A dynamic three-dimensional network visualization program for integration into cyberciege and other network visualization scenarios

Detailed information and intellectual understanding of a network's topology and vulnerabilities is invaluable to better securing computer networks. Network protocol analyzers and intrusion detection systems can provide this additional information. In particular, game-based trainers, such as CyberCIEGE, have been shown to improve the level of training and understanding of network security professionals. This thesis' objective is to enhance these applications by developing NTAV3D, or, Network Topology and Attack Visualizer (Three Dimensional). NTAV3D is a tool that displays network topology, vulnerabilities, and attacks in an interactive, three dimensional environment. This augments the design and gameplay of CyberCIEGE by increasing gameplayer interaction and data display. Additionally, NTAV3D can be expanded to provide this capability to network analysis and intrusion detection tools. Furthermore, NTAV3D expands on ideas and results from related work of the best ways to visualize network topology, vulnerabilities, and attacks. NTAV3D was created using open-source software technologies including Xj3D, X3D, Java, and XML. It is also one of the first applications to be built with only the Xj3D toolkit. Therefore, the development process allowed evaluation of these technologies, resulting in recommendations for future improvements.http://archive.org/details/adynamicthreedim109453384US Navy (USN) authors.Approved for public release; distribution is unlimited

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

Integrated modeling and analysis methodologies for architecture-level vehicle design.

In order to satisfy customer expectations, a ground vehicle must be designed to meet a broad range of performance requirements. A satisfactory vehicle design process implements a set of requirements reflecting necessary, but perhaps not sufficient conditions for assuring success in a highly competitive market. An optimal architecture-level vehicle design configuration is one of the most important of these requirements. A basic layout that is efficient and flexible permits significant reductions in the time needed to complete the product development cycle, with commensurate reductions in cost. Unfortunately, architecture-level design is the most abstract phase of the design process. The high-level concepts that characterize these designs do not lend themselves to traditional analyses normally used to characterize, assess, and optimize designs later in the development cycle. This research addresses the need for architecture-level design abstractions that can be used to support ground vehicle development. The work begins with a rigorous description of hierarchical function-based abstractions representing not the physical configuration of the elements of a vehicle, but their function within the design space. The hierarchical nature of the abstractions lends itself to object orientation - convenient for software implementation purposes - as well as description of components, assemblies, feature groupings based on non-structural interactions, and eventually, full vehicles. Unlike the traditional early-design abstractions, the completeness of our function-based hierarchical abstractions, including their interactions, allows their use as a starting point for the derivation of analysis models. The scope of the research in this dissertation includes development of meshing algorithms for abstract structural models, a rigid-body analysis engine, and a fatigue analysis module. It is expected that the results obtained in this study will move systematic design and analysis to the earliest phases of the vehicle development process, leading to more highly optimized architectures, and eventually, better ground vehicles. This work shows that architecture level abstractions in many cases are better suited for life cycle support than geometric CAD models. Finally, substituting modeling, simulation, and optimization for intuition and guesswork will do much to mitigate the risk inherent in large projects by minimizing the possibility of incorporating irrevocably compromised architecture elements into a vehicle design that no amount of detail-level reengineering can undo

