On the Learnability of Physically Unclonable Functions (Record no. 79669)

000 -LEADER
fixed length control field 04143nam a22005775i 4500
001 - CONTROL NUMBER
control field 978-3-319-76717-8
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220801221433.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 180324s2018 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783319767178
-- 978-3-319-76717-8
082 04 - CLASSIFICATION NUMBER
Call Number 006.3
100 1# - AUTHOR NAME
Author Ganji, Fatemeh.
245 10 - TITLE STATEMENT
Title On the Learnability of Physically Unclonable Functions
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2018.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XXIV, 86 p. 21 illus., 4 illus. in color.
490 1# - SERIES STATEMENT
Series statement T-Labs Series in Telecommunication Services,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Introduction -- Definitions and Preliminaries -- PAC Learning of Arbiter PUFs -- PAC Learning of XOR Arbiter PUFs -- PAC Learning of Ring Oscillator PUFs -- PAC Learning of Bistable Ring PUFs -- Follow-up -- Conclusion.
520 ## - SUMMARY, ETC.
Summary, etc This book addresses the issue of Machine Learning (ML) attacks on Integrated Circuits through Physical Unclonable Functions (PUFs). It provides the mathematical proofs of the vulnerability of various PUF families, including Arbiter, XOR Arbiter, ring-oscillator, and bistable ring PUFs, to ML attacks. To achieve this goal, it develops a generic framework for the assessment of these PUFs based on two main approaches. First, with regard to the inherent physical characteristics, it establishes fit-for-purpose mathematical representations of the PUFs mentioned above, which adequately reflect the physical behavior of these primitives. To this end, notions and formalizations that are already familiar to the ML theory world are reintroduced in order to give a better understanding of why, how, and to what extent ML attacks against PUFs can be feasible in practice. Second, the book explores polynomial time ML algorithms, which can learn the PUFs under the appropriate representation. More importantly, in contrast to previous ML approaches, the framework presented here ensures not only the accuracy of the model mimicking the behavior of the PUF, but also the delivery of such a model. Besides off-the-shelf ML algorithms, the book applies a set of algorithms hailing from the field of property testing, which can help to evaluate the security of PUFs. They serve as a “toolbox”, from which PUF designers and manufacturers can choose the indicators most relevant for their requirements. Last but not least, on the basis of learning theory concepts, the book explicitly states that the PUF families cannot be considered as an ultimate solution to the problem of insecure ICs. As such, it provides essential insights into both academic research on and the design and manufacturing of PUFs.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-319-76717-8
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2018.
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-- text
-- txt
-- rdacontent
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-- computer
-- c
-- rdamedia
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-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Coding theory.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Information theory.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer science—Mathematics.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Electronic circuits.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Coding and Information Theory.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Mathematical Applications in Computer Science.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Electronic Circuits and Systems.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2192-2829
912 ## -
-- ZDB-2-ENG
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-- ZDB-2-SXE

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