Presentation is loading. Please wait.

Presentation is loading. Please wait.

SuperPUF : Integrating Heterogeneous Physically Unclonable Functions Michael Wang, Andrew Yates, Igor L. Markov.

Similar presentations


Presentation on theme: "SuperPUF : Integrating Heterogeneous Physically Unclonable Functions Michael Wang, Andrew Yates, Igor L. Markov."— Presentation transcript:

1 SuperPUF : Integrating Heterogeneous Physically Unclonable Functions Michael Wang, Andrew Yates, Igor L. Markov

2 2 Outline Motivation Existing PUF Designs Process Variation and Entropy for PUFs SuperPUF Architecture Design Automation Generalizing SuperPUF Extending to 3D Empirical Validation Future Work

3 3 Motivation Counterfeit ICs damage suppliers’ reputations and displace IC sales Secret keys stored in non-volatile memory are expensive and can be probed Alternative: Physical Unclonable Functions (PUFs) generate secret keys by sampling on-chip process variation

4 A physical unclonable function is a physical entity that is embodied in a physical structure and is easy to evaluate but hard to predict. Further, an individual PUF device must be easy to make but practically impossible to duplicate, even given the exact manufacturing process that produced it. In this respect it is the hardware analog of a one-way function. "Physical unclonable function." Wikipedia, The Free Encyclopedia. Wikimedia Foundation, Inc. 11 September 2014. Web. 30 Oct. 2014.

5 5 Existing PUF Designs Arbiter PUFs Composed of pairs of identical delay paths, MUXes, and an arbiter Signal is sent through delay paths, arbiter detects which path propagates signal first Large number of possible challenges (2 N for N MUXes), but responses are highly correlated Ring Oscillator (RO) PUFs Generate CRPs by comparing the frequencies of identical ring oscillators Multiple oscillations compound the small differences in circuits; well suited for low process variation situations Clock PUFs Use clock skews to generate CRPs Clock PUFs are connected to many parts of the IC; difficult to tamper with SRAM PUFs, On chip power-up, process variation biases an SRAM cell to start at either a 1 or a 0 One bit per SRAM cell Simple: no precisely-timed circuits and SRAM arrays are widespread

6 6 Outline Motivation Existing PUF Design Process Variation and Entropy for PUFs SuperPUF Architecture Design Automation Generalizing SuperPUF Extending to 3D Empirical Validation Future Work

7 7 Process Variation in PUFs Three main types of variation: granular, spatial, dynamic Granular Variation - Constant with distance Spatial Variation - Decays with distance - Represented by the spherical equation below: Dynamic Variation - Includes thermal fluctuations, EM noise and IR drop, circuit-aging effects - Stable PUFs must be insensitive to dynamic variation

8 8 Entropy in PUFs Differential Entropy h can be estimated: Discrete Entropy quantifies losses during integration and extraction of discrete PUF readouts To extract discrete entropy from continuous distribution: perform quantization into ∆, assign single probabilities to each, and apply Shannon’s formula:

9 9 Note on PUF Robustness PUFs convert continuous values (transition time, voltage, transistor strength, etc.) into bits Minute dynamic variations of near-threshold values routinely produce undesirable fluctuations in generated bits There is a general tradeoff between extracted entropy and robustness

10 10 Outline Motivation Existing PUF Design Process Variation and Entropy for PUFs SuperPUF Architecture Design Automation Generalizing SuperPUF Extending to 3D Empirical Validation Future Work

11 11 ClockPUF Revisited Clock signals are tapped, returned to arbiter using tree structure Sinks chosen to form diamond annulus Y. Yao, M.-B. Kim, I.L. Markov, F. Koushanfar, “ClockPUF: Physical Unclonable Functions Based on Clock Networks”, DATE 2013:422-427.

12 12 SuperPUF Architecture Previous tree structure from ClockPUF can be extended to link entropy sources in general Overhead can be improved using path (fig. a vs fig. b). Path removes need for entropy sources to be placed in a diamond annulus A path not restricted to diamond annulus shape; has flexibility to link entropy sources to take advantage of both high (c) and low (d) spatial correlation

13 13 SuperPUF Architecture Transition from ClockPUF tree to SuperPUF path requires architecture that can carry several signal transition on single wire Entropy sources connected by a path; time-varying signals combined with path using XOR gates:

14 14 SuperPUF Architecture Figure 1: The rise and fall of SuperPUF: linking entropy sources (from ClockPUF) with a single path using XOR gates. SPICE waveforms are shown for 6 (top), 12 (middle) and 24 (bottom) XOR gates.

