Page |
Exact Location |
Text in the Book |
Text Should Be |
Reported by |

xviii |
Line 13 |
Φ(x) Probability density function of ... |
Φ(x) Cumulative distribution function of ... |
Thomas Popp |

65 |
Paragraph 3, Line 6 |
Hence, Var(Pdata) and Var(Pel.noise) ... |
Hence, Var(Pop) and Var(Pdata) ... |
Thomas Popp |

91 |
Paragraph 2, Line 3 |
... if only S is known ... the variable *T = (X_bar - μ) · sqrt(n) / S* is ... |
... if only s is known ... the variable *T = (X_bar - μ) · sqrt(n) / s* is ... |
Thomas Popp |

92 |
Second to last paragraph, Lines 6-8 |
Hence, we want to have that *p((X_bar - μ) · σ / sqrt(n) < -μ · σ / sqrt(n)) = 1 - α*. This allows deriving the number of traces *n*: *p((X_bar - μ) · σ / sqrt(n) < -μ · σ / sqrt(n)) = Φ(-μ · σ / sqrt(n)) = 1 - α*. |
Hence, we want to have that *p((X_bar - μ) · sqrt(n) / σ < -μ · sqrt(n) / σ) = 1 - α*. This allows deriving the number of traces *n*: *p((X_bar - μ) · sqrt(n) / σ < -μ · sqrt(n) / σ) = Φ(-μ · sqrt(n) / σ) = 1 - α*. |
Stefan Tillich |

93 |
Paragraph 3, Line 2 |
... with precision c = 0.01 is 176 306. |
... with precision c = 0.01mV is 176 306. |
Thomas Popp |

93 |
Paragraph 3, Line 3, Word 6 |
N(1.86,1.63) |
N(111.86,1.63) |
Stefan Tillich |

93 |
Paragraph 3, Line 3-4 |
... with confidence 0.99 is n = 4. |
... with confidence 0.99 is n = 1 (the actual value of n is 0.00115, however, it can only be a positive integer). This means that already one trace is more than enough to tell with very high confidence that the mean of the distribution is different from zero, i.e. the hypothesis μ_0 = 0 is already part of the critical region in this case with very high probability and is thus rejected. |
Yu Yu |

95 |
Paragraph 1, Line 2 |
(if not, we just switch X and Y). |
(if not, we just switch X_bar and Y_bar). |
Stefan Tillich |

95 |
Paragraph 1, Lines 3-5 |
We know that *p(Z < 0)* equals *Φ(-(μ_X - μ_Y) · sqrt(n) / (2 / sqrt(σ)))* and therefore we have *Φ(-(μ_X - μ_Y) · sqrt(n) / (2 / sqrt(σ))) = 1 - α*. |
We know that *p(Z < 0)* equals *Φ(-(μ_X - μ_Y) · sqrt(n) / (2 · σ))* and therefore we have *Φ(-(μ_X - μ_Y) · sqrt(n) / (2 · σ)) = 1 - α*. |
Stefan Tillich |

95 |
Lines 2/3 of "Important Box" |
... *X ~ N(μ_X, σ / sqrt(n/2))* and *Y ~ N(μ_Y, σ / sqrt(n/2))* ... |
... *X_bar ~ N(μ_X, σ / sqrt(n/2))* and *Y_bar ~ N(μ_Y, σ / sqrt(n/2))* ... |
Stefan Tillich |

95 |
Paragraph 4, Line 10 |
... confidence interval with c = 1, about n = 4823 traces would be ... |
... confidence interval with c = 1mV, about n = 2412 traces would be ... |
Thomas Popp |

95 |
Paragraph 5, Line 4 |
... we need n = 112 traces ... |
... we need n = 56 traces ... |
Thomas Popp |

148 |
Line 1 of "Important Box" |
For |ρ_{ck,ct} <= 0.2| and ... |
For |ρ_{ck,ct}| <= 0.2 and ... |
Thomas Popp |

168 |
"Important Box" at the bottom |
The power consumption a cryptographic device ... |
The power consumption of a cryptographic device ... |
Thomas Popp |

233 |
Paragraph 1, Lines 4-5 |
... (notice that this a random result) ... |
... (notice that this is a random result) ... |
Thomas Popp |

241 |
Paragraph 2, Line 5 |
... performed by the two SR AND cells, the two SR OR cells, and the ... |
... performed by the SR AND cell, the SR OR cell, and the ... |
Thomas Popp |

241 |
Paragraph 2, Line 8 |
It calculates as output *d_{m(t+1)} = d XOR m(t+1)* and its inverse. |
It calculates as output *d_{m(t+1)} = d XOR m(t+1)*. |
Thomas Popp |

249 |
Last paragraph, Line 6 |
... to recompute a the masked table ... |
... to recompute the masked table ... |
Thomas Popp |

252 |
Paragraph 3, Line 2, Word 7 |
ρ(H, tilde{T}) = ρ(HW(V XOR W), tilde{T}) |
ρ(H, tilde{T}) = ρ(HW(U XOR V), tilde{T}) |
Stefan Tillich |

252 |
Equation 10.2, at the end |
, HW(v_m)) |
, HW(v_m))) |
Stefan Tillich |

258 |
The three equations |
*comb(u, v) = - 89.95 · sin(HW(u XOR
v)^3) - - 7.82 · sin(HW(u XOR v)^2) + 67.66*
pre(HW(u_m), HW(v_m)) = sin(HW(u_m) - HW(v_m))^2
ρ(comb(u,v), pre(HW(u_m),HW(v_m))) = 0.83 |
*comb(u, v) = - 89.95 · sin(HW(u XOR
v))^3 - 7.82 · sin(HW(u XOR v))^2 + 67.66 · sin(HW(u XOR v))*
pre(HW(u_m), HW(v_m)) = sin((HW(u_m) - HW(v_m))^2)
ρ(comb(u,v), pre(HW(u_m),HW(v_m))) = 0.84 |
Stefan Tillich, Thomas Popp |

258 |
Paragraph 4, Line 6, Word 3 |
*u = HW((d_i XOR k_j)* |
*u = d_i XOR k_j* |
Stefan Tillich |