From the reviews of the first edition: "It is certainly no exaggeration to say that A Singular Introduction to Commutative Algebra aims to lead a further stage in the computational revolution in commutative algebra . Among the great strengths and most distinctive features is a new, completely unified treatment of the global and local theories. making it one of the most flexible and most efficient systems of its type....another strength of Greuel and Pfister's book is its breadth of coverage of theoretical topics in the portions of commutative algebra closest to algebraic geometry, with algorithmic treatments of almost every topic....Greuel and Pfister have written a distinctive and highly useful book that should be in the library of every commutative algebraist and algebraic geometer, expert and novice alike." J.B. Little, MAA, March 2004 The second edition is substantially enlarged by a chapter on Groebner bases in non-commtative rings, a chapter on characteristic and triangular sets with applications to primary decomposition and polynomial solving and an appendix on polynomial factorization including factorization over algebraic field extensions and absolute factorization, in the uni- and multivariate case.

A Singular Introduction to Commutative Algebra

Table of basic properties Notation and basic definitions Preface 1. What is the integral closure 2. Integral closure of rings 3. Separability 4. Noetherian rings 5. Rees algebras 6. Valuations 7. Derivations 8. Reductions 9. Analytically unramified rings 10. Rees valuations 11. Multiplicity and integral closure 12. The conductor 13. The Briancon-Skoda theorem 14. Two-dimensional regular local rings 15. Computing the integral closure 16. Integral dependence of modules 17. Joint reductions 18. Adjoints of ideals 19. Normal homomorphisms Appendix A. Some background material Appendix B. Height and dimension formulas References Index.

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Integral closure of ideals, rings, and modules

To appear as a chapter of the volume " Boolean Methods and Models " ,

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Vectorial Boolean Functions for Cryptography

This ACM volume deals with tackling problems that can be represented by data structures which are essentially matrices with polynomial entries, mediated by the disciplines of commutative algebra and algebraic geometry. The discoveries stem from an interdisciplinary branch of research which has been growing steadily over the past decade. The author covers a wide range, from showing how to obtain deep heuristics in a computation of a ring, a module or a morphism, to developing means of solving nonlinear systems of equations - highlighting the use of advanced techniques to bring down the cost of computation. Although intended for advanced students and researