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Methods to Enhance the PUF Reliability of Key Generation from PUFs - - PowerPoint PPT Presentation

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Methods to Enhance the PUF Reliability of Key Generation from PUFs J.-L.Danger, F . Lozach, Z. Cherif PROOFS14, Busan, South Korea Introduction to PUF and its reliability Methods to improve the reliability Experimental results

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Methods to Enhance the PUF Reliability of Key Generation from PUFs

J.-L.Danger, F . Lozac’h, Z. Cherif PROOFS’14, Busan, South Korea

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Introduction to PUF and its reliability Methods to improve the reliability Experimental results

Presentation Outline

Introduction to PUF and its reliability Methods to improve the reliability Experimental results

2 27 Sept 14 Presented by J.-L.Danger Methods to Enhance the PUF Reliability

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Introduction to PUF and its reliability Methods to improve the reliability Experimental results

PUF

PUF reminder

◮ Device fingerprint ◮ Avoid Reverse engineering attack of NVM memory but ◮ Suffers from attacks and reliability problems

This talk:

◮ presents methods to enhance the PUF reliability ◮ how to apply them to the “Loop PUF” ◮ presents the results from real devices (49 PUFs in ASIC

65nm)

3 27 Sept 14 Presented by J.-L.Danger Methods to Enhance the PUF Reliability

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Introduction to PUF and its reliability Methods to improve the reliability Experimental results

Loop PUF

◮ Set of N identical controllable delay chains of M elements

forming a ring oscillator

◮ For each challenge of MxN bits, the time is measured ◮ The response is the sorting of the time obtained from the

different challenges

◮ FPGA implementation presented by Cherif et al.1

1 N C1 CN

T

measurement

challenge C

Figure: Example of LPUF composed of N delay chains of 1 element

1Cherif et al. [CDGB12] 4 27 Sept 14 Presented by J.-L.Danger Methods to Enhance the PUF Reliability

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Introduction to PUF and its reliability Methods to improve the reliability Experimental results

Example of Key generation with the Loop PUF

  • 1. Choose two equivalent challenges (same Hamming

Weight)

  • 2. Measure the Time T1 with Challenge C1
  • 3. Measure the Time T2 with Challenge C2
  • 4. The Key bit is given by

KEY bit = sign(T1 − T2) (1)

5 27 Sept 14 Presented by J.-L.Danger Methods to Enhance the PUF Reliability

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Introduction to PUF and its reliability Methods to improve the reliability Experimental results

Reliability issue

◮ The ∆T = T1 − T2 measurement is highly dependant on

the noise level, thus generating potential errors.

◮ An helper data is very useful to help correcting the errors

PUF correction PUF ref. key helper creation Use noisy key key helper Enrollment Figure: Use of helpers to correct the key

6 27 Sept 14 Presented by J.-L.Danger Methods to Enhance the PUF Reliability

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Introduction to PUF and its reliability Methods to improve the reliability Experimental results

Studied Methods to improve the reliability

  • 1. Selecting the challenges
  • 2. Enlarging the PUF measurement window
  • 3. Increasing the number of measurements
  • 4. Removing the most unreliable bits
  • 5. Correcting the key

7 27 Sept 14 Presented by J.-L.Danger Methods to Enhance the PUF Reliability

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Introduction to PUF and its reliability Methods to improve the reliability Experimental results

Selecting the challenges

What are the best challenges to generate one key bit ? Answer: those having the maximum Hamming Distance Proof: as ∆T = T1 − T2 =

N

  • i=1

ti,C1i − ti,C2i (2)

Where ti,C1i represents the time of the elementary delay element i controlled by the challenge bit C1i .

⇒ The total number of elementary delays involved in ∆T is the Hamming distance HD(C1, C2) between the two challenges. ⇒ For one key bit, choose two equivalent and complementary challenges (HW=N/2, HD=N)

8 27 Sept 14 Presented by J.-L.Danger Methods to Enhance the PUF Reliability

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Introduction to PUF and its reliability Methods to improve the reliability Experimental results

Selecting the challenges : all key bits

The Hamming distance between complementary challenge pair and the other pairs must be as great as possible to avoid correlated key bits. references :

◮ ⇒ Use of Constant Weight Codes A(n, d, w), studied

in [BSR, CDG+13, CCD+]

Table: Lower Bound of Constant Weight Codes

(n,w) d n/2 n/3 n/4 n/5 n/6 n/7 (12,6) 22 132 ?

  • ?
  • (16,8)

30

  • 1170
  • (18,9)

34 424

  • ?
  • (20,10)

38

  • ?

13452

  • (24,12)

46 2576 15906

  • 151484
  • (28,14)

54

  • ?
  • 1535756

(30,15) 58 19210

  • ?

?

  • 9

27 Sept 14 Presented by J.-L.Danger Methods to Enhance the PUF Reliability

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Introduction to PUF and its reliability Methods to improve the reliability Experimental results

Enlarging the PUF measurement window

◮ Based on an increase of the measurement time. ◮ Classical methods for RO-PUF [DV13].

The noise can be reduced when enlarging the measurement window (width = mw) ∆T = T1 − T2 + n(t) (3) n(t) ∼ N(0, s2/mw) (4) but this can increase significantly the key generation time.

10 27 Sept 14 Presented by J.-L.Danger Methods to Enhance the PUF Reliability

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Introduction to PUF and its reliability Methods to improve the reliability Experimental results

Increasing the Number of Measurement

◮ The principle is to repeat the measurement of ∆T R times. ◮ Method very similar to the Time Majority voting presented

in [AMS+10]. n(t) ∼ N(0, s2/R) (5)

◮ The difference with enlarging mw is that the repetition R of

the measurement can be controlled dynamically.

◮ If ∆T is not above a fixed threshold Th, There is a new

measurement

11 27 Sept 14 Presented by J.-L.Danger Methods to Enhance the PUF Reliability

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Introduction to PUF and its reliability Methods to improve the reliability Experimental results

Removing the most unreliable key bits

◮ A helper data is needed in order to indicate the most

unreliable bits [HB10].

◮ the error probability depends on the probability of having

|∆T| less than the Threshold |Th|. Pr(|∆T| < |Th|) = erf |Th| σ √ 2

  • (6)

0.2 0.4 0.6 0.8 1 1.2

  • 8
  • 6
  • 4
  • 2

2 4 6 8

  • Th

Th

pdf(∆T)=Ν(0,σ2) pdf(∆T1)=Ν(E(∆T1),s2)

12 27 Sept 14 Presented by J.-L.Danger Methods to Enhance the PUF Reliability

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Introduction to PUF and its reliability Methods to improve the reliability Experimental results

Correcting the key

◮ Well known method explained in many

papers [GCvDD02], [MTV09]

◮ based on error-correction codes (ECC) to correct errors ◮ The helper indicates the code ◮ The method can take advantage of the less reliable bits

knowledge (case of the Loop PUF). For instance:

◮ combine a low-cost Hamming codes ◮ and the Chase algorithm [Cha72] 13 27 Sept 14 Presented by J.-L.Danger Methods to Enhance the PUF Reliability

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Introduction to PUF and its reliability Methods to improve the reliability Experimental results

Setup and parameters

◮ Methods tested on ASIC prototype embedding 49 Loop

PUFs.

◮ 3 result types:

  • 1. The error rate. shows the performance of the key

generation procedure in terms of reliability.

  • 2. The Key length. depends on both the number of challenge

pairs and the number of ignored unreliable bits mnib.

  • 3. The key generation time consumption. influenced by

both the measurement window mw and the number of unreliable bits mnib .

14 27 Sept 14 Presented by J.-L.Danger Methods to Enhance the PUF Reliability

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Introduction to PUF and its reliability Methods to improve the reliability Experimental results

Unstable bits

Cartography of the 49 PUFs:

Cartography of the number of unstable bits per PUF 1 2 3 4 5 6 chip column 1 2 3 4 5 6 chip row 2 4 6 8 10

  • Nb. of unreliable bits

15 27 Sept 14 Presented by J.-L.Danger Methods to Enhance the PUF Reliability

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Introduction to PUF and its reliability Methods to improve the reliability Experimental results

Key Generation Time Consumption

1 10 100 0xa 0xb 0xc 0xd 0xe 0xf Key generation time consumption (in milliseconds) Window width mnib = 0 mnib = 1 mnib = 2 mnib = 3 mnib = 4 mnib = 5 mnib = 6 mnib = 7 mnib = 8 mnib = 9 mnib = 10

Figure: Impact of mnib and the mw on the key generation time.

16 27 Sept 14 Presented by J.-L.Danger Methods to Enhance the PUF Reliability

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Introduction to PUF and its reliability Methods to improve the reliability Experimental results

Error Rate Evaluation Without Correction Scheme

<10e-9 1e-08 1e-07 1e-06 1e-05 0.0001 0.001 0.01 0.1 1 0.001 0.01 0.1 1 Binary Error Rate Key generation time consumption (s) mnib = 0 mnib = 1 mnib = 2 mnib = 3 mnib = 4 mnib = 5 mnib = 6 mnib = 7 mnib = 8 mnib = 9 mnib = 10

Figure: BER evolution without correction schemes when varying the mnib parameter.

