition for resolving the conflicts caused by heterogeneities between DaaSs. We rely on two-layered mediated ontology for deriving automatically DaaSs compositions that incorporate necessary mediation services. A preliminary evaluation has been performed based on our initial investigation leading to better improvement.
    01/2011;
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    ABSTRACT: Due to the large development of medical information systems over the last few years, there is today a strong need for an infrastructure that uniformly integrates the distributed and heterogeneous collections of patient data to deliver value-added information to healthcare professionals at the points of care. The adoption of Electronic Health Records (EHRs) and Web services as a software infrastructure has become an extremely important prerequisite for patient data integration. In this paper we propose a semantic-enabled architecture for the automatic composition of EHR (Electronic Health Record) DaaSs (Data-as-a-Service). In our architecture, DaaSs are selected and composed automatically to resolve the user queries (i.e. queries posed by physicians, nurses, etc) using a query rewriting approach. Our proposed approach can also handle the semantic conflicts of data exchanged among component services in an EHR DaaS composition by deriving and applying automatically the necessary data conversions.
    T. Large-Scale Data- and Knowledge-Centered Systems. 01/2011; 4:95-123.
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    ABSTRACT: Data Mashup is a special class of mashup application that combines information on the fly from multiple data sources to respond to transient business needs. In this paper, we propose two optimization algorithms to optimize Data Mashups. The first allows for selecting the minimum number of services required in the data mashup. The second exploits the services' constraints on inputs and outputs to filter out superfluous calls to component services in the data mashup. These two algorithms are evaluated and tested in the healthcare application domain, and the reported results are very promising.
    IEEE International Conference on Services Computing, SCC 2011, Washington, DC, USA, 4-9 July, 2011; 01/2011
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    ABSTRACT: Rich types of data offered by data as a service(DaaS) in the cloud are typically associated with different and complex data concerns that DaaS service providers, data providers and data consumers must carefully examine and agree with before passing and utilizing data. Unlike service agreements, data agreements, reflecting conditions established on the basis of data concerns, between relevant stakeholders have got little attention. However, as data concerns are complex and contextual, given the trend of mixing data sources by automated techniques, such as data mash up, data agreements must be associated with data discovery, retrieval and utilization. Unfortunately, exchanging data agreements so far has not been automated and incorporated into service and data discovery and composition. In this paper, we analyze possible steps and propose interactions among data consumers, DaaS service providers and data providers in exchanging data agreements. Based on that, we present a novel service for composing, managing, analyzing data agreements for DaaS in cloud environments and data marketplaces.
    2011 IEEE Asia-Pacific Services Computing Conference, APSCC 2011, Jeju, Korea (South), December 12-15, 2011; 01/2011
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    ABSTRACT: Data Mashup is a special class of mashup appli- cation that combines information on the fly from multiple data sources to respond to transient business needs. Data mashup is a difficult task that would require an important programming skill on the side of mashups' creators, and involves handling many challenging privacy and security concerns raised by data providers. This situation prevents non-expert users from mashing up data at large. In this paper, we present a declarative approach for mashing-up data. The approach allows data mashup creators to build data mashups without any program- ming involved. The approach builds the mashups automatically and takes into account the data's privacy concerns. We evaluate the efficiency of the approach via a thorough set of experiments. The results show that handling data privacy introduces only a negligible cost in the mashup building time. Keywords-Privacy, Data Mashup, DaaS Web Services.
    IEEE International Conference on Web Services, ICWS 2011, Washington, DC, USA, July 4-9, 2011; 01/2011
  • Amin Mesmoudi, Michaël Mrissa, Mohand-Said Hacid
    [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, we investigate the combination of configuration and query rewriting for semantic Web service composition. Given a user query and a set of service descrip- tions, we rely on query rewriting to find services that imple- ment the functionalities expressed in the user query (discovery stage). Then, we use configuration to capture dependencies between services, and to generate a set of composed Web ser- vices described as a directed acyclic graph, while maintaining validity with respect to business rules (orchestration stage). Finally, we propose a semantic ranking algorithm to rank results according to user preferences (classification stage). The techniques used in our approach take into account the semantics of concepts utilized to describe the elements (services, business rules, query and user preferences) involved in the composition process. We provide a formal approach and its implementation, together with experiments on Web services from different application domains.
    IEEE International Conference on Web Services, ICWS 2011, Washington, DC, USA, July 4-9, 2011; 01/2011
  • [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, we present , a dynamic framework for preserving privacy in Web services. We define a Web service-aware privacy model that deals with the privacy of input data, output data, and operation usage. We introduce a matching protocol that caters for partial and total privacy compatibility. Finally, we propose a negotiation model to reconcile clients' requirements with providers' policies in case of incompatibility.
    Proceedings of the 2011 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2011, Campus Scientifique de la Doua, Lyon, France, August 22-27, 2011; 01/2011
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Data as a Service (DaaS) builds on service-oriented technologies to enable fast access to data resources on the Web. However, this paradigm raises several new concerns that traditional privacy models for Web services do not handle. First, the distinction between the roles of service providers and data providers is unclear, leaving the latter helpless for specifying and verifying the enforcement of their data privacy requirements. Second, traditional models for privacy policies focus only on the service interface without taking into account privacy policies related to data resources. Third, unstructured data resources, as well as user permissions and obligations related to data that are utilized in DaaS are not taken into account. In this paper, we study data privacy as one of these concerns, which relates to the management of private information. The main contribution of this paper consists in: 1)~devising a model for making explicit privacy constraints of DaaS, and 2)~on the basis of the proposed privacy model, developing techniques that allow handling the privacy concern when querying DaaS. We validate the applicability of our proposal with some experiments.
    Web Services, European Conference on. 11/2010;
  • [Show abstract] [Hide abstract]
    ABSTRACT: Semantic Web Services (SWS) aim at the automated discovery, selection and orchestration of Web services on the basis of comprehensive, machine-interpretable semantic descriptions. However, heterogeneities between distinct SWS representations pose strong limitations w.r.t. interoperability and reusability. Hence, semantic-level mediation, i.e. mediation between concurrent semantic representations of services, is a key requirement to allow SWS matchmaking algorithms to compare capabilities of distinct SWS. Semantic-level mediation requires to identify similarities across distinct SWS representations. Since current approaches rely either on manual one-to-one mappings or on semi-automatic mappings based on the exploitation of linguistic or structural similarities, these are perceived to be costly and error-prone. We propose a mediation approach enabling the implicit representation of similarities across distinct SWS by grounding these in so-called Mediation Spaces (MS). Given a set of SWS and their respective MS grounding, a general-purpose mediator automatically computes similarities to identify the most appropriate SWS for a given request. A prototypical application illustrates our approach.
    Service Oriented Computing and Applications 01/2010;
  • Source
    8th IEEE European Conference on Web Services (ECOWS 2010), 1-3 December 2010, Ayia Napa, Cyprus; 01/2010
  • Source
    Michael Mrissa, Philippe Thiran
    01/2010;

Publication Stats

161 Citations
7.02 Total Impact Points

Institutions

  • 2004–2013
    • Claude Bernard University Lyon 1
      Villeurbanne, Rhône-Alpes, France
  • 2010–2012
    • French National Centre for Scientific Research
      Lutetia Parisorum, Île-de-France, France
  • 2009–2010
    • University of Lyon
      Lyons, Rhône-Alpes, France
  • 2008
    • University of Namur
      • PROJUCIT Research Center
      Namen, Walloon Region, Belgium
  • 2005
    • Zayed University
      Abū Z̧aby, Abu Dhabi, United Arab Emirates
    • Université Bordeaux 1
      Talence, Aquitaine, France