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FZI Forschungszentrum Informatik, Germany
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27 Papers

Model-guided Security Analysis of Interconnected Embedded Systems

Topics: Component-Based Software Engineering; Domain-Specific Modeling; Systems Engineering

Authors: Yasamin Mahmoodi , Sebastian Reiter , Alexander Viehl , Oliver Bringmann and Wolfgang Rosenstiel

Affiliation: FZI Forschungszentrum Informatik, Germany

Digital Object Identifier: 10.5220/0006724606020609

Proceedings of MODELSWARD 2018, ISBN: 978-989-758-283-7

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Software-intensive and networked embedded systems implement more and more security critical tasks. The following paper presents a framework to support security analysis along the design process using virtual prototypes (VPs). VPs describe the interconnection between different system components, include actual application codes and even integrate existing physical prototypes. These enable the user to detect structural security flaws, implementation flaws and even hardware-based security problems. Benefits of using VPs are the early availability in the design process and the fact that VPs are based on software, therefore established security analysis methods for software can be applied. This paper provides a methodology and tooling support to apply VP in the context of security analyses. Especially the integration in a model-driven design (MDD) process is highlighted. A proposed security UML profile as well as code generation ease the VP-based analysis.
Collapse Button Related Ontology Subjects/Areas/Topics (8)
Applications and Software Development

Languages, Tools and Architectures

Software Engineering

Component-Based Software Engineering

Methodologies, Processes and Platforms

Systems Engineering
Domain-Specific Modeling and Domain-Specific Languages

Model-Driven Software Development

A Low-cost Life Sign Detection Method based on Time Series Analysis of Facial Feature Points

Topics: Biometrics; Pattern Recognition; Medical Signal Acquisition, Analysis and Processing; Image Analysis and Processing; Detection and Identification

Authors: Timon Bloecher 1 , Leyre Garralda Iriarte 2 , Johannes Schneider 1 , Christoph Zimmermann 1 and Wilhelm Stork 1

Affiliations: 1 FZI Forschungszentrum Informatik, Germany , 2 Public University of Navarre, Spain

Digital Object Identifier: 10.5220/0006141601470154

Proceedings of BIOSIGNALS 2017/BIOSTEC, ISBN: 978-989-758-212-7

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The use of image based presentation attack detection (PAD) systems has experienced an enormous growth of interest in recent years. The most accurate techniques in literature addressing this topic rely on the verification of the actual three-dimensionality of the face, which increases complexity and costs of the system. In this work, we propose an effective and low-cost face spoofing detector system to supplement a PPGI-based vital signal monitoring application. Starting from a set of automatically located facial feature points, the movement information of this set of points was obtained. Based on a time series analysis of the landmark position distances using peak descriptors and cross-correlation coefficients as classifiers in a sliding window, life signs have been exploited to develop a system being able to recognize false detections and biometric spoofs. To verify the performance, experiments on three different benchmark datasets (CASIA face anti-spoofing, MSU and IDIAP Replay-Attack databases) were made. The evaluation of the proposed low-cost approach showed good results (accuracy of ~85-95%) compared to more resource-intensive state-of-the-art methods.
Collapse Button Related Ontology Subjects/Areas/Topics (23)
Applications

Data Manipulation

Neurocomputing

Applications and Services

Detection and Identification

Neurotechnology, Electronics and Informatics

Artificial Intelligence

Health Engineering and Technology Applications

Pattern Recognition

Biomedical Engineering

Human-Computer Interaction

Physiological Computing Systems

Biomedical Signal Processing

Medical Image Detection, Acquisition, Analysis and Processing

Sensor Networks

Biometrics

Methodologies and Methods

Soft Computing

Biometrics and Pattern Recognition

Multimedia

Telecommunications
Computer Vision, Visualization and Computer Graphics

Multimedia Signal Processing

SEMF – The Semantic Engineering Modeling Framework - Bringing Semantics into the Eclipse Modeling Framework for Space Systems Engineering

Topics: Meta-Modeling: Foundations and Tools; Reasoning about Models; Model-Driven Architecture; Systems Engineering; Frameworks for Model-Driven Development

Authors: Tobias Hoppe 1 , Harald Eisenmann 2 , Alexander Viehl 3 and Oliver Bringmann 4

