Constraint rule-based programming of norms for electronic institutions

Peer reviewedPostprin

On the Security of Software Systems and Services

This work investigates new methods for facing the security issues and threats arising from the composition of software. This task has been carried out through the formal modelling of both the software composition scenarios and the security properties, i.e., policies, to be guaranteed. Our research moves across three different modalities of software composition which are of main interest for some of the most sensitive aspects of the modern information society. They are mobile applications, trust-based composition and service orchestration. Mobile applications are programs designed for being deployable on remote platforms. Basically, they are the main channel for the distribution and commercialisation of software for mobile devices, e.g., smart phones and tablets. Here we study the security threats that affect the application providers and the hosting platforms. In particular, we present a programming framework for the development of applications with a static and dynamic security support. Also, we implemented an enforcement mechanism for applying fine-grained security controls on the execution of possibly malicious applications. In addition to security, trust represents a pragmatic and intuitive way for managing the interactions among systems. Currently, trust is one of the main factors that human beings keep into account when deciding whether to accept a transaction or not. In our work we investigate the possibility of defining a fully integrated environment for security policies and trust including a runtime monitor. Finally, Service-Oriented Computing (SOC) is the leading technology for business applications distributed over a network. The security issues related to the service networks are many and multi-faceted. We mainly deal with the static verification of secure composition plans of web services. Moreover, we introduce the synthesis of dynamic security checks for protecting the services against illegal invocations

CBR and MBR techniques: review for an application in the emergencies domain

The purpose of this document is to provide an in-depth analysis of current reasoning engine practice and the integration strategies of Case Based Reasoning and Model Based Reasoning that will be used in the design and development of the RIMSAT system. RIMSAT (Remote Intelligent Management Support and Training) is a European Commission funded project designed to: a.. Provide an innovative, 'intelligent', knowledge based solution aimed at improving the quality of critical decisions b.. Enhance the competencies and responsiveness of individuals and organisations involved in highly complex, safety critical incidents - irrespective of their location. In other words, RIMSAT aims to design and implement a decision support system that using Case Base Reasoning as well as Model Base Reasoning technology is applied in the management of emergency situations. This document is part of a deliverable for RIMSAT project, and although it has been done in close contact with the requirements of the project, it provides an overview wide enough for providing a state of the art in integration strategies between CBR and MBR technologies.Postprint (published version

VALIDATING REQUIREMENTS SPECIFICATIONS STATED IN KNOWLEDGE REPRESENTATION LANGUAGE TEMPLAR

Techniques for analysis and validation of software requirements specifications written in the knowledge representation language Templar are presented. Templar specifications are analyzed in terms of ambiguity, non-minimality, contradiction, incompleteness, and redundancy. Since Templar is a powerful knowledge representation language supporting a rich set of modeling primitives, it is difficult to reason directly on Templar specifications. To solve this problem, Templar specifications are mapped into equivalent temporal logic programs which are analyzed in terms the criteria listed above. However, it is hard to reason about Templar specifications because some of the criteria cannot be formally proven, and the verification of other criteria constitute undecidable or intractable problems. To overcome these difficulties, we consider a set of tractable conditions for each criteria, which serve as "alarms" for the user. If a condition is violated then it means that the specification either definitely has or potentially can have a problem. Furthermore, the user is notified about the source and the nature of the problem in certain cases.Information Systems Working Papers Serie

Legal linked data ecosystems and the rule of law

This chapter introduces the notions of meta-rule of law and socio-legal ecosystems to both foster and regulate linked democracy. It explores the way of stimulating innovative regulations and building a regulatory quadrant for the rule of law. The chapter summarises briefly (i) the notions of responsive, better and smart regulation; (ii) requirements for legal interchange languages (legal interoperability); (iii) and cognitive ecology approaches. It shows how the protections of the substantive rule of law can be embedded into the semantic languages of the web of data and reflects on the conditions that make possible their enactment and implementation as a socio-legal ecosystem. The chapter suggests in the end a reusable multi-levelled meta-model and four notions of legal validity: positive, composite, formal, and ecological

Personalizable Knowledge Integration

Large repositories of data are used daily as knowledge bases (KBs) feeding computer systems that support decision making processes, such as in medical or financial applications. Unfortunately, the larger a KB is, the harder it is to ensure its consistency and completeness. The problem of handling KBs of this kind has been studied in the AI and databases communities, but most approaches focus on computing answers locally to the KB, assuming there is some single, epistemically correct solution. It is important to recognize that for some applications, as part of the decision making process, users consider far more knowledge than that which is contained in the knowledge base, and that sometimes inconsistent data may help in directing reasoning; for instance, inconsistency in taxpayer records can serve as evidence of a possible fraud. Thus, the handling of this type of data needs to be context-sensitive, creating a synergy with the user in order to build useful, flexible data management systems. Inconsistent and incomplete information is ubiquitous and presents a substantial problem when trying to reason about the data: how can we derive an adequate model of the world, from the point of view of a given user, from a KB that may be inconsistent or incomplete? In this thesis we argue that in many cases users need to bring their application-specific knowledge to bear in order to inform the data management process. Therefore, we provide different approaches to handle, in a personalized fashion, some of the most common issues that arise in knowledge management. Specifically, we focus on (1) inconsistency management in relational databases, general knowledge bases, and a special kind of knowledge base designed for news reports; (2) management of incomplete information in the form of different types of null values; and (3) answering queries in the presence of uncertain schema matchings. We allow users to define policies to manage both inconsistent and incomplete information in their application in a way that takes both the user's knowledge of his problem, and his attitude to error/risk, into account. Using the frameworks and tools proposed here, users can specify when and how they want to manage/solve the issues that arise due to inconsistency and incompleteness in their data, in the way that best suits their needs