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암호해독을 위한 소인수분해

Integer Factorization for Decryption

  • 이상운 (강릉원주대학교 멀티미디어공학과) ;
  • 최명복 (강릉원주대학교 멀티미디어공학과)
  • Lee, Sang-Un (Dept. of Multimedia Eng., Gangneung-Wonju National University) ;
  • Choi, Myeong-Bok (Dept. of Multimedia Eng., Gangneung-Wonju National University)
  • 투고 : 2013.04.19
  • 심사 : 2013.12.13
  • 발행 : 2013.12.31

초록

큰 반소수 n=pq의 소인수 p,q를 나눗셈 시행법으로 직접 찾는 것은 현실적으로 거의 불가능하다. 따라서 대부분의 소인수분해 알고리즘은$a^2{\equiv}b^2$ (mod n)의 제곱합동을 찾아 p=GCD(a-b, n), q=GCD(a+b, n)의 소인수를 찾는 간접 방법을 적용하고 있다. n = pq에 대해 p와 q를 선택한 영역은 $l(p)=l(q)=l(\sqrt{n})=0.5l(n)$의 [$10{\cdots}01$, $99{\cdots}9$] 범위에서 $\sqrt{n}$을 기준으로 $10{\cdots}00$ < p < $\sqrt{n}$$\sqrt{n}$ < q < $99{\cdots}9$에 존재한다는 사실만이 밝혀졌다. 본 논문은 n으로 부터 획득한 정보를 이용하여 p의 범위를 보다 축소시키는 방법을 제안한다. 제안 방법은 $n=n_{LR}+n_{RL}$, $l(n_{LR})=l(n_{RL})=l(\sqrt{n})$으로 분할하여 $p_{min}=n_{LR}$, $q_{min}=n_{RL}$로 설정하는 방법을 적용하였다. 본 논문에서 제안한 n의 정보로 p의 범위를 축소하는 방법은 $\sqrt{n}$의 정보로 p의 범위 축소 방법에 비해 최소 17.79%에서 최대 90.17%의 범위 축소 효과를 얻었다.

It is impossible directly to find a prime number p,q of a large semiprime n = pq using Trial Division method. So the most of the factorization algorithms use the indirection method which finds a prime number of p = GCD(a-b, n), q=GCD(a+b, n); get with a congruence of squares of $a^2{\equiv}b^2$ (mod n). It is just known the fact which the area that selects p and q about n=pq is between $10{\cdots}00$ < p < $\sqrt{n}$ and $\sqrt{n}$ < q < $99{\cdots}9$ based on $\sqrt{n}$ in the range, [$10{\cdots}01$, $99{\cdots}9$] of $l(p)=l(q)=l(\sqrt{n})=0.5l(n)$. This paper proposes the method that reduces the range of p using information obtained from n. The proposed method uses the method that sets to $p_{min}=n_{LR}$, $q_{min}=n_{RL}$; divide into $n=n_{LR}+n_{RL}$, $l(n_{LR})=l(n_{RL})=l(\sqrt{n})$. The proposed method is more effective from minimum 17.79% to maxmimum 90.17% than the method that reduces using $\sqrt{n}$ information.

키워드

참고문헌

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피인용 문헌

  1. Generalized Divisibility Rule of Natural Number m vol.14, pp.5, 2014, https://doi.org/10.7236/JIIBC.2014.14.5.87