15 15 Outline Motivation Existing PUF Design Process Variation and Entropy for PUFs SuperPUF Architecture Design Automation Generalizing SuperPUF Extending to 3D Empirical Validation Future Work

16 16 Design Automation

17 17 RCM/LK Step 5a is done using Reverse Cuthill-Mckee Algorithm Step 5b is done using the Lin Kernighan TSP solver; linking sources to a least- cost path reduces to TSP: View n points in the Manhattan plane as vertices of a clique G with Manhattan distances as edge weights. Form a larger clique G’ by adding a ghost vertex g connected to all other vertices in G through 0-cost edges. Then each least-cost path of G corresponds (one-to-one) to a least-cost tour in G’ with the two edges adjacent to g removed.

18 18 Greedy

19 19 Greedy Greedy approach selects and links sources simultaneously (as opposed to RCM-LK 2-step). ‘First’ source is chosen arbitrarily. At each iteration afterwards, select source nearest to the previously selected source, subject to an entropy cutoff. Backtrack if no sources reach entropy cutoff before desired length of path is reached. Multiple random starts can be done with different ‘first’ sources.

20 20 Outline Motivation Existing PUF Design Process Variation and Entropy for PUFs SuperPUF Architecture Design Automation Generalizing SuperPUF Extending to 3D Empirical Validation Future Work

21 21 Generalizing SuperPUF Applying SuperPUF methodology to a heterogeneous set of entropy sources introduces three complications: 1.PUFs that require different readout regimes (ClockPUF, RO PUF, etc) must be multiplexed on a single ECP with appropriate enable signals 2.Estimating conditional-entropies between heterogeneous sources may require more complicated simulations

22 22 Generalizing SuperPUF 3.Introduction of entropy sources with flexible locations requires revisions in highlighted step (right) Potential for optimization: consider possible RO-PUF locations, estimating their correlations as functions of distance to other sources A more directed optimization: place entropy sources along an already constructed ECP

23 23 Generalizing SuperPUF

24 24 3D Through-silicon vias (TSVs) act as additional entropy sources that can be linked by a path (blue highlight) TSVs must also be accounted for as interconnects in both the entropy matrix and the distance matrix (red highlight)

25 25 3D Pairwise distances between entropy sources on adjacent 2D dice are calculated by: 1. Finding the TSV that ensures the shortest total distance 2.Adding the cost of the TSV to that of the planar interconnects

26 26 Outline Motivation Existing PUF Design Process Variation and Entropy for PUFs SuperPUF Architecture Design Automation Generalizing SuperPUF Extending to 3D Empirical Validation Conclusions

27 27 RCM-LK vs Greedy Algorithms implemented in C++ and compiled with g++ 4.7 on a Linux system Accurate circuit simulation performed by 500x Monte Carlo runs of ngSPICE- 25 to model process variation Benchmarked algorithmic approaches using clock networks from ISPD 2010

28 28 RCM-LK vs Greedy RCM-LK performs poorly compared to Greedy; LK links entropy sources effectively, but RCM selects sources poorly Greedy optimizes for entropy and wire-length simultaneously, and so bits/mm is maximised Discrete entropy is expressed in bits. Wire length is expressed in millimeters.

29 29 Empirical Validation Impact of spatial correlation and distance between sources affect entropy on RO-based SuperPUF:

30 30 Outline Motivation Existing PUF Design Process Variation and Entropy for PUFs SuperPUF Architecture Design Automation Generalizing SuperPUF Extending to 3D Empirical Validation Conclusions

31 31 Our Work: Anticipates the potential integration of multiple PUFs from reusable IP blocks and new entropy sources; increasingly likely with 3D ICs Differs from previous research in its empirical entropy calculations Employs simulation based validation; test chip validation is impractical Acknowledgment. This work was partially supported by the NSF Award 1162087. Conclusions

32 Thank you!


Download ppt "SuperPUF : Integrating Heterogeneous Physically Unclonable Functions Michael Wang, Andrew Yates, Igor L. Markov."

Similar presentations


Ads by Google