On the Learnability of Physically Unclonable Functions (eBook)
XXIV, 86 Seiten
Springer International Publishing (Verlag)
978-3-319-76717-8 (ISBN)
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.
List of Publications Related to this Thesis 7
Contents 8
Acronyms 10
Symbols and Operators 11
List of Figures 15
List of Tables 16
List of Algorithms 17
Abstract 18
1 Introduction 20
1.1 Motivation 20
1.1.1 Hardware Root of Trust 21
1.1.2 Fragile Security of ICs 21
1.2 Physically Unclonable Functions 22
1.3 Thesis Statement 24
1.3.1 Problem Statement 24
1.3.2 Our Attack Model 25
1.3.3 Thesis Contributions 26
1.4 Outline of the Thesis 27
2 Definitions and Preliminaries 28
2.1 Notations 28
2.2 PUFs 28
2.3 Boolean Functions 30
2.3.1 Linearity of Boolean Functions 31
2.3.2 Average Sensitivity of Boolean Functions 32
2.3.3 Non-linearity of PUFs over mathbbF2 and the Existence of Influential Bits 33
2.4 Linear Threshold Functions 34
2.5 Regular Language and Principles of DFAs 36
2.6 Probably Approximately Correct Model 37
3 PAC Learning of Arbiter PUFs 40
3.1 Introduction 40
3.2 Representing Arbiter PUFs by DFAs 42
3.2.1 Discretization Process of Delay Values 44
3.2.2 Building a DFA Representing an Arbiter PUF 45
3.3 PAC Learning of Arbiter PUFs 48
3.4 Comparison with Related Work 51
3.5 Practical Considerations 52
3.5.1 The Important Role of M 52
3.5.2 Dealing with the Metastable Condition 53
4 PAC Learning of XOR Arbiter PUFs 54
4.1 Introduction 55
4.2 LTF Representation of XOR Arbiter PUFs 56
4.3 PAC Learning of XOR Arbiter PUFs 58
4.4 PAC Learning of Noisy XOR Arbiter PUFs 62
4.5 Discussion 63
4.5.1 Theoretical Considerations 63
4.5.2 Practical Considerations 65
5 PAC Learning of Ring Oscillator PUFs 67
5.1 Introduction 68
5.2 DL Representation of RO-PUFs 69
5.3 PAC Learnability of the 2-DL Representing the RO-PUF 71
5.4 Results and Discussion 73
6 PAC Learning of Bistable Ring PUFs 76
6.1 Introduction 77
6.2 Architecture of the BR-PUF Family 78
6.3 A Constant Upper Bound on the Number of Influential Bits 79
6.3.1 Heuristic Approaches 79
6.3.2 A Boolean-Analytical Approach 81
6.4 PAC Learning of PUFs Without Prior Knowledge of Their … 83
6.5 Results and Discussion 85
7 Follow-Up Work 90
7.1 Lattice Basis Reduction Attack 90
7.2 Laser Fault Injection Attack 91
8 Conclusion and Future Work 93
References 96
| Erscheint lt. Verlag | 24.3.2018 |
|---|---|
| Reihe/Serie | T-Labs Series in Telecommunication Services |
| Zusatzinfo | XXIV, 86 p. 21 illus., 4 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Themenwelt | Mathematik / Informatik ► Mathematik |
| Technik ► Elektrotechnik / Energietechnik | |
| Schlagworte | bistable ring PUFs • Learnable PUFs • ML attack • PAC learning of PUFs • Physically Unclonable Function PUF • physical security primitives • PUF circuit design • PUF vulnerability • ring-oscillator • XOR Arbiter |
| ISBN-10 | 3-319-76717-8 / 3319767178 |
| ISBN-13 | 978-3-319-76717-8 / 9783319767178 |
| Haben Sie eine Frage zum Produkt? |
PDF (Wasserzeichen)Größe: 4,3 MB
DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasserzeichen und ist damit für Sie personalisiert. Bei einer missbräuchlichen Weitergabe des eBooks an Dritte ist eine Rückverfolgung an die Quelle möglich.
Dateiformat: PDF (Portable Document Format)
Mit einem festen Seitenlayout eignet sich die PDF besonders für Fachbücher mit Spalten, Tabellen und Abbildungen. Eine PDF kann auf fast allen Geräten angezeigt werden, ist aber für kleine Displays (Smartphone, eReader) nur eingeschränkt geeignet.
Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.
Zusätzliches Feature: Online Lesen
Dieses eBook können Sie zusätzlich zum Download auch online im Webbrowser lesen.
Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.
aus dem Bereich
