Digital Watermarking for Machine Learning Model (Record no. 15282)

MARC details
000 -LEADER
fixed length control field 02629nam a2200361Ia 4500
000 - LEADER
fixed length control field 03824nam a22003975i 4500
001 - CONTROL NUMBER
control field 978-981-19-7554-7
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240319120915.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 230529s2023 si | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789811975547
-- 978-981-19-7554-7
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 6.31
245 ## - TITLE STATEMENT
Title Digital Watermarking for Machine Learning Model
Statement of responsibility, etc. edited by Lixin Fan, Chee Seng Chan, Qiang Yang.
Medium [electronic resource] :
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2023.
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Singapore
Name of publisher, distributor, etc. Springer Nature Singapore
Date of publication, distribution, etc. 2023
300 ## - PHYSICAL DESCRIPTION
Extent XVI, 225 p. 1 illus.
Other physical details online resource.
520 ## - SUMMARY, ETC.
Summary, etc. Machine learning (ML) models, especially large pretrained deep learning (DL) models, are of high economic value and must be properly protected with regard to intellectual property rights (IPR). Model watermarking methods are proposed to embed watermarks into the target model, so that, in the event it is stolen, the model's owner can extract the pre-defined watermarks to assert ownership. Model watermarking methods adopt frequently used techniques like backdoor training, multi-task learning, decision boundary analysis etc. to generate secret conditions that constitute model watermarks or fingerprints only known to model owners. These methods have little or no effect on model performance, which makes them applicable to a wide variety of contexts. In terms of robustness, embedded watermarks must be robustly detectable against varying adversarial attacks that attempt to remove the watermarks. The efficacy of model watermarking methods is showcased in diverse applications including image classification, image generation, image captions, natural language processing and reinforcement learning. This book covers the motivations, fundamentals, techniques and protocols for protecting ML models using watermarking. Furthermore, it showcases cutting-edge work in e.g. model watermarking, signature and passport embedding and their use cases in distributed federated learning settings.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computer Imaging, Vision, Pattern Recognition and Graphics.
9 (RLIN) 32217
Topical term or geographic name entry element Computer vision.
9 (RLIN) 32218
Topical term or geographic name entry element Data and Information Security.
9 (RLIN) 32219
Topical term or geographic name entry element Data protection.
9 (RLIN) 32220
Topical term or geographic name entry element Image processing
9 (RLIN) 32221
Topical term or geographic name entry element Image processing.
9 (RLIN) 32221
Topical term or geographic name entry element Image Processing.
9 (RLIN) 32222
Topical term or geographic name entry element Machine learning.
9 (RLIN) 32223
Topical term or geographic name entry element Machine Learning.
9 (RLIN) 32224
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Chan, Chee Seng.
9 (RLIN) 32225
Personal name Fan, Lixin.
9 (RLIN) 32226
Personal name Yang, Qiang.
9 (RLIN) 32227
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-981-19-7554-7">https://doi.org/10.1007/978-981-19-7554-7</a>
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type e-Book
Source of classification or shelving scheme Dewey Decimal Classification
Holdings
Withdrawn status Lost status Damaged status Not for loan Home library Current library Shelving location Date acquired Source of acquisition Total Checkouts Barcode Date last seen Price effective from Koha item type Public note
        S. R. Ranganathan Learning Hub S. R. Ranganathan Learning Hub Online   Veda Library Solutions Pvt. Ltd., Noida   EB2268 2024-03-19 2024-03-19 e-Book Platform:Springer