Affiliations: 1 Airbus DS GmbH and FZI Research Center for Information Technology, Germany , 2 Airbus DS GmbH, Germany , 3 FZI Research Center for Information Technology, Germany , 4 FZI Research Center for Information Technology and University of Tübingen, Germany

Digital Object Identifier: 10.5220/0006118702930301

Proceedings of MODELSWARD 2017, ISBN: 978-989-758-210-3

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This paper presents an approach to integrate concepts realizing multiple classification and dynamic reclassification into the Eclipse Modeling Framework (EMF) in order to overcome the restricted number of modeling concepts of EMF and the strong class-object-relationship of Java. Hereby, the impact of integrating knowledge modeling approaches – as realized with Protégé – into EMF without extending Java itself is examined. Consequently, objects are configurable during the system development life-cycle by retyping. In combination with reasoning functionality – as known from knowledge management frameworks – several pieces of knowledge can be inferred and checked automatically as illustrated by examples from aerospace industry. As a result, inconsistencies can be revealed much easier leading to considerably less potential for failures and a drastically reduction of follow-on costs. Significant improvements in areas like, object classification, knowledge derivation, and guided system development, are highlighted in this paper.
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Frameworks for Model-Driven Development

Model-Driven Architecture

Reasoning about Models

Languages, Tools and Architectures

Model-Driven Software Development

Software Engineering

MetaModeling

Models

Systems Engineering
Methodologies, Processes and Platforms

Paradigm Trends

A Methodology for Deriving Conceptual Data Models from Systems Engineering Artefacts

Topics: Business Process Modeling; Domain-Specific Modeling; Meta-Modeling: Foundations and Tools; Constraint Modeling and Languages; Systems Engineering

Authors: Christian Hennig 1 , Harald Eisenmann 1 , Alexander Viehl 2 and Oliver Bringmann 3

Affiliations: 1 Airbus Defence and Space, Germany , 2 FZI Research Center for Information Technology, Germany , 3 Eberhard-Karls-University of Tübingen, Germany

Digital Object Identifier: 10.5220/0005676604970508

Proceedings of MODELSWARD 2016, ISBN: 978-989-758-168-7

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This paper presents a novel methodology for deriving Conceptual Data Models in the scope of Model-based Systems Engineering. Based on an assessment of currently employed methodologies, substantial limitations of the state of the art are identified. Consequently, a new methodology, overcoming present shortcomings, is elaborated, containing detailed and prescriptive guidelines for deriving conceptual data models used for representing engineering data in a multi-disciplinary design process. For highlighting the applicability and benefits of the approach, the derivation of a semantically strong conceptual data model in the context of Model-based Space Systems Engineering is presented as a case study.
Collapse Button Related Ontology Subjects/Areas/Topics (18)
Artificial Intelligence

Enterprise Information Systems

Model-Driven Software Development

Business Process Management

Knowledge Management and Information Sharing

Models

Constraint Modeling and Languages

Knowledge-Based Systems

Paradigm Trends

Domain-Specific Modeling and Domain-Specific Languages

Languages, Tools and Architectures

Software Engineering

e-Business

MetaModeling

Symbolic Systems

Enterprise Engineering

Methodologies, Processes and Platforms

Systems Engineering

SCDML: A Language for Conceptual Data Modeling in Model-based Systems Engineering

Topics: Model Transformation; Domain-Specific Modeling; Meta-Modeling: Foundations and Tools; Constraint Modeling and Languages; Systems Engineering

Authors: Christian Hennig 1 , Tobias Hoppe 2 , Harald Eisenmann 1 , Alexander Viehl 2 and Oliver Bringmann 3

Affiliations: 1 Airbus Defence and Space, Germany , 2 FZI Research Center for Information Technology, Germany , 3 Eberhard-Karls-University of Tübingen, Germany

Digital Object Identifier: 10.5220/0005676501840192

Proceedings of MODELSWARD 2016, ISBN: 978-989-758-168-7

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This paper presents the design and usage of a language for Conceptual Data Modeling in Model-based Systems Engineering. Based on an existing analysis of presently employed data modeling languages, a new conceptual data modeling language is defined that brings together characteristic features from software engineering languages, features from languages classically employed for knowledge engineering, as well as entirely newly developed functional aspects. This language has been applied to model a spacecraft as an example, demonstrating its utility for developing complex, multidisciplinary systems in the scope of Modelbased Space Systems Engineering.
Collapse Button Related Ontology Subjects/Areas/Topics (11)
Constraint Modeling and Languages

