The POLIPO Security Framework

Systems of systems are dynamic coalitions of distributed, autonomous and heterogeneous systems that collaborate to achieve a common goal. While offering several advantages in terms of scalability and flexibility, the systems of systems paradigm has a significant impact on systems interoperability and on the security requirements of the collaborating systems. In this chapter we introduce POLIPO, a security framework that protects the information exchanged among the systems in a system of systems, while preserving systems’ autonomy and interoperability. Information is protected from unauthorized access and improper modification by combining context-aware access control with trust management. Autonomy and interoperability are enabled by the use of ontology-based services. More precisely, each authority may refer to different ontologies to define the semantics of the terms used in the security policy of the system it governs and to describe domain knowledge and context information. A semantic alignment technique is then employed to map concepts from different ontologies and align the systems’ vocabularies. We demonstrate the applicability of our solution with a prototype implementation of the framework for a scenario in the maritime safety and security domain

A study of existing Ontologies in the IoT-domain

Several domains have adopted the increasing use of IoT-based devices to collect sensor data for generating abstractions and perceptions of the real world. This sensor data is multi-modal and heterogeneous in nature. This heterogeneity induces interoperability issues while developing cross-domain applications, thereby restricting the possibility of reusing sensor data to develop new applications. As a solution to this, semantic approaches have been proposed in the literature to tackle problems related to interoperability of sensor data. Several ontologies have been proposed to handle different aspects of IoT-based sensor data collection, ranging from discovering the IoT sensors for data collection to applying reasoning on the collected sensor data for drawing inferences. In this paper, we survey these existing semantic ontologies to provide an overview of the recent developments in this field. We highlight the fundamental ontological concepts (e.g., sensor-capabilities and context-awareness) required for an IoT-based application, and survey the existing ontologies which include these concepts. Based on our study, we also identify the shortcomings of currently available ontologies, which serves as a stepping stone to state the need for a common unified ontology for the IoT domain.Comment: Submitted to Elsevier JWS SI on Web semantics for the Internet/Web of Thing

Semantic web technologies for video surveillance metadata

Video surveillance systems are growing in size and complexity. Such systems typically consist of integrated modules of different vendors to cope with the increasing demands on network and storage capacity, intelligent video analytics, picture quality, and enhanced visual interfaces. Within a surveillance system, relevant information (like technical details on the video sequences, or analysis results of the monitored environment) is described using metadata standards. However, different modules typically use different standards, resulting in metadata interoperability problems. In this paper, we introduce the application of Semantic Web Technologies to overcome such problems. We present a semantic, layered metadata model and integrate it within a video surveillance system. Besides dealing with the metadata interoperability problem, the advantages of using Semantic Web Technologies and the inherent rule support are shown. A practical use case scenario is presented to illustrate the benefits of our novel approach

Knowledge formalization in experience feedback processes : an ontology-based approach

Because of the current trend of integration and interoperability of industrial systems, their size and complexity continue to grow making it more difficult to analyze, to understand and to solve the problems that happen in their organizations. Continuous improvement methodologies are powerful tools in order to understand and to solve problems, to control the effects of changes and finally to capitalize knowledge about changes and improvements. These tools involve suitably represent knowledge relating to the concerned system. Consequently, knowledge management (KM) is an increasingly important source of competitive advantage for organizations. Particularly, the capitalization and sharing of knowledge resulting from experience feedback are elements which play an essential role in the continuous improvement of industrial activities. In this paper, the contribution deals with semantic interoperability and relates to the structuring and the formalization of an experience feedback (EF) process aiming at transforming information or understanding gained by experience into explicit knowledge. The reuse of such knowledge has proved to have significant impact on achieving themissions of companies. However, the means of describing the knowledge objects of an experience generally remain informal. Based on an experience feedback process model and conceptual graphs, this paper takes domain ontology as a framework for the clarification of explicit knowledge and know-how, the aim of which is to get lessons learned descriptions that are significant, correct and applicable

Improving Knowledge Retrieval in Digital Libraries Applying Intelligent Techniques

Nowadays an enormous quantity of heterogeneous and distributed information is stored in the digital University. Exploring online collections to find knowledge relevant to a user’s interests is a challenging work. The artificial intelligence and Semantic Web provide a common framework that allows knowledge to be shared and reused in an efficient way. In this work we propose a comprehensive approach for discovering E-learning objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. We have used Case Based-Reasoning methodology to develop a prototype for supporting efficient retrieval knowledge from online repositories. We suggest a conceptual architecture for a semantic search engine. OntoUS is a collaborative effort that proposes a new form of interaction between users and digital libraries, where the latter are adapted to users and their surroundings

Re-use of an ontology for modelling urban energy systems

The use of ontologies for the interoperability of software models is widespread, with many applications also in the energy domain. By formulating a shared data structure and a definition of concepts and their properties, a language is created that can be used between modellers and - formalised in an ontology - between model components. When modelling energy systems, connections between different infrastructures are critical, e.g. the interaction between the gas and electricity markets or the need for various infrastructures including power, heat, water and transport in cities. While a commonly shared ontology of energy systems would be highly desirable, the fact is that different existing models or applications already use dedicated ontologies, and have been demonstrated to work well using them. To benefit from linking data sources and connecting models developed with different ontologies, a translation between concepts can be made. In this paper a model of an urban energy system built upon one ontology is initialised using energy transformation technologies defined in another ontology, thus illustrating how this common perspective might benefit researchers in the energy domain. ©2010 IEEE

The Information-Flow Approach to Ontology-Based Semantic Integration

In this article we argue for the lack of formal foundations for ontology-based semantic alignment. We analyse and formalise the basic notions of semantic matching and alignment and we situate them in the context of ontology-based alignment in open-ended and distributed environments, like the Web. We then use the mathematical notion of information flow in a distributed system to ground three hypotheses that enable semantic alignment. We draw our exemplar applications of this work from a variety of interoperability scenarios including ontology mapping, theory of semantic interoperability, progressive ontology alignment, and situated semantic alignment