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E-raamat: Digital Fingerprinting

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  • Formaat: PDF+DRM
  • Ilmumisaeg: 25-Oct-2016
  • Kirjastus: Springer-Verlag New York Inc.
  • Keel: eng
  • ISBN-13: 9781493966011
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Digital FingerprintingSuurem pilt
  • Formaat: PDF+DRM
  • Ilmumisaeg: 25-Oct-2016
  • Kirjastus: Springer-Verlag New York Inc.
  • Keel: eng
  • ISBN-13: 9781493966011
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This is the first book on digital fingerprinting that comprehensively covers the major areas of study in a range of information security areas including authentication schemes, intrusion detection, forensic analysis and more.  Available techniques for assurance are limited and authentication schemes are potentially vulnerable to the theft of digital tokens or secrets.  Intrusion detection can be thwarted by spoofing or impersonating devices, and forensic analysis is incapable of demonstrably tying a particular device to specific digital evidence.  This book presents an innovative and effective approach that addresses these concerns.  

This book introduces the origins and scientific underpinnings of digital fingerprinting. It also proposes a unified framework for digital fingerprinting, evaluates methodologies and includes examples and case studies. The last chapter of this book covers the future directions of digital fingerprinting. 

This book is designed for practitioners and researchers working in the security field and military. Advanced-level students focused on computer science and engineering will find this book beneficial as secondary textbook or reference. 


