Digital provenance - models, systems, and applications

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

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 watermarking and novel security devices

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Data Hiding and Its Applications

Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content over the internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. The goal of this book is to focus on the improvement of data hiding algorithms and their different applications (both traditional and emerging), bringing together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others

The Road towards Predictable Automotive High-Performance Platforms

Due to the trends of centralizing the E/E architecture and new computing-intensive applications, high-performance hardware platforms are currently finding their way into automotive systems. However, the SoCs currently available on the market have significant weaknesses when it comes to providing predictable performance for time-critical applications. The main reason for this is that these platforms are optimized for averagecase performance. This shortcoming represents one major risk in the development of current and future automotive systems. In this paper we describe how high-performance and predictability could (and should) be reconciled in future HW/SW platforms. We believe that this goal can only be reached in a close collaboration between system suppliers, IP providers, semiconductor companies, and OS/hypervisor vendors. Furthermore, academic input will be needed to solve remaining challenges and to further improve initial solutions

Internet of Things data contextualisation for scalable information processing, security, and privacy

The Internet of Things (IoT) interconnects billions of sensors and other devices (i.e., things) via the internet, enabling novel services and products that are becoming increasingly important for industry, government, education and society in general. It is estimated that by 2025, the number of IoT devices will exceed 50 billion, which is seven times the estimated human population at that time. With such a tremendous increase in the number of IoT devices, the data they generate is also increasing exponentially and needs to be analysed and secured more efficiently. This gives rise to what is appearing to be the most significant challenge for the IoT: Novel, scalable solutions are required to analyse and secure the extraordinary amount of data generated by tens of billions of IoT devices. Currently, no solutions exist in the literature that provide scalable and secure IoT scale data processing. In this thesis, a novel scalable approach is proposed for processing and securing IoT scale data, which we refer to as contextualisation. The contextualisation solution aims to exclude irrelevant IoT data from processing and address data analysis and security considerations via the use of contextual information. More specifically, contextualisation can effectively reduce the volume, velocity and variety of data that needs to be processed and secured in IoT applications. This contextualisation-based data reduction can subsequently provide IoT applications with the scalability needed for IoT scale knowledge extraction and information security. IoT scale applications, such as smart parking or smart healthcare systems, can benefit from the proposed method, which  improves the scalability of data processing as well as the security and privacy of data.   The main contributions of this thesis are: 1) An introduction to context and contextualisation for IoT applications; 2) a contextualisation methodology for IoT-based applications that is modelled around observation, orientation, decision and action loops; 3) a collection of contextualisation techniques and a corresponding software platform for IoT data processing (referred to as contextualisation-as-a-service or ConTaaS) that enables highly scalable data analysis, security and privacy solutions; and 4) an evaluation of ConTaaS in several IoT applications to demonstrate that our contextualisation techniques permit data analysis, security and privacy solutions to remain linear, even in situations where the number of IoT data points increases exponentially

Steganography- A Powerful Web Security Tool for Data Transmission

The main objective of this paper titled � Steganography � A secured tool for web data transmission� is to provide security for data files during transmission in the network. The main motto of this type of data security is to prevent data access by unauthorized users during data transmission. The steganography is the process to convert the transmitting data in the network in an unreadable format and it is difficult to understand the stolen person