Policy-Based Autonomic Data Governance

  • Seraphin Calo
  • Elisa Bertino
  • Dinesh Verma

Part of the Lecture Notes in Computer Science book series (LNCS, volume 11550)

Also part of the Information Systems and Applications, incl. Internet/Web, and HCI book sub series (LNISA, volume 11550)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Systems, Use-Cases and Foundational Principles Underlying Generative Policies

    1. Front Matter
      Pages 1-1
    2. Seraphin Calo, Irene Manotas, Geeth de Mel, Daniel Cunnington, Mark Law, Dinesh Verma et al.
      Pages 3-20
    3. Gavin Pearson, Dinesh Verma, Geeth de Mel
      Pages 21-41
    4. Dinesh Verma, Seraphin Calo, Shonda Witherspoon, Irene Manotas, Elisa Bertino, Amani M. Abu Jabal et al.
      Pages 42-65
  3. Approaches and Techniques for Safe Autonomy

    1. Front Matter
      Pages 67-67
    2. Hagit Grushka-Cohen, Ofer Biller, Oded Sofer, Lior Rokach, Bracha Shapira
      Pages 82-90
    3. Pierpaolo Bo, Alessandro Granato, Marco Ernesto Mancuso, Claudio Ciccotelli, Leonardo Querzoni
      Pages 91-112
    4. Asmaa Sallam, Elisa Bertino
      Pages 113-133
  4. Policies and Autonomy in Federated and Distributed Environments

    1. Front Matter
      Pages 135-135
    2. Kanthi Sarpatwar, Roman Vaculin, Hong Min, Gong Su, Terry Heath, Giridhar Ganapavarapu et al.
      Pages 137-153
    3. Changchang Liu, Supriyo Chakraborty, Dinesh Verma
      Pages 154-179
    4. Franck Le, Jorge Ortiz, Dinesh Verma, Dilip Kandlur
      Pages 180-201
    5. Antonino Rullo, Edoardo Serra, Jorge Lobo
      Pages 202-226
  5. Back Matter
    Pages 227-227

About this book


Advances in artificial intelligence, sensor computing, robotics, and mobile systems are making autonomous systems a reality. At the same time, the influence of edge computing is leading to more distributed architectures incorporating more autonomous elements. The flow of information is critical in such environments, but the real time, distributed nature of the system components complicates the data protection mechanisms. Policy-based management has proven useful in simplifying the complexity of management in domains like networking, security, and storage; it is expected that many of those benefits would carry over to the task of managing big data and autonomous systems.

This book aims at providing an overview of recent work and identifying challenges related to the design of policy-based approaches for managing big data and autonomous systems. An important new direction explored in the book is to make the major elements of the system self-describing and self-managing. This would lead to architectures where policy mechanisms are tightly coupled with the system elements. In such integrated architectures, we need new models for information assurance, traceability of information, and better provenance on information flows. In addition when dealing with devices with actuation capabilities and, thus, being able to make changes to physical spaces, safety is critical. With an emphasis on policy-based mechanisms for governance of data security and privacy, and for safety assurance, the papers in this volume follow three broad themes: foundational principles and use-cases for the autonomous generation of policies; safe autonomy; policies and autonomy in federated environments.


anomaly detection artificial intelligence complex systems computer crime computer networks data mining data security databases intrusion detection large scale systems semantics sensors telecommunication networks telecommunication traffic

Editors and affiliations

  1. 1.IBM ResearchYorktown HeightsUSA
  2. 2.Purdue UniversityWest LafayetteUSA
  3. 3.IBM ResearchYorktown HeightsUSA

Bibliographic information