Introduction
1(4)
Yong Guan
Sneha Kumar Kasera
Cliff Wang
Ryan M. Gerdes
1 Overview
1(1)
2 Applications and Requirements of Fingerprints
2(1)
3 Types of Fingerprints
2(3)
Types and Origins of Fingerprints
5(26)
Davide Zanetti
Srdjan Capkun
Boris Danev
1 Introduction
5(1)
2 Physical-Layer Device Identification
6(11)
2.1 General View
6(2)
2.2 Device Under Identification
8(1)
2.3 Identification Signals
9(1)
2.4 Features
9(3)
2.5 Device Fingerprints
12(1)
2.6 Physical-Layer Identification System
13(1)
2.7 System Performance and Design Issues
14(1)
2.8 Improving Physical-Layer Identification Systems
15(2)
3 State of the Art
17(8)
3.1 Transient-Based Approaches
17(4)
3.2 Modulation-Based Approaches
21(1)
3.3 Other Approaches
22(1)
3.4 Attacking Physical-Layer Device Identification
23(1)
3.5 Summary and Conclusion
24(1)
4 Future Research Directions
25(1)
5 Conclusion
26(5)
References
27(4)
Device Measurement and Origin of Variation
31(8)
Ryan M. Gerdes
Mani Mina
Thomas E. Daniels
1 Introduction
31(3)
1.1 ABCD Parameters
33(1)
1.2 Proposed Model
33(1)
2 Measuring Parameters
34(2)
3 Determining Component Significance
36(2)
3.1 Constructing Model Input
36(1)
3.2 Producing Model Output
36(1)
3.3 Evaluating Model Output
37(1)
4 Conclusion
38(1)
References
38(1)
Crytpo-Based Methods and Fingerprints
39(30)
Joe H. Novak
Sneha Kumar Kasera
Yong Guan
1 Introduction
39(2)
1.1 Authentication
39(1)
1.2 Key Generation
40(1)
2 Techniques
41(23)
2.1 Physical Unclonable Functions
41(8)
2.2 Controlled Physical Unclonable Functions
49(3)
2.3 Clock Skew
52(6)
2.4 Wireless Devices
58(3)
2.5 Optical Media
61(2)
2.6 Trojan Detection
63(1)
2.7 Software Control
63(1)
3 Tradeoffs
64(1)
3.1 Benefits
64(1)
3.2 Drawbacks
65(1)
4 Summary
65(4)
References
66(3)
Fingerprinting by Design: Embedding and Authentication
69(20)
Paul L. Yu
Brian M. Sadler
Gunjan Verma
John S. Baras
1 Background
69(3)
1.1 Intrinsic Fingerprints
69(1)
1.2 Fingerprint Embedding
70(1)
1.3 Fingerprinting and Communications
71(1)
2 Introduction to Embedded Authentication
72(1)
3 Framework for Embedded Authentication
72(5)
3.1 Authentication System---Transmitter
73(1)
3.2 Authentication System---Receiver
74(3)
3.3 Authentication Performance
77(1)
4 Metrics for Embedded Fingerprint Authentication
77(5)
4.1 Impact on Data BER
77(1)
4.2 Authentication Performance
78(1)
4.3 Security Analysis
79(2)
4.4 Complexity
81(1)
5 Experimental Results
82(3)
5.1 Authentication Performance
82(1)
5.2 Key Equivocation
82(2)
5.3 Impact on Data BER
84(1)
6 Conclusions
85(4)
Appendix: Precoding and Power-Allocation with CSI
85(1)
No CSI
85(1)
Perfect CSI
86(1)
Statistical CSI
86(1)
References
87(2)
Digital Fingerprint: A Practical Hardware Security Primitive
89(26)
Gang Qu
Carson Dunbar
Xi Chen
Aijiao Cui
1 Introduction
89(4)
2 Digital Fingerprinting for IP Protection
93(7)
2.1 Background on Fingerprinting
93(1)
2.2 The Need and Challenge of Digital Fingerprinting IPs
94(1)
2.3 Requirements of Digital Fingerprinting
94(1)
2.4 Iterative Fingerprinting Techniques
95(3)
2.5 Fingerprinting with Constraint-Addition
98(2)
3 Observability Don't Care Fingerprinting
100(4)
3.1 Illustrative Example
100(1)
3.2 Observability Don't Care Conditions
101(1)
3.3 Finding Locations for Circuit Modification Based on ODCs
101(1)
3.4 Determining Potential Fingerprinting Modifications
102(1)
3.5 Maintaining Overhead Constraints
103(1)
3.6 Security Analysis
103(1)
4 Satisfiability Don't Care Fingerprinting
104(5)
4.1 Satisfiability Don't Care and Illustrative Example
104(1)
4.2 Assumptions for SDC Based Fingerprinting
105(1)
4.3 SDC Based Fingerprinting Technique
106(1)
4.4 Fingerprint Embedding Scheme
107(1)
4.5 Security Analysis
108(1)
5 Scan Chain Fingerprinting
109(4)
5.1 Illustrative Example
109(1)
5.2 Basics on Scan Chain Design
110(1)
5.3 Scan Chain Fingerprinting
111(1)
5.4 Security Analysis
111(2)
6 Conclusion
113(2)
References
113(2)
Operating System Fingerprinting
115(26)
Jonathan Gurary
Ye Zhu
Riccardo Bettati
Yong Guan
1 Overview of Operating System Fingerprinting
115(1)
2 Major Operating System Fingerprinting Techniques
116(8)
2.1 OS Fingerprinting
116(6)
2.2 Reconnaissance Through Packet-Content Agnostic Traffic Analysis
122(1)
2.3 Analysis of Smartphone Traffic
123(1)
2.4 Analysis of Encrypted Traffic
124(1)
3 Case Study: Smartphone OS Reconnaissance
124(11)
3.1 System and Threat Model
127(1)
3.2 Identifying Smartphone Operating Systems
128(4)
3.3 Empirical Evaluation
132(3)
4 Summary and Future Directions
135(6)
Appendix A Detailed Descriptions of Algorithms
136(1)
References
137(4)
Secure and Trustworthy Provenance Collection for Digital Forensics
141(36)
Adam Bates
Devin J. Pohly
Kevin R.B. Butler
1 Introduction
141(1)
2 Provenance-Aware Systems
142(5)
2.1 Disclosed Provenance-Aware Systems
143(1)
2.2 Automatic Provenance-Aware Systems
144(3)
3 Ensuring the Trustworthiness of Provenance
147(3)
3.1 Security Challenges to Provenance Collection
147(2)
3.2 The Provenance Monitor Concept
149(1)
4 High-Fidelity Whole Systems Provenance
150(9)
4.1 Design of Hi-Fi
150(1)
4.2 Handling of System-Level Objects
151(3)
4.3 Hi-Fi Implementation
154(4)
4.4 Limitations of Hi-Fi
158(1)
5 Linux Provenance Modules
159(6)
5.1 Augmenting Whole-System Provenance
159(1)
5.2 Threat Model
160(1)
5.3 Design of LPM
161(3)
5.4 Deploying LPM
164(1)
6 Analyzing the Security of Provenance Monitors
165(6)
6.1 Completeness Analysis of Hi-Fi
165(4)
6.2 Security Analysis of LPM
169(2)
7 Current and Future Challenges to Provenance for Forensics
171(6)
References
173(4)
Conclusion
177(6)
Yong Guan
Sneha Kumar Kasera
Cliff Wang
Ryan M. Gerdes
1 Overview
177(1)
2 Measurements of Fingerprints
178(1)
3 Fingerprints and Crypto-Based Methods
179(1)
4 Science of Fingerprints
179(1)
5 Security of Fingerprints
180(3)
Index 183
Ryan M. Gerdes is an assistant professor of Electrical and Computer Engineering at Virginia Polytechnic Institute. His interests include signal and data authentication, hardware and device security, computer and network security, transportation security, and applied electromagnetics. Yong Guan is an associate professor at Iowa State University. His research and teaching are in computer networks and distributed systems, with focuses on security issues, including computer and network forensics, wireless and sensor network security, privacy-enhancing technologies for the Internet, and secure real-time computing and communication. Sneha Kumar Kasera is a professor in the School of Computing at the University of Utah. Before joining the University of Utah, he spent four years in the Mobile Networking Research Department at Bell Labs, Lucent Technologies. Earlier, I obtained a Ph.D. in Computer Science from the Advanced Networks ResearchGroup at the University of Massachusetts in Amherst.  Cliff Wang is the program director at US Army Research Office, managing a large portfolio of university research. He is also appointed as an adjunct professor at North Carolina State University. Dr. Wang is a fellow of IEEE.
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