cryptography and copy protection

Cryptography and copy protection

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Unformatted text preview: the code! 33 Rennes presentation Example: DES DPA Signal Round 1 Round 2 Round 3 DPA Signal KcW N = 300 100 MS/s PCW average 34 Rennes presentation Same DES DPA Signal - Zoom DPA Signal KcW PCW average Target Bit = 17 (S5) S-BOX DPA Signal 20 17 18 19 PPerm DPA Signal N = 300 100 MS/s S8 S7 S6 S5 S4 S3 S2 S1 35 Rennes presentation Reverse engineering the code Round 1 Round 2 XOR Exch RL EPerm SBOX Round 3 XOR Exch RL DPA Signal KcW N = 300 100 MS/s PCW average 36 Rennes presentation Brief Platform Description Oscilloscope file transfer Arm scope retrieve file Scope trigger on IO Current waveform acquisition Server stores files and runs Treatment software Main PC runs Acquisition software R GCR Card extention command emission Card reader Protection box 37 Rennes presentation A popular protection against DPA s Curve desynchronization smears DPA peaks s Huge number of raw curves required (50000) to do a DPA 38 Rennes presentation The Problem (as seen by the bad guy) Desynchronization sources can be discrete or continuous : • quantum binomial random events (dummy cycles = DS) • voluntary unstable continuous clock drifts Can we get rid of their impact ? • Restore the true DPA peaks in a rigorous mathematical way • Reduce the number of acquisitions Mathematically : • Central-limit theorem è DS add-up to a normal law • The desynchronization’s effect is a convolution product : measured-DPA-peaks = true-DPA-peaks«G(T,σ) ò X(t)=a Xtrue (t-τ)× Exp[-(τ-T)2/ (2σ 2)] dτ 39 Rennes presentation A look at the scope (unstable clock drift) Desynchronized Synchronized 1 GS/s 40 Rennes presentation Related tools and problems in physics s How to repair a blurred image? x As frustrating as it seems, the useful data necessary to repair a blurred image is already in the image. x Photons were simply “mixed-up” and sent to the wrong places. s Question: If the blurring function K is known (say the exact non voluntary movement of the photographer) can we still restore the image? 41 Rennes presentation A few (spectacular) examples function K = blurred image = = deconvolved images (Richardson-Lu...
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This note was uploaded on 10/18/2010 for the course MATH CS 301 taught by Professor Aliulger during the Fall '10 term at Koç University.

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