Effizientes Maschinelles Lernen für die Angriffserkennung

Detecting and fending off attacks on computer systems is an enduring problem in computer security. In light of a plethora of different threats and the growing automation used by attackers, we are in urgent need of more advanced methods for attack detection. In this thesis, we address the necessity of advanced attack detection and develop methods to detect attacks using machine learning to establish a higher degree of automation for reactive security. Machine learning is data-driven and not void of bias. For the effective application of machine learning for attack detection, thus, a periodic retraining over time is crucial. However, the training complexity of many learning-based approaches is substantial. We show that with the right data representation, efficient algorithms for mining substring statistics, and implementations based on probabilistic data structures, training the underlying model can be achieved in linear time. In two different scenarios, we demonstrate the effectiveness of so-called language models that allow to generically portray the content and structure of attacks: On the one hand, we are learning malicious behavior of Flash-based malware using classification, and on the other hand, we detect intrusions by learning normality in industrial control networks using anomaly detection. With a data throughput of up to 580 Mbit/s during training, we do not only meet our expectations with respect to runtime but also outperform related approaches by up to an order of magnitude in detection performance. The same techniques that facilitate learning in the previous scenarios can also be used for revealing malicious content, embedded in passive file formats, such as Microsoft Office documents. As a further showcase, we additionally develop a method based on the efficient mining of substring statistics that is able to break obfuscations irrespective of the used key length, with up to 25 Mbit/s and thus, succeeds where related approaches fail. These methods significantly improve detection performance and enable operation in linear time. In doing so, we counteract the trend of compensating increasing runtime requirements with resources. While the results are promising and the approaches provide urgently needed automation, they cannot and are not intended to replace human experts or traditional approaches, but are designed to assist and complement them.Die Erkennung und Abwehr von Angriffen auf Endnutzer und Netzwerke ist seit vielen Jahren ein anhaltendes Problem in der Computersicherheit. Angesichts der hohen Anzahl an unterschiedlichen Angriffsvektoren und der zunehmenden Automatisierung von Angriffen, bedarf es dringend moderner Methoden zur Angriffserkennung. In dieser Doktorarbeit werden Ansätze entwickelt, um Angriffe mit Hilfe von Methoden des maschinellen Lernens zuverlässig, aber auch effizient zu erkennen. Sie stellen der Automatisierung von Angriffen einen entsprechend hohen Grad an Automatisierung von Verteidigungsmaßnahmen entgegen. Das Trainieren solcher Methoden ist allerdings rechnerisch aufwändig und erfolgt auf sehr großen Datenmengen. Laufzeiteffiziente Lernverfahren sind also entscheidend. Wir zeigen, dass durch den Einsatz von effizienten Algorithmen zur statistischen Analyse von Zeichenketten und Implementierung auf Basis von probabilistischen Datenstrukturen, das Lernen von effektiver Angriffserkennung auch in linearer Zeit möglich ist. Anhand von zwei unterschiedlichen Anwendungsfällen, demonstrieren wir die Effektivität von Modellen, die auf der Extraktion von sogenannten n-Grammen basieren: Zum einen, betrachten wir die Erkennung von Flash-basiertem Schadcode mittels Methoden der Klassifikation, und zum anderen, die Erkennung von Angriffen auf Industrienetzwerke bzw. SCADA-Systeme mit Hilfe von Anomaliedetektion. Dabei erzielen wir während des Trainings dieser Modelle einen Datendurchsatz von bis zu 580 Mbit/s und übertreffen gleichzeitig die Erkennungsleistung von anderen Ansätzen deutlich. Die selben Techniken, um diese lernenden Ansätze zu ermöglichen, können außerdem für die Erkennung von Schadcode verwendet werden, der in anderen Dateiformaten eingebettet und mittels einfacher Verschlüsselungen obfuskiert wurde. Hierzu entwickeln wir eine Methode die basierend auf der statistischen Auswertung von Zeichenketten einfache Verschlüsselungen bricht. Der entwickelte Ansatz arbeitet unabhängig von der verwendeten Schlüssellänge, mit einem Datendurchsatz von bis zu 25 Mbit/s und ermöglicht so die erfolgreiche Deobfuskierung in Fällen an denen andere Ansätze scheitern. Die erzielten Ergebnisse in Hinsicht auf Laufzeiteffizienz und Erkennungsleistung sind vielversprechend. Die vorgestellten Methoden ermöglichen die dringend nötige Automatisierung von Verteidigungsmaßnahmen, sollen den Experten oder etablierte Methoden aber nicht ersetzen, sondern diese unterstützen und ergänzen

Developing a distributed electronic health-record store for India

The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India

A Framework for Dynamic Terrain with Application in Off-road Ground Vehicle Simulations

The dissertation develops a framework for the visualization of dynamic terrains for use in interactive real-time 3D systems. Terrain visualization techniques may be classified as either static or dynamic. Static terrain solutions simulate rigid surface types exclusively; whereas dynamic solutions can also represent non-rigid surfaces. Systems that employ a static terrain approach lack realism due to their rigid nature. Disregarding the accurate representation of terrain surface interaction is rationalized because of the inherent difficulties associated with providing runtime dynamism. Nonetheless, dynamic terrain systems are a more correct solution because they allow the terrain database to be modified at run-time for the purpose of deforming the surface. Many established techniques in terrain visualization rely on invalid assumptions and weak computational models that hinder the use of dynamic terrain. Moreover, many existing techniques do not exploit the capabilities offered by current computer hardware. In this research, we present a component framework for terrain visualization that is useful in research, entertainment, and simulation systems. In addition, we present a novel method for deforming the terrain that can be used in real-time, interactive systems. The development of a component framework unifies disparate works under a single architecture. The high-level nature of the framework makes it flexible and adaptable for developing a variety of systems, independent of the static or dynamic nature of the solution. Currently, there are only a handful of documented deformation techniques and, in particular, none make explicit use of graphics hardware. The approach developed by this research offloads extra work to the graphics processing unit; in an effort to alleviate the overhead associated with deforming the terrain. Off-road ground vehicle simulation is used as an application domain to demonstrate the practical nature of the framework and the deformation technique. In order to realistically simulate terrain surface interactivity with the vehicle, the solution balances visual fidelity and speed. Accurately depicting terrain surface interactivity in off-road ground vehicle simulations improves visual realism; thereby, increasing the significance and worth of the application. Systems in academia, government, and commercial institutes can make use of the research findings to achieve the real-time display of interactive terrain surfaces

