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Data Science for Cyber-Security (Security Science and Technology)

Data Science for Cyber-Security (Security Science and Technology)

Data Science for Cyber-Security (Security Science and Technology)
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Data Science for Cyber-Security (Security Science and Technology) Hardback - 2018

by Nick Heard, Niall Adams Patrick Rubin-D

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World Scientific Publishing Europe Ltd, 2018-11-20. hardcover. Used: Good. 6.00x0.75x9.00. Buy with confidence. Excellent Customer Service & Return policy.
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Details

  • Title Data Science for Cyber-Security (Security Science and Technology)
  • Author Nick Heard, Niall Adams Patrick Rubin-D
  • Binding Hardback
  • Condition Used: Good
  • Pages 304
  • Volumes 1
  • Language ENG
  • Publisher World Scientific Publishing Europe Ltd
  • Publication date 2018-11-20
  • Features Bibliography, Index
  • Bookseller's Inventory # SONG1786345633
  • ISBN 9781786345639 / 1786345633
  • Weight 1.27 lbs (0.58 kg)
  • Dimensions 9 x 6 x 0.75 in (22.86 x 15.24 x 1.91 cm)
  • Size 6.00x0.75x9.00
  • Category Computers - Computer Security
  • Library of Congress subjects Internet - Security measures - Data, Data protection - Statistical methods
  • Library of Congress Catalogue Number 2018021228
  • Dewey Decimal Code 005.8
  • Quantity available 1

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Reader reviews for Data Science for Cyber-Security (Security Science and Technology)

From the publisher

Cyber-security is a matter of rapidly growing importance in industry and government. This book provides insight into a range of data science techniques for addressing these pressing concerns.

The application of statistical and broader data science techniques provides an exciting growth area in the design of cyber defences. Networks of connected devices, such as enterprise computer networks or the wider so-called Internet of Things, are all vulnerable to misuse and attack, and data science methods offer the promise to detect such behaviours from the vast collections of cyber traffic data sources that can be obtained. In many cases, this is achieved through anomaly detection of unusual behaviour against understood statistical models of normality.

This volume presents contributed papers from an international conference of the same name held at Imperial College. Experts from the field have provided their latest discoveries and review state of the art technologies.

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