DocumentCode
3368530
Title
The Improvement of the Commonly Used Linear Polynomial Selection Methods
Author
Hao Zhu ; Shenghui Su
Author_Institution
Coll. of Comput. Sci., Beijing Univ. of Technol., Beijing, China
fYear
2013
fDate
14-15 Dec. 2013
Firstpage
459
Lastpage
463
Abstract
The general number field sieve (GNFS) is asymptotically the fastest algorithm known for factoring large integers. One of the most important steps of GNFS is to select a good polynomial pair. Whether we can select a good polynomial pair, directly affects the efficiency of the sieving step. Now there are three linear methods widely used which base-m method, Murphy method and Klein Jung method. Base-m method is to construct polynomial based on the m-expansion of the integer, Murphy method mainly focuses on the root property of the polynomial and Klein Jung method restricts the first three coefficients size of the polynomial in a certain range. In this paper, we compare the size property and root property of the polynomials which select from the three methods. A good leading coefficient ad of f1 is important. The good means that ad has some small prime divisors. Klein Jung method does not give a concrete method to choose a good ad in its first step. We choose these better ad first and store in a set Ad, then take the Ad as input. Through the pretreatment we can get better polynomial and speed up the efficiency of Klein Jung method at the same time.
Keywords
number theory; polynomials; GNFS; Kleinjung method; Murphy method; base-m method; factoring; general number field sieve; integers; leading coefficient; linear methods; linear polynomial selection methods; m-expansion; prime divisors; root property; sieving step; Algorithm design and analysis; Concrete; Educational institutions; Encryption; Polynomials; Kleinjung method; general number field sieve; leading coefficient; polynomial selection;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Security (CIS), 2013 9th International Conference on
Conference_Location
Leshan
Print_ISBN
978-1-4799-2548-3
Type
conf
DOI
10.1109/CIS.2013.103
Filename
6746439
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