Models of Interaction as a Grounding for Peer to Peer Knowledge Sharing

Most current attempts to achieve reliable knowledge sharing on a large scale have relied on pre-engineering of content and supply services. This, like traditional knowledge engineering, does not by itself scale to large, open, peer to peer systems because the cost of being precise about the absolute semantics of services and their knowledge rises rapidly as more services participate. We describe how to break out of this deadlock by focusing on semantics related to interaction and using this to avoid dependency on a priori semantic agreement; instead making semantic commitments incrementally at run time. Our method is based on interaction models that are mobile in the sense that they may be transferred to other components, this being a mechanism for service composition and for coalition formation. By shifting the emphasis to interaction (the details of which may be hidden from users) we can obtain knowledge sharing of sufficient quality for sustainable communities of practice without the barrier of complex meta-data provision prior to community formation

Diagnosing runtime violations of security and dependability properties

Monitoring the preservation of security and dependability (S&D) properties of complex software systems is widely accepted as a necessity. Basic monitoring can detect violations but does not always provide sufficient information for deciding what the appropriate response to a violation is. Such decisions often require additional diagnostic information that explains why a violation has occurred and can, therefore, indicate what would be an appropriate response action to it. In this thesis, we describe a diagnostic procedure for generating explanations of violations of S&D properties developed as extension of a runtime monitoring framewoek, called EVEREST. The procedure is based on a combination of abductive and evidential reasoning about violations of S&D properties which are expressed in Event Calculus

Enabling Multi-Perspective Business Process Compliance

A particular challenge for any enterprise is to ensure that its business processes conform with compliance rules, i.e., semantic constraints on the multiple perspectives of the business processes. Compliance rules stem, for example, from legal regulations, corporate best practices, domain-specific guidelines, and industrial standards. In general, compliance rules are multi-perspective, i.e., they not only restrict the process behavior (i.e. control flow), but may refer to other process perspectives (e.g. time, data, and resources) and the interactions (i.e. message exchanges) of a business process with other processes as well. The aim of this thesis is to improve the specification and verification of multi-perspective process compliance based on three contributions: 1. The extended Compliance Rule Graph (eCRG) language, which enables the visual modeling of multi-perspective compliance rules. Besides control flow, the latter may refer to the time, data, resource, and interaction perspectives of a business process. 2. A framework for multi-perspective monitoring of the compliance of running processes with a given set of eCRG compliance rules. 3. Techniques for verifying business process compliance with respect to the interaction perspective. In particular, we consider compliance verification for cross-organizational business processes, for which solely incomplete process knowledge is available. All contributions were thoroughly evaluated through proof-of-concept prototypes, case studies, empirical studies, and systematic comparisons with related works

Survey of Human Models for Verification of Human-Machine Systems

We survey the landscape of human operator modeling ranging from the early cognitive models developed in artificial intelligence to more recent formal task models developed for model-checking of human machine interactions. We review human performance modeling and human factors studies in the context of aviation, and models of how the pilot interacts with automation in the cockpit. The purpose of the survey is to assess the applicability of available state-of-the-art models of the human operators for the design, verification and validation of future safety-critical aviation systems that exhibit higher-level of autonomy, but still require human operators in the loop. These systems include the single-pilot aircraft and NextGen air traffic management. We discuss the gaps in existing models and propose future research to address them

Intensional Cyberforensics

This work focuses on the application of intensional logic to cyberforensic analysis and its benefits and difficulties are compared with the finite-state-automata approach. This work extends the use of the intensional programming paradigm to the modeling and implementation of a cyberforensics investigation process with backtracing of event reconstruction, in which evidence is modeled by multidimensional hierarchical contexts, and proofs or disproofs of claims are undertaken in an eductive manner of evaluation. This approach is a practical, context-aware improvement over the finite state automata (FSA) approach we have seen in previous work. As a base implementation language model, we use in this approach a new dialect of the Lucid programming language, called Forensic Lucid, and we focus on defining hierarchical contexts based on intensional logic for the distributed evaluation of cyberforensic expressions. We also augment the work with credibility factors surrounding digital evidence and witness accounts, which have not been previously modeled. The Forensic Lucid programming language, used for this intensional cyberforensic analysis, formally presented through its syntax and operational semantics. In large part, the language is based on its predecessor and codecessor Lucid dialects, such as GIPL, Indexical Lucid, Lucx, Objective Lucid, and JOOIP bound by the underlying intensional programming paradigm.Comment: 412 pages, 94 figures, 18 tables, 19 algorithms and listings; PhD thesis; v2 corrects some typos and refs; also available on Spectrum at http://spectrum.library.concordia.ca/977460

Diagnosing runtime violations of security and dependability properties

Monitoring the preservation of security and dependability (S&D) properties of complex software systems is widely accepted as a necessity. Basic monitoring can detect violations but does not always provide sufficient information for deciding what the appropriate response to a violation is. Such decisions often require additional diagnostic information that explains why a violation has occurred and can, therefore, indicate what would be an appropriate response action to it. In this thesis, we describe a diagnostic procedure for generating explanations of violations of S&D properties developed as extension of a runtime monitoring framewoek, called EVEREST. The procedure is based on a combination of abductive and evidential reasoning about violations of S&D properties which are expressed in Event Calculus.EThOS - Electronic Theses Online ServiceGBUnited Kingdo