Methodologies, Processes and Platforms

Paradigm Trends

Domain-Specific Modeling and Domain-Specific Languages

Model Transformation

Software Engineering

Languages, Tools and Architectures

Model-Driven Software Development

Systems Engineering
MetaModeling

Models

Survey on Textual Notations for the Unified Modeling Language

Topics: Domain-Specific Modeling; General-Purpose Modeling Languages and Standards; Syntax and Semantics of Modeling Languages

Authors: Stephan Seifermann and Henning Groenda

Affiliation: FZI Research Center for Information Technology, Germany

Digital Object Identifier: 10.5220/0005644900280039

Proceedings of MODELSWARD 2016, ISBN: 978-989-758-168-7

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The Unified Modeling Language (UML) has become the lingua franca of software description languages. Textual notations of UML are also accessible for visually impaired people and allow a more developer-oriented and compact presentation. There are many textual notations that largely differ in their syntax, coverage of the UML, user editing experience, and applicability in teams due to the lack of a standardized textual notation. The available surveys do not cover the academic state of the art, the editing experience and applicability in teams. This implies heavy effort for evaluating and selecting notations. This survey identifies textual notations for UML that can be used instead of or in combination with graphical notations, e.g. by collaborating teams or in different contexts. We identified and rated the current state of 16 known notations plus 15 notations that were not covered in previous surveys. 20 categories cover the applicability in engineering teams. No single editable textual notation has full UML coverage. The mean coverage is 2.7 diagram types and editing support varies between none and 7 out of 9 categories. The survey facilitates the otherwise unclear notation selection and can reduce selection effort.
Collapse Button Related Ontology Subjects/Areas/Topics (6)
Domain-Specific Modeling and Domain-Specific Languages

Languages, Tools and Architectures

Software Engineering

General-Purpose Modeling Languages and Standards

Model-Driven Software Development

Syntax and Semantics of Modeling Languages

On Languages for Conceptual Data Modeling in Multi-disciplinary Space Systems Engineering

Topics: Domain-Specific Modeling; Syntax and Semantics of Modeling Languages; Constraint Modeling and Languages; Systems Engineering

Authors: Christian Hennig 1 , Harald Eisenmann 2 , Alexander Viehl 1 and Oliver Bringmann 3

Affiliations: 1 FZI Research Center for Information Technology, Germany , 2 Airbus Defence and Space, Germany , 3 Eberhard-Karls-University of Tübingen, Germany

Digital Object Identifier: 10.5220/0005329003840393

Proceedings of MODELSWARD 2015, ISBN: 978-989-758-083-3

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The engineering of complex systems is more and more supported through computer-based models that rely on a comprehensive specification of their underlying data. This paper reflects on extensive industrial experience with a sophisticated application of conceptual data modeling, addressing requirements as they arise in the context of space systems engineering. For this purpose identified needs for conceptual data modeling in the scope of Model-Based Systems Engineering are formulated. Established and evolving approaches and technologies for building conceptual data models are characterized, analyzed, and discussed regarding their suitability for modeling engineering data. Based on this analysis of the state of the art, recommendations for the future evolution of conceptual data modeling are formulated.
Collapse Button Related Ontology Subjects/Areas/Topics (8)
Constraint Modeling and Languages

Methodologies, Processes and Platforms

Syntax and Semantics of Modeling Languages

Domain-Specific Modeling and Domain-Specific Languages

Model-Driven Software Development

Systems Engineering
Languages, Tools and Architectures

Software Engineering

Comparison of Request Admission Based Performance Isolation Approaches in Multi-tenant SaaS Applications

Topics: Cloud Computing Architecture; Cloud Middleware Frameworks; Cloud Application Architectures; Cloud Applications Performance and Monitoring; Cloud Optimization and Automation; Qos for Applications on Clouds

Authors: Rouven Kreb 1 and Manuel Loesch 2

Affiliations: 1 SAP AG, Germany , 2 FZI Research Center for Information Technology, Germany