17 27 Sept 14 Presented by J.-L.Danger Methods to Enhance the PUF Reliability

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Introduction to PUF and its reliability Methods to improve the reliability Experimental results

Error Rate Evaluation With Correction Scheme

<10e-9 1e-08 1e-07 1e-06 1e-05 0.0001 0.001 0.01 0.1 1 0.01 0.1 Binary Error Rate Key generation time (s) mnib=0 mnib=1 mnib=2 mnib=3

Figure: BER evolution when varying the key length using a correction scheme.

18 27 Sept 14 Presented by J.-L.Danger Methods to Enhance the PUF Reliability

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Introduction to PUF and its reliability Methods to improve the reliability Experimental results

Hardware Implementation Complexity

Table: Hardware complexity of the error correction algorithm: number

  • f occupied slices in Xilinx Virtex 5 technology.

Loop PUF complexity 20 adaptive key quantification 97 Key correction complexity 235 Total complexity 117 352 BER at 10 ms 10−9 10−5 BER at 100 ms 10−9 10−9 key length ≥ 56 ≥ 61

19 27 Sept 14 Presented by J.-L.Danger Methods to Enhance the PUF Reliability

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Introduction to PUF and its reliability Methods to improve the reliability Experimental results

Conclusions

◮ Five methods are presented to enhance the Loop PUF

reliability

◮ Most of them portable to other PUFs ◮ Validated theoretically and by experience ◮ On a 65nm ASIC embedding 49 PUFs ◮ Interest to eliminate unstable bits for a low-cost and

efficient PUF

◮ In a reasonnable time

20 27 Sept 14 Presented by J.-L.Danger Methods to Enhance the PUF Reliability

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Introduction to PUF and its reliability Methods to improve the reliability Experimental results

R´ ef´ erences

[AMS+10] Frederik Armknecht, Roel Maes, Ahmad-Reza Sadeghi, Berk Sunar, and Pim Tuyls. Memory leakage-resilient encryption based on physically unclonable functions. In Towards Hardware-Intrinsic Security - Foundations and Practice, pages 135–164. 2010. [BSR]

  • A. Brouwer, N. Sloane, and E.M. Rains.

Constant weight codes. http://www.win.tue.nl/~aeb/codes/Andw.html. [CCD+] Yeow Meng Chee, Zouha Cherif, Jean-Luc Danger, Sylvain Guilley, Han Mao Kiah, Jon-Lark Kim, Patrick Sol´ e, and Xiande Zhang. Multiply constant-weight codes and the reliability of loop physically unclonable functions. IEEE Transactions on Information Theory. To appear (accepted July 2014), DOI: 10.1109/TIT.2014.2359207. [CDG+13] Zouha Cherif, Jean-Luc Danger, Sylvain Guilley, Jon-Lark Kim, and Patrick Sol´ e. Multiply constant weight codes. In Information Theory Proceedings (ISIT), 2013 IEEE International Symposium on, pages 306–310, 2013. [CDGB12] Zouha Cherif, Jean-Luc Danger, Sylvain Guilley, and Lilian Bossuet. An Easy-to-Design PUF based on a single oscillator: the Loop PUF. In DSD, September 5-8 2012. C ¸ es ¸me, Izmir, Turkey; (Online PDF). [Cha72]

  • D. Chase.

Class of algorithms for decoding block codes with channel measurement information. Information Theory, IEEE Transactions on, 18(1):170–182, 1972. 21 27 Sept 14 Presented by J.-L.Danger Methods to Enhance the PUF Reliability

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Introduction to PUF and its reliability Methods to improve the reliability Experimental results [DV13] Jeroen Delvaux and Ingrid Verbauwhede. Fault Injection Modeling Attacks on 65nm Arbiter and RO Sum PUFs via Environmental Changes. Cryptology ePrint Archive, Report 2013/619, 2013. http://eprint.iacr.org/2013/619. [GCvDD02]

  • B. Gassend, D. Clarke, M. van Dijk, and S. Devadas.

Controlled physical random functions. In Computer Security Applications Conference, 2002. Proceedings. 18th Annual, pages 149 – 160, 2002. [HB10] Maximilian Hofer and Christoph B¨

  • hm.

An alternative to error correction for sram-like pufs. In Stefan Mangard and Franc ¸ois-Xavier Standaert, editors, CHES 2010, Santa Barbara, CA, USA, August 17-20, 2010. Proceedings, volume 6225 of LNCS, pages 335–350. Springer, 2010. [MTV09] Roel Maes, Pim Tuyls, and Ingrid Verbauwhede. Low-overhead implementation of a soft decision helper data algorithm for sram pufs. In CHES 2009, Lausanne, Switzerland, September 6-9, 2009, Proceedings, volume 5747 of Lecture Notes in Computer Science, pages 332–347. Springer, 2009. 22 27 Sept 14 Presented by J.-L.Danger Methods to Enhance the PUF Reliability