Adversarial Machine Learning (Record no. 12252)

MARC details
000 -LEADER
fixed length control field 01802nmm a2200205Ia 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220920s9999||||xx |||||||||||||| ||und||
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781107338548
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.31
Item number J774A
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Joseph, A. D.
Relator term Author
Language of a work English
9 (RLIN) 1883
245 #0 - TITLE STATEMENT
Title Adversarial Machine Learning
Statement of responsibility, etc. / by A. D. Joseph and others.
Medium [Electronic Resource]
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Cambridge
Name of publisher, distributor, etc. : Cambridge University Press,
Date of publication, distribution, etc. 2019
300 ## - PHYSICAL DESCRIPTION
Extent xiv, 325p.
500 ## - GENERAL NOTE
General note Written by leading researchers, this complete introduction brings together all the theory and tools needed for building robust machine learning in adversarial environments. Discover how machine learning systems can adapt when an adversary actively poisons data to manipulate statistical inference, learn the latest practical techniques for investigating system security and performing robust data analysis, and gain insight into new approaches for designing effective countermeasures against the latest wave of cyber-attacks. Privacy-preserving mechanisms and the near-optimal evasion of classifiers are discussed in detail, and in-depth case studies on email spam and network security highlight successful attacks on traditional machine learning algorithms. Providing a thorough overview of the current state of the art in the field, and possible future directions, this groundbreaking work is essential reading for researchers, practitioners and students in computer security and machine learning, and those wanting to learn about the next stage of the cybersecurity arms race.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computer Science
9 (RLIN) 926
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Nelson, B.
Relationship information [Author]
9 (RLIN) 1884
Personal name Rubinstein, B. I. P.
Relationship information [Author]
9 (RLIN) 1885
Personal name Tygar, J. D.
Relationship information [Author]
9 (RLIN) 1886
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1017/9781107338548">https://doi.org/10.1017/9781107338548</a>
Electronic format type PDF
Link text Click to Access the Online Book
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type e-Book
Suppress in OPAC
Holdings
Withdrawn status Lost status Damaged status Use restrictions Not for loan Collection Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type Public note
      e-Book For Access   Textbook S. R. Ranganathan Learning Hub S. R. Ranganathan Learning Hub Online 2022-09-20 Infokart India Pvt. Ltd., New Delhi 215.00   006.31 J774A EB0392 2022-09-20 2022-09-20 e-Book Platform : Cambridge Core