Digital Object Identifier: 10.5220/0004948804330438

Proceedings of CLOSER 2014, ISBN: 978-989-758-019-2

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In the Software-as-a-Service model one single application instance is usually shared between different tenants to decrease operational costs. However, sharing at this level may lead to undesired influence from one tenant onto the performance observed by the others. Intentionally, the application does not manage hardware resources and the responsible OS is not aware of application level entities like tenants. Consequently, it is difficult to control the performance of individual tenants to make sure they are isolated. In this paper we present an overview and classification of methods to ensure performance isolation based on request admission control. Further, informational requirements of these methods are discussed.
Collapse Button Related Ontology Subjects/Areas/Topics (10)
Cloud Application Architectures

Cloud Computing Enabling Technology

Fundamentals

Cloud Applications Performance and Monitoring

Cloud Middleware Frameworks

Platforms and Applications

Cloud Computing

Cloud Optimization and Automation

QoS for Applications on Clouds
Cloud Computing Architecture

Ontology Development towards Expressive and Reasoning-enabled Building Information Model for an Intelligent Energy Management System

Topics: Ontology Engineering; Decision Support Systems; Knowledge Representation; Applications and Case-Studies

Authors: Hendro Wicaksono , Preslava Dobreva , Polina Häfner and Sven Rogalski

Affiliation: Karlsruhe Institute of Technology, Germany

Digital Object Identifier: 10.5220/0004540300380047

Proceedings of KEOD 2013/IC3K, ISBN: 978-989-8565-81-5

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In recent years, energy consumption in buildings has been rising and is currently representing a significant percentage of the whole energy consumption on earth. The EU has responded this trend by requiring zero energy consumption by 2020 and by supporting innovative research approaches for improving energy efficiency in buildings without decreasing inhabitants comfort. This paper describes the approach to develop an intelligent system for building specific energy management that allows occupants and facility managers to monitor and control the energy consumption and also detects their wasting points. An ontology based information model for building energy management offering expressive representation and reasoning capability is also introduced in this paper. We highlight an approach to develop the ontology as the knowledge base providing the intelligence of the system. Furthermore we demonstrate how the energy performance analysis is improved using the ontology based approach.
Collapse Button Related Ontology Subjects/Areas/Topics (12)
Applications and Case-studies

Enterprise Information Systems

Knowledge-Based Systems

Artificial Intelligence

Information Systems Analysis and Specification

Ontologies and the Semantic Web

Data Engineering

Knowledge Engineering and Ontology Development

Ontology Engineering

Decision Support Systems

Knowledge Representation

Symbolic Systems

Semi-automated Ontology Population from Building Construction Drawings

Topics: Ontology Engineering; Decision Support Systems; Knowledge Acquisition; Applications and Case-Studies

Authors: Polina Häfner , Victor Häfner , Hendro Wicaksono and Jivka Ovtcharova

Affiliation: Karlsruhe Institute of Technology, Germany

Digital Object Identifier: 10.5220/0004626303790386

Proceedings of KEOD 2013/IC3K, ISBN: 978-989-8565-81-5

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Ontologies have been applied as knowledge representation in different domains, including intelligent building management. One of the challenges in using ontologies is the population with building specific information, such as the building elements and the energy consuming devices. The population usually has to be done manually by analysis and interpreting the building drawings, thus it requires extensive work. This is due to the lack of semantic information in the existing building construction drawings, which only contain geometrical information. However, it is possible to understand the semantics of the drawings, if the knowledge in interpreting the semantics of the symbols, shapes and other geometric information is present. This paper introduces a tool to extract the semantic information from CAD drawings and populate the ontology using the extracted semantic information in a semi-automatic way. The drawing primitives from CAD files are used to perform the pattern matching and classification algorithms to extract the semantic information. The resulting semantic information is then mapped to the corresponding ontology classes of a T-Box ontology. Finally individuals of the corresponding classes are created to populate the ontology and their geometric properties like world coordinate position and bounding box are set.
Collapse Button Related Ontology Subjects/Areas/Topics (12)
Applications and Case-studies

Enterprise Information Systems

Knowledge-Based Systems

Artificial Intelligence

Information Systems Analysis and Specification

Ontologies and the Semantic Web

Data Engineering

Knowledge Acquisition

Ontology Engineering

Decision Support Systems

Knowledge Engineering and Ontology Development

Symbolic Systems

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