Fourth Conference on Artificial Intelligence for Space Applications

Proceedings of a conference held in Huntsville, Alabama, on November 15-16, 1988. The Fourth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: space applications of expert systems in fault diagnostics, in telemetry monitoring and data collection, in design and systems integration; and in planning and scheduling; knowledge representation, capture, verification, and management; robotics and vision; adaptive learning; and automatic programming

3D-based Advanced Machine Service Support

In the face of today's unpredictable and fluctuating global market, there have been trends in industry towards wider adoption of more advanced and flexible new generation manufacturing systems. These have brought about new challenges to manufacturing equipment builders/suppliers in respect of satisfying ever-increasing customers' requirements for such advanced manufacturing systems. To stay competitive, in addition to supplying high quality equipment, machine builders/suppliers must also be capable of providing their customers with cost-effective, efficient and comprehensive service support, throughout the equipment's lifecycle. This research study has been motivated by the relatively unexplored potential of integrating 3D virtual technology with various machine service support tools/techniques to address the aforementioned challenges. The hypothesis formulated for this study is that a 3D-based virtual environment can be used as an integration platform to improve service support for new generation manufacturing systems. In order to ensure the rigour of the study, it has been initiated with a two-stage (iterative) literature review, consisting of: a preliminary review for the identification of practical problems/main issues related to the area of machine service support and in-depth reviews for the identification of research problems/questions and potential solutions. These were then followed by iterations of intensive research activities, consisting of: requirements identification, concept development, prototype implementation, testing and exploration, reflection and feedback. The process has been repeated and revised continuously until satisfactory results, required for answering the identified research problems/questions, were obtained. The main focus of this study is exploring how a 3D-based virtual environment can be used as an integration platform for supporting a more cost-effective and comprehensive strategy for improving service support for new generation manufacturing systems. One of the main outcomes of this study is the proposal of a conceptual framework for a novel 3D-based advanced machine service support strategy and a reference architecture for a corresponding service support system, for allowing machine builders/suppliers to: (1) provide more cost-effective remote machine maintenance support, and (2) provide more efficient and comprehensive extended service support during the equipment's life cycle. The proposed service support strategy advocates the tight integration of conventional (consisting of mainly machine monitoring, diagnostics, prognostics and maintenance action decision support) and extended (consisting of mainly machine re-configuration, upgrade and expansion support) service support functions. The proposed service support system is based on the integration of a 3D-based virtual environment with the equipment control system, a re-configurable automated service support system, coupled with a maintenance-support-tool/strategy support environment and an equipment re-configuration/upgrade/expansion support environment, in a network/lntenet framework. The basic concepts, potential benefits and limitations of the proposed strategy/ system have been explored via a prototype based on a laboratory-scale test bed. The prototype consists of a set of integrated modular network-ready software tools consisting of: (1) an integrated 20/30 visualisation and analysis module, (2) support tools library modules, (3) communication modules and (4) a set of modular and re-configurable automated data logging, maintenance and re-configuration support modules. A number of test cases based on various machine service support scenarios, have been conducted using the prototype. The experimentation has shown the potential and feasibility (technical implementation aspects) of the proposed 3D-based approach. This research study has made an original contribution to knowledge in the field of machine service support. It has contributed a novel approach of using a 3D-based virtual environment as an integration platform for improving the capability of machine builders/suppliers in providing more cost-effective and comprehensive machine service support for complex new generation manufacturing systems. Several important findings have resulted from this work in particular with respect to how various 20/30 visualisation environments are integrated with machine service support tools/techniques for improving service support for complex manufacturing systems. A number of aspects have also been identified for future work

Security in Distributed, Grid, Mobile, and Pervasive Computing

This book addresses the increasing demand to guarantee privacy, integrity, and availability of resources in networks and distributed systems. It first reviews security issues and challenges in content distribution networks, describes key agreement protocols based on the Diffie-Hellman key exchange and key management protocols for complex distributed systems like the Internet, and discusses securing design patterns for distributed systems. The next section focuses on security in mobile computing and wireless networks. After a section on grid computing security, the book presents an overview of security solutions for pervasive healthcare systems and surveys wireless sensor network security

Guide Me in Analysis: A Framework for Guidance Designers

Guidance is an emerging topic in the field of visual analytics. Guidance can support users in pursuing their analytical goals more efficiently and help in making the analysis successful. However, it is not clear how guidance approaches should be designed and what specific factors should be considered for effective support. In this paper, we approach this problem from the perspective of guidance designers. We present a framework comprising requirements and a set of specific phases designers should go through when designing guidance for visual analytics. We relate this process with a set of quality criteria we aim to support with our framework, that are necessary for obtaining a suitable and effective guidance solution. To demonstrate the practical usability of our methodology, we apply our framework to the design of guidance in three analysis scenarios and a design walk-through session. Moreover, we list the emerging challenges and report how the framework can be used to design guidance solutions that mitigate these issues