Adversarial Machine Learning (Record no. 12252)
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fixed length control field | 01802nmm a2200205Ia 4500 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
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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 | |
Link text | Click to Access the Online Book |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | e-Book |
Suppress in OPAC |
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 |
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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 |