Network Science and Cybersecurity

  • Robinson E. Pino

Part of the Advances in Information Security book series (ADIS, volume 55)

Table of contents

  1. Front Matter
    Pages i-x
  2. Massimiliano Albanese, Robert F. Erbacher, Sushil Jajodia, C. Molinaro, Fabio Persia, Antonio Picariello et al.
    Pages 39-62
  3. Bruce McCormick
    Pages 63-73
  4. Yan M. Yufik
    Pages 75-91
  5. Dhireesha Kudithipudi, Cory Merkel, Mike Soltiz, Garrett S. Rose, Robinson E. Pino
    Pages 93-103
  6. Garrett S. Rose, Dhireesha Kudithipudi, Ganesh Khedkar, Nathan McDonald, Bryant Wysocki, Lok-Kwong Yan
    Pages 105-123
  7. Kent W. Nixon, Yiran Chen, Zhi-Hong Mao, Kang Li
    Pages 125-135
  8. Bryant Wysocki, Nathan McDonald, Clare Thiem, Garrett Rose, Mario Gomez II
    Pages 137-153
  9. Misty Blowers, Jonathan Williams
    Pages 155-175
  10. Xueyang Wang, Ramesh Karri
    Pages 177-187
  11. Hasan Cam, Pierre A. Mouallem, Robinson E. Pino
    Pages 205-220
  12. Steve Hutchinson
    Pages 221-237
  13. Tanvir Atahary, Scott Douglass, Tarek M. Taha
    Pages 251-271
  14. Michael J. Shevenell, Justin L. Shumaker, Arthur H. Edwards, Robinson E. Pino
    Pages 273-285

About this book

Introduction

Network Science and Cybersecurity introduces new research and development efforts for cybersecurity solutions and applications taking place within various U.S. Government Departments of  Defense, industry and academic laboratories.

This book examines new algorithms and tools, technology platforms and reconfigurable technologies for cybersecurity systems. Anomaly-based intrusion detection systems (IDS) are explored as a key component of any general network intrusion detection service, complementing signature-based IDS components by attempting to identify novel attacks.  These attacks  may not yet be known or have well-developed signatures.  Methods are also suggested to simplify the construction of metrics in such a manner that they retain their ability to effectively cluster data, while simultaneously easing human interpretation of outliers.

This is a professional book for practitioners or government employees working in cybersecurity, and can also be used as a reference.  Advanced-level students in computer science or electrical engineering studying security will also find this book useful . 

Keywords

Alert Aggregation Anomaly Detection Big Data Cyber Intelligence Cybersecurity Hardware Security Human Factors Internet of Things Intrusion Detection and Prevention Machine Learning Mobile Security Network Science Neuromorphic Computing Rootkit Detection

Editors and affiliations

  • Robinson E. Pino
    • 1
  1. 1.ICF InternationalFairfaxUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4614-7597-2
  • Copyright Information Springer Science+Business Media New York 2014
  • Publisher Name Springer, New York, NY
  • eBook Packages Computer Science
  • Print ISBN 978-1-4614-7596-5
  • Online ISBN 978-1-4614-7597-2
  • Series Print ISSN 1568-2633
  • About this book
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