Policy-based autonomic data governance / Seraphin Calo, Elisa Bertino, Dinesh Verma (eds.)

Includes bibliographical references and index

Part I: Systems, use-cases and foundational principles underlying generative policies: 1. AGENP : an ASGrammar-based GENerative policy framework / Seraphin Calo, Irene Manotas, Geeth de Mel, Daniel Cunnington, Mark Law, Dinesh Verma, Alessandra Russo, and Elisa Bertino -- 2. Value of information : quantification and application to coalition machine learning / Gavin Pearson, Dinesh Verma, and Geeth de Mel -- 3. Self-generating policies for machine learning in coalition environments / Dinesh Verma, Seraphin Calo, Shonda Witherspoon, Irene Manotas, Elisa Bertino, Amani M. Abu Jabal, Greg Cirincione, Ananthram Swami, Gavin Pearson, and Geeth de Mel

Part II: Approaches and techniques for safe autonomy: 4. Can N-version decision-making prevent the rebirth of HAL 9000 in military camo? Using a "golden rule" threshold to prevent AI mission individuation / Sorin Adam Matei and Elisa Bertino -- 5. Simulating user activity for assessing effect of sampling on DB activity monitoring anomaly detection / Hagit Grushka-Cohen, Ofer Biller, Oded Sofer, Lior Rokach, and Bracha Shapira -- 6. FADa-CPS : faults and attacks discrimination in cyber physical systems / Pierpaolo Bo, Alessandro Granato, Marco Ernesto Mancuso, Claudio Ciccotelli, and Leonardo Querzoni -- 7. Techniques and systems for anomaly detection in database systems / Asmaa Sallam and Elisa Bertino

Part III: Policies and autonomy in federated and distributed environments: 8. Towards enabling trusted artificial intelligence via blockchain / Kanthi Sarpatwar, Roman Vaculin, Hong Min, Gong Su, Terry Heath, Giridhar Ganapavarapu, and Donna Dillenberger -- 9. Secure model fusion for distributed learning using partial homomorphic encryption / Changchang Liu, Supriyo Chakraborty, and Dinesh Verma -- 10. Policy-based identification of IoT devices' vendor and type by DNS traffic analysis / Franck Le, Jorge Ortiz, Dinesh Verma, and Dilip Kandlur -- 11. Redundancy as a measure of fault-tolerance for the Internet of Things : a review / Antonino Rullo, Edoardo Serra, and Jorge Lobo

Available to OhioLINK libraries

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