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    Wireless Sensor Networks: Security, Coverage, and Localization
    Modern Data Strategy
    Cyber Defense and Situational Awareness
    Ebook series3 titles

    Advances in Information Security Series

    By Alexander Kott, Mike Fleckenstein, Kim-Kwang Raymond Choo and

    ()

    About this series

    The authors develop a malware fingerprinting framework to cover accurate android malware detection and family attribution in this book. The authors emphasize the following: (1) the scalability over a large malware corpus; (2) the resiliency to common obfuscation techniques; (3) the portability over different platforms and architectures.
    First, the authors propose an approximate fingerprinting technique for android packaging that captures the underlying static structure of the android applications in the context of bulk and offline detection at the app-market level. This book proposes a malware clustering framework to perform malware clustering by building and partitioning the similarity network of malicious applications on top of this fingerprinting technique. Second, the authors propose an approximate fingerprinting technique that leverages dynamic analysis and natural language processing techniques to generate Android malware behavior reports. Basedon this fingerprinting technique, the authors propose a portable malware detection framework employing machine learning classification. Third, the authors design an automatic framework to produce intelligence about the underlying malicious cyber-infrastructures of Android malware. The authors then leverage graph analysis techniques to generate relevant intelligence to identify the threat effects of malicious Internet activity associated with android malware.
    The authors elaborate on an effective android malware detection system, in the online detection context at the mobile device level.  It is suitable for deployment on mobile devices, using machine learning classification on method call sequences. Also, it is resilient to common code obfuscation techniques and adaptive to operating systems and malware change overtime, using natural language processing and deep learning techniques.
    Researchers working in mobile and network security, machine learning and pattern recognition will find this book useful as a reference. Advanced-level students studying computer science within these topic areas will purchase this book as well.
    LanguageEnglish
    PublisherSpringer
    Release dateJan 5, 2015
    Wireless Sensor Networks: Security, Coverage, and Localization
    Modern Data Strategy
    Cyber Defense and Situational Awareness

    Titles in the series (3)

    • 62

      Cyber Defense and Situational Awareness
      Cyber Defense and Situational Awareness

      Cyber Defense and Situational Awareness

      Alexander Kott
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      This book is the first publication to give a comprehensive, structured treatment to the important topic of situational awareness in cyber defense. It presents the subject in a logical, consistent, continuous discourse, covering key topics such as formation of cyber situational awareness, visualization and human factors, automated learning and inference, use of ontologies and metrics, predicting and assessing impact of cyber attacks, and achieving resilience of cyber and physical mission. Chapters include case studies, recent research results and practical insights described specifically for this book. Situational awareness is exceptionally prominent in the field of cyber defense. It involves science, technology and practice of perception, comprehension and projection of events and entities in cyber space. Chapters discuss the difficulties of achieving cyber situational awareness – along with approaches to overcoming the difficulties - in the relatively young field of cyber defense where key phenomena are so unlike the more conventional physical world. Cyber Defense and Situational Awareness is designed as a reference for practitioners of cyber security and developers of technology solutions for cyber defenders. Advanced-level students and researchers focused on security of computer networks will also find this book a valuable resource.

      This book is the first publication to give a comprehensive, structured treatment to the important topic of situational awareness in cyber defense. It presents the subject in a logical, consistent, continuous discourse, covering key topics such as formation of cyber situational awareness, visualization and human factors, automated learning and inference, use of ontologies and metrics, predicting and assessing impact of cyber attacks, and achieving resilience of cyber and physical mission. Chapters include case studies, recent research results and practical insights described specifically for this book. Situational awareness is exceptionally prominent in the field of cyber defense. It involves science, technology and practice of perception, comprehension and projection of events and entities in cyber space. Chapters discuss the difficulties of achieving cyber situational awareness – along with approaches to overcoming the difficulties - in the relatively young field of cyber defense where key phenomena are so unlike the more conventional physical world. Cyber Defense and Situational Awareness is designed as a reference for practitioners of cyber security and developers of technology solutions for cyber defenders. Advanced-level students and researchers focused on security of computer networks will also find this book a valuable resource.

