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Algorithms for solving linear and po...
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Bard, Gregory V.
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Algorithms for solving linear and polynomial systems of equations over finite fields, with applications to cryptanalysis.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Algorithms for solving linear and polynomial systems of equations over finite fields, with applications to cryptanalysis./
作者:
Bard, Gregory V.
面頁冊數:
200 p.
附註:
Adviser: Lawrence C. Washington.
Contained By:
Dissertation Abstracts International68-08B.
標題:
Computer Science. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3277391
ISBN:
9780549159858
Algorithms for solving linear and polynomial systems of equations over finite fields, with applications to cryptanalysis.
Bard, Gregory V.
Algorithms for solving linear and polynomial systems of equations over finite fields, with applications to cryptanalysis.
- 200 p.
Adviser: Lawrence C. Washington.
Thesis (Ph.D.)--University of Maryland, College Park, 2007.
This dissertation contains algorithms for solving linear and polynomial systems of equations over GF (2). The objective is to provide fast and exact tools for algebraic cryptanalysis and other applications. Accordingly, it is divided into two parts.
ISBN: 9780549159858Subjects--Topical Terms:
626642
Computer Science.
Algorithms for solving linear and polynomial systems of equations over finite fields, with applications to cryptanalysis.
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This dissertation contains algorithms for solving linear and polynomial systems of equations over GF (2). The objective is to provide fast and exact tools for algebraic cryptanalysis and other applications. Accordingly, it is divided into two parts.
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The first part deals with polynomial systems. Chapter 2 contains a successful cryptanalysis of Keeloq, the block cipher used in nearly all luxury automobiles. The attack is more than 16,000 times faster than brute force, but queries 0.62 x 232 plaintexts. The polynomial systems of equations arising from that cryptanalysis were solved via SAT-solvers. Therefore, Chapter 3 introduces a new method of solving polynomial systems of equations by converting them into CNF-SAT problems and using a SAT-solver. Finally, Chapter 4 contains a discussion on how SAT-solvers work internally.
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The second part deals with linear systems over GF (2), and other small fields (and rings). These occur in cryptanalysis when using the XL algorithm, which converts polynomial systems into larger linear systems. We introduce a new complexity model and data structures for GF (2)-matrix operations. This is discussed in Appendix B but applies to all of Part II. Chapter 5 contains an analysis of "the Method of Four Russians" for multiplication and a variant for matrix inversion, which is log n faster than Gaussian Elimination, and can be combined with Strassen-like algorithms. Chapter 6 contains an algorithm for accelerating matrix multiplication over small finite fields. It is feasible but the memory cost is so high that it is mostly of theoretical interest. Appendix A contains some discussion of GF (2)-linear algebra and how it differs from linear algebra in R and C . Appendix C discusses algorithms faster than Strassen's algorithm, and contains proofs that matrix multiplication, matrix squaring, triangular matrix inversion, LUP-factorization, general matrix inversion and the taking of determinants, are equicomplex. These proofs are already known, but are here gathered into one place in the same notation.
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