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ic:laboratoare:07 [2016/11/16 20:04] marios.choudary |
ic:laboratoare:07 [2018/11/05 14:25] (current) dan.dragan |
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| - Obtain a large number (thousands) of leakage samples for that target, when processing different plaintexts | - Obtain a large number (thousands) of leakage samples for that target, when processing different plaintexts | ||
| - Choose a suitable leakage model (usually the hamming weight of the target value) | - Choose a suitable leakage model (usually the hamming weight of the target value) | ||
| - | - For each possible key candidate (e.g. all values from 0 to 255), compute [[http://en.wikipedia.org/wiki/Pearson_product-moment_correlation_coefficient | Person's correlation coefficient]] between the leakage model estimate for that key candidate and the leakage traces. | + | - For each possible key candidate (e.g. all values from 0 to 255), compute [[http://en.wikipedia.org/wiki/Pearson_product-moment_correlation_coefficient | Pearson's correlation coefficient]] between the leakage model estimate for that key candidate and the leakage traces. |
| - Decide for the key that gives maximum correlation | - Decide for the key that gives maximum correlation | ||
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| Compute the success rate (SR) for different amounts of leakage traces (e.g. $N \in \{10, 20, 50, 100, 200, 500, 1000\}$) and then plot the SR as a function of N. | Compute the success rate (SR) for different amounts of leakage traces (e.g. $N \in \{10, 20, 50, 100, 200, 500, 1000\}$) and then plot the SR as a function of N. | ||
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