# Lecture 4 ## Recap Negligible function $\epsilon(n)$ if $\forall c>0,\exist N$ such that $n>N$, $\epsilon (n)<\frac{1}{n^c}$ Example: $\epsilon(n)=2^{-n},\epsilon(n)=\frac{1}{n^{\log (\log n)}}$ ## Chapter 2: Computational Hardness ### One-way function #### Strong One-Way Function 1. $\exists$ a P.P.T. that computes $f(x),\forall x\in\{0,1\}^n$ 2. $\forall \mathcal{A}$ adversaries, $\exists \epsilon(n),\forall n$. $$ P[x\gets \{0,1\}^n;y=f(x):f(\mathcal{A}(y,1^n))=y]<\epsilon(n) $$ _That is, the probability of success guessing should decreasing (exponentially) as encrypted message increase (linearly)..._ To negate statement 2: $$ P[x\gets \{0,1\}^n;y=f(x):f(\mathcal{A}(y,1^n))=y]=\mu(n) $$ is a negligible function. Negation: $\exists \mathcal{A}$, $P[x\gets \{0,1\}^n;y=f(x):f(\mathcal{A}(y,1^n))=y]=\mu(n)$ is not a negligible function. That is, $\exists c>0,\forall N \exists n>N \epsilon(n)>\frac{1}{n^c}$ $\mu(n)>\frac{1}{n^c}$ for infinitely many $n$. or infinitely often. > Keep in mind: $P[success]=\frac{1}{n^c}$, it can try $O(n^c)$ times and have a good chance of succeeding at least once. #### Definition 28.4 (Weak one-way function) $f:\{0,1\}^n\to \{0,1\}^*$ 1. $\exists$ a P.P.T. that computes $f(x),\forall x\in\{0,1\}^n$ 2. $\forall \mathcal{A}$ adversaries, $\exists \epsilon(n),\forall n$. $$ P[x\gets \{0,1\}^n;y=f(x):f(\mathcal{A}(y,1^n))=y]<1-\frac{1}{p(n)} $$ _The probability of success should not be too close to 1_ ### Probability #### Useful bound $0