    • 69

      Wireless Sensor Networks: Security, Coverage, and Localization
      Wireless Sensor Networks: Security, Coverage, and Localization

      Wireless Sensor Networks: Security, Coverage, and Localization

      Rastko R. Selmic
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      This book presents a comprehensive overview of wireless sensor networks (WSNs) with an emphasis on security, coverage, and localization. It offers a structural treatment of WSN building blocks including hardware and protocol architectures and also provides a systems-level view of how WSNs operate. These building blocks will allow readers to program specialized applications and conduct research in advanced topics. A brief introductory chapter covers common applications and communication protocols for WSNs. Next, the authors review basic mathematical models such as Voroni diagrams and Delaunay triangulations. Sensor principles, hardware structure, and medium access protocols are examined. Security challenges ranging from defense strategies to network robustness are explored, along with quality of service measures. Finally, this book discusses recent developments and future directions in WSN platforms. Each chapter concludes with classroom-tested exercises that reinforce key concepts. This book is suitable for researchers and for practitioners in industry. Advanced-level students in electrical engineering and computer science will also find the content helpful as a textbook or reference.

      This book presents a comprehensive overview of wireless sensor networks (WSNs) with an emphasis on security, coverage, and localization. It offers a structural treatment of WSN building blocks including hardware and protocol architectures and also provides a systems-level view of how WSNs operate. These building blocks will allow readers to program specialized applications and conduct research in advanced topics. A brief introductory chapter covers common applications and communication protocols for WSNs. Next, the authors review basic mathematical models such as Voroni diagrams and Delaunay triangulations. Sensor principles, hardware structure, and medium access protocols are examined. Security challenges ranging from defense strategies to network robustness are explored, along with quality of service measures. Finally, this book discusses recent developments and future directions in WSN platforms. Each chapter concludes with classroom-tested exercises that reinforce key concepts. This book is suitable for researchers and for practitioners in industry. Advanced-level students in electrical engineering and computer science will also find the content helpful as a textbook or reference.

    • 70

      Modern Data Strategy
      Modern Data Strategy

      Modern Data Strategy

      Mike Fleckenstein
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      This book contains practical steps business users can take to implement data management in a number of ways, including data governance, data architecture, master data management, business intelligence, and others. It defines data strategy, and covers chapters that illustrate how to align a data strategy with the business strategy, a discussion on valuing data as an asset, the evolution of data management, and who should oversee a data strategy. This provides the user with a good understanding of what a data strategy is and its limits. Critical to a data strategy is the incorporation of one or more data management domains. Chapters on key data management domains—data governance, data architecture, master data management and analytics, offer the user a practical approach to data management execution within a data strategy. The intent is to enable the user to identify how execution on one or more data management domains can help solve business issues. This book is intended for business users who work with data, who need to manage one or more aspects of the organization’s data, and who want to foster an integrated approach for how enterprise data is managed. This book is also an excellent reference for students studying computer science and business management or simply for someone who has been tasked with starting or improving existing data management.

      This book contains practical steps business users can take to implement data management in a number of ways, including data governance, data architecture, master data management, business intelligence, and others. It defines data strategy, and covers chapters that illustrate how to align a data strategy with the business strategy, a discussion on valuing data as an asset, the evolution of data management, and who should oversee a data strategy. This provides the user with a good understanding of what a data strategy is and its limits. Critical to a data strategy is the incorporation of one or more data management domains. Chapters on key data management domains—data governance, data architecture, master data management and analytics, offer the user a practical approach to data management execution within a data strategy. The intent is to enable the user to identify how execution on one or more data management domains can help solve business issues. This book is intended for business users who work with data, who need to manage one or more aspects of the organization’s data, and who want to foster an integrated approach for how enterprise data is managed. This book is also an excellent reference for students studying computer science and business management or simply for someone who has been tasked with starting or improving existing data management.

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