6 research outputs found

    Digital provenance - models, systems, and applications

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    Data provenance refers to the history of creation and manipulation of a data object and is being widely used in various application domains including scientific experiments, grid computing, file and storage system, streaming data etc. However, existing provenance systems operate at a single layer of abstraction (workflow/process/OS) at which they record and store provenance whereas the provenance captured from different layers provide the highest benefit when integrated through a unified provenance framework. To build such a framework, a comprehensive provenance model able to represent the provenance of data objects with various semantics and granularity is the first step. In this thesis, we propose a such a comprehensive provenance model and present an abstract schema of the model. ^ We further explore the secure provenance solutions for distributed systems, namely streaming data, wireless sensor networks (WSNs) and virtualized environments. We design a customizable file provenance system with an application to the provenance infrastructure for virtualized environments. The system supports automatic collection and management of file provenance metadata, characterized by our provenance model. Based on the proposed provenance framework, we devise a mechanism for detecting data exfiltration attack in a file system. We then move to the direction of secure provenance communication in streaming environment and propose two secure provenance schemes focusing on WSNs. The basic provenance scheme is extended in order to detect packet dropping adversaries on the data flow path over a period of time. We also consider the issue of attack recovery and present an extensive incident response and prevention system specifically designed for WSNs

    Digital provenance - models, systems, and applications

    Get PDF
    Data provenance refers to the history of creation and manipulation of a data object and is being widely used in various application domains including scientific experiments, grid computing, file and storage system, streaming data etc. However, existing provenance systems operate at a single layer of abstraction (workflow/process/OS) at which they record and store provenance whereas the provenance captured from different layers provide the highest benefit when integrated through a unified provenance framework. To build such a framework, a comprehensive provenance model able to represent the provenance of data objects with various semantics and granularity is the first step. In this thesis, we propose a such a comprehensive provenance model and present an abstract schema of the model. ^ We further explore the secure provenance solutions for distributed systems, namely streaming data, wireless sensor networks (WSNs) and virtualized environments. We design a customizable file provenance system with an application to the provenance infrastructure for virtualized environments. The system supports automatic collection and management of file provenance metadata, characterized by our provenance model. Based on the proposed provenance framework, we devise a mechanism for detecting data exfiltration attack in a file system. We then move to the direction of secure provenance communication in streaming environment and propose two secure provenance schemes focusing on WSNs. The basic provenance scheme is extended in order to detect packet dropping adversaries on the data flow path over a period of time. We also consider the issue of attack recovery and present an extensive incident response and prevention system specifically designed for WSNs

    Context-Aware Privacy Protection Framework for Wireless Sensor Networks

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    Smart Wireless Sensor Networks

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    The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks

    Qualitative and Quantitative Security Analyses for ZigBee Wireless Sensor Networks

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