Towards a Cloud-Based Ontology for Service Model Security -- Technical Report

The adoption of cloud computing has brought significant advancements in the operational models of businesses. However, this shift also brings new security challenges by expanding the attack surface. The offered services in cloud computing have various service models. Each cloud service model has a defined responsibility divided based on the stack layers between the service user and their cloud provider. Regardless of its service model, each service is constructed from sub-components and services running on the underlying layers. In this paper, we aim to enable more transparency and visibility by designing an ontology that links the provider's services with the sub-components used to deliver the service. Such breakdown for each cloud service sub-components enables the end user to track the vulnerabilities on the service level or one of its sub-components. Such information can result in a better understanding and management of reported vulnerabilities on the sub-components level and their impact on the offered services by the cloud provider. Our ontology and source code are published as an open-source and accessible via GitHub: \href{https://github.com/mohkharma/cc-ontology}{mohkharma/cc-ontology}Comment: 8 page

Contribution to the elaboration of a decision support system based on modular ontologies for ecological labelling

With the rising concern of sustainability and environmental performance, eco-labeled products and services are becoming more and more popular. In addition to the financial costs, the long and complex process of eco-labeling sometimes demotivates manufacturers and service providers to be certificated. In this research work, we propose a decision support process and implement a decision support platform aiming at further improvement and acceleration of the eco-labeling process in order to democratize a broader application and certification of eco-labels. The decision support platform is based on a comprehensive knowledge base composed of various domain ontologies that are constructed according to official eco-label criteria documentation. Traditional knowledge base in relational data model is low interoperable, lack of inference support and difficult to be reused. In our research, the knowledge base composed of interconnected ontologies modules covers various products and services, and allows reasoning and semantic querying. A domain-centric modularization scheme about EU Eco-label laundry detergent product criteria is introduced as an application case. This modularization scheme separates the entity knowledge and rule knowledge so that the ontology modules can be reused easily in other domains. We explore a reasoning methodology based on inference with SWRL (Semantic Web Rule Language) rules which allows decision making with explanation. Through standard RDF (Resource Description Framework) and OWL (Web Ontology Language) ontology query interface, the assets of the decision support platform will stimulate domain knowledge sharing and can be applied into other application. In order to foster the reuse of ontology modules, we also proposed a usercentric approach for federate contextual ontologies (mapping and integration). This approach will create an ontology federation by a contextual configuration that avoid the “OWL:imports” disadvantages. Instead of putting mapping or new semantics in ontology modules, our approach will conserve the extra contextual information separately without impacting original ontologies or without importing all ontologies’ concepts. By introducing this contextualization, it becomes easier to support more expressive semantics in term of ontology integration itself, then it will also facilitate application agents to access and reuse ontologies. To realize this approach, we elaborate a new plug-in for the Protégé ontology editor

Coping with evolution in information systems: a database perspective

Business organisations today are faced with the complex problem of dealing with evolution in their software information systems. This effectively concerns the accommodation and facilitation of change, in terms of both changing user requirements and changing technological requirements. An approach that uses the software development life-cycle as a vehicle to study the problem of evolution is adopted. This involves the stages of requirements analysis, system specification, design, implementation, and finally operation and maintenance. The problem of evolution is one requiring proactive as well as reactive solutions for any given application domain. Measuring evolvability in conceptual models and the specification of changing requirements are considered. However, even "best designs" are limited in dealing with unanticipated evolution, and require implementation phase paradigms that can facilitate an evolution correctly (semantic integrity), efficiently (minimal disruption of services) and consistently (all affected parts are consistent following the change). These are also discussedComputingM. Sc. (Information Systems

Reverse Engineering Heterogeneous Applications

Nowadays a large majority of software systems are built using various technologies that in turn rely on different languages (e.g. Java, XML, SQL etc.). We call such systems heterogeneous applications (HAs). By contrast, we call software systems that are written in one language homogeneous applications. In HAs the information regarding the structure and the behaviour of the system is spread across various components and languages and the interactions between different application elements could be hidden. In this context applying existing reverse engineering and quality assurance techniques developed for homogeneous applications is not enough. These techniques have been created to measure quality or provide information about one aspect of the system and they cannot grasp the complexity of HAs. In this dissertation we present our approach to support the analysis and evolution of HAs based on: (1) a unified first-class description of HAs and, (2) a meta-model that reifies the concept of horizontal and vertical dependencies between application elements at different levels of abstraction. We implemented our approach in two tools, MooseEE and Carrack. The first is an extension of the Moose platform for software and data analysis and contains our unified meta-model for HAs. The latter is an engine to infer derived dependencies that can support the analysis of associations among the heterogeneous elements composing HA. We validate our approach and tools by case studies on industrial and open-source JEAs which demonstrate how we can handle the complexity of such applications and how we can solve problems deriving from their heterogeneous nature

gbeta - a Language with Virtual Attributes, Block Structure, and Propagating, Dynamic Inheritance

A language design development process is presented which leads to a language, gbeta, with a tight integration of virtual classes, general block structure, and a multiple inheritance mechanism based on coarse-grained structural type equivalence. From this emerges the concept of propagating specialization. The power lies in the fact that a simple expression can have far-reaching but well-organized consequences, e.g., in one step causing the combination of families of classes, then by propagation the members of those families, and finally by propagation the methods of the members. Moreover, classes are first class values which can be constructed at run-time, and it is possible to inherit from classes whether or not they are compile-time constants, and whether or not they were created dynamically. It is also possible to change the class and structure of an existing object at run-time, preserving object identity. Even though such dynamism is normally not seen in statically type-checked languages, these constructs have been integrated without compromising the static type safety of the language