Integrating deep and shallow natural language processing components : representations and hybrid architectures

We describe basic concepts and software architectures for the integration of shallow and deep (linguistics-based, semantics-oriented) natural language processing (NLP) components. The main goal of this novel, hybrid integration paradigm is improving robustness of deep processing. After an introduction to constraint-based natural language parsing, we give an overview of typical shallow processing tasks. We introduce XML standoff markup as an additional abstraction layer that eases integration of NLP components, and propose the use of XSLT as a standardized and efficient transformation language for online NLP integration. In the main part of the thesis, we describe our contributions to three hybrid architecture frameworks that make use of these fundamentals. SProUT is a shallow system that uses elements of deep constraint-based processing, namely type hierarchy and typed feature structures. WHITEBOARD is the first hybrid architecture to integrate not only part-of-speech tagging, but also named entity recognition and topological parsing, with deep parsing. Finally, we present Heart of Gold, a middleware architecture that generalizes WHITEBOARD into various dimensions such as configurability, multilinguality and flexible processing strategies. We describe various applications that have been implemented using the hybrid frameworks such as structured named entity recognition, information extraction, creative document authoring support, deep question analysis, as well as evaluations. In WHITEBOARD, e.g., it could be shown that shallow pre-processing increases both coverage and efficiency of deep parsing by a factor of more than two. Heart of Gold not only forms the basis for applications that utilize semanticsoriented natural language analysis, but also constitutes a complex research instrument for experimenting with novel processing strategies combining deep and shallow methods, and eases replication and comparability of results.Diese Arbeit beschreibt Grundlagen und Software-Architekturen für die Integration von flachen mit tiefen (linguistikbasierten und semantikorientierten) Verarbeitungskomponenten für natürliche Sprache. Das Hauptziel dieses neuartigen, hybriden Integrationparadigmas ist die Verbesserung der Robustheit der tiefen Verarbeitung. Nach einer Einführung in constraintbasierte Analyse natürlicher Sprache geben wir einen Überblick über typische Aufgaben flacher Sprachverarbeitungskomponenten. Wir führen XML Standoff-Markup als zusätzliche Abstraktionsebene ein, mit deren Hilfe sich Sprachverarbeitungskomponenten einfacher integrieren lassen. Ferner schlagen wir XSLT als standardisierte und effiziente Transformationssprache für die Online-Integration vor. Im Hauptteil der Arbeit stellen wir unsere Beiträge zu drei hybriden Architekturen vor, welche auf den beschriebenen Grundlagen aufbauen. SProUT ist ein flaches System, das Elemente tiefer Verarbeitung wie Typhierarchie und getypte Merkmalsstrukturen nutzt. WHITEBOARD ist das erste System, welches nicht nur Part-of-speech-Tagging, sondern auch Eigennamenerkennung und flaches topologisches Parsing mit tiefer Verarbeitung kombiniert. Schließlich wird Heart of Gold vorgestellt, eine Middleware-Architektur, welche WHITEBOARD hinsichtlich verschiedener Dimensionen wie Konfigurierbarkeit, Mehrsprachigkeit und Unterstützung flexibler Verarbeitungsstrategien generalisiert. Wir beschreiben verschiedene, mit Hilfe der hybriden Architekturen implementierte Anwendungen wie strukturierte Eigennamenerkennung, Informationsextraktion, Kreativitätsunterstützung bei der Dokumenterstellung, tiefe Frageanalyse, sowie Evaluationen. So konnte z.B. in WHITEBOARD gezeigt werden, dass durch flache Vorverarbeitung sowohl Abdeckung als auch Effizienz des tiefen Parsers mehr als verdoppelt werden. Heart of Gold bildet nicht nur Grundlage für semantikorientierte Sprachanwendungen, sondern stellt auch eine wissenschaftliche Experimentierplattform für weitere, neuartige Kombinationsstrategien dar, welche zudem die Replizierbarkeit und Vergleichbarkeit von Ergebnissen erleichtert

Architecture-centric support for security orchestration and automation

Security Orchestration, Automation and Response (SOAR) platforms leverage integration and orchestration technologies to (i) automate manual and repetitive labor-intensive tasks, (ii) provide a single panel of control to manage various types of security tools (e.g., intrusion detection system, antivirus and firewall) and (iii) streamline complex Incident Response Process (IRP) responses. SOAR platforms increase the operational efficiency of overwhelmed security teams in a Security Operation Centre (SOC) and accelerate the SOC’s defense and response capacity against ever-growing security incidents. Security tools, IRPs and security requirements form the underlying execution environment of SOAR platforms, which are changing rapidly due to the dynamic nature of security threats. A SOAR platform is expected to adapt continuously to these dynamic changes. Flexible integration, interpretation and interoperability of security tools are essential to ease the adaptation of a SOAR platform. However, most of the effort for designing and developing existing SOAR platforms are ad-hoc in nature, which introduces several engineering challenges and research challenges. For instance, the advancement of a SOAR platform increases its architectural complexity and makes the operation of such platforms difficult for end-users. These challenges come from a lack of a comprehensive view, design space and architectural support for SOAR platforms. This thesis aims to contribute to the growing realization that it is necessary to advance SOAR platforms by designing, implementing and evaluating architecture-centric support to address several of the existing challenges. The envisioned research and development activities require the identification of current practices and challenges of SOAR platforms; hence, a Multivocal Literature Review (MLR) has been designed, conducted and reported. The MLR identifies the functional and non-functional requirements, components and practices of a security orchestration domain, along with the open issues. This thesis advances the domain of a SOAR platform by providing a layered architecture, which considers the key functional and non-functional requirements of a SOAR platform. The proposed architecture is evaluated experimentally with a Proof of Concept (PoC) system, Security Tool Unifier (STUn), using seven security tools, a set of IRPs and playbooks. The research further identifies the need for and design of (i) an Artificial Intelligence (AI) based integration framework to interpret the activities of security tools and enable interoperability automatically, (ii) a semantic-based automated integration process to integrate security tools and (iii) AI-enabled design and generation of a declarative API from user query, namely DecOr, to hide the internal complexity of a SOAR platform from end-users. The experimental evaluation of the proposed approaches demonstrates that (i) consideration of architectural design decisions supports the development of an easy to interact with, modify and update SOAR platform, (ii) an AI-based integration framework and automated integration process provides effective and efficient integration and interpretation of security tools and IRPs and (iii) DecOr increases the usability and flexibility of a SOAR platform. This thesis is a useful resource and guideline for both practitioners and researchers who are working in the security orchestration domain. It provides an insight into how an architecture-centric approach, with incorporation of AI technologies, reduces the operational complexity of SOAR platforms.Thesis (Ph.D.) -- University of Adelaide, School of Computer Science, 202

Proceedings of Monterey Workshop 2001 Engineering Automation for Sofware Intensive System Integration

The 2001 Monterey Workshop on Engineering Automation for Software Intensive System Integration was sponsored by the Office of Naval Research, Air Force Office of Scientific Research, Army Research Office and the Defense Advance Research Projects Agency. It is our pleasure to thank the workshop advisory and sponsors for their vision of a principled engineering solution for software and for their many-year tireless effort in supporting a series of workshops to bring everyone together.This workshop is the 8 in a series of International workshops. The workshop was held in Monterey Beach Hotel, Monterey, California during June 18-22, 2001. The general theme of the workshop has been to present and discuss research works that aims at increasing the practical impact of formal methods for software and systems engineering. The particular focus of this workshop was "Engineering Automation for Software Intensive System Integration". Previous workshops have been focused on issues including, "Real-time & Concurrent Systems", "Software Merging and Slicing", "Software Evolution", "Software Architecture", "Requirements Targeting Software" and "Modeling Software System Structures in a fastly moving scenario".Office of Naval ResearchAir Force Office of Scientific Research Army Research OfficeDefense Advanced Research Projects AgencyApproved for public release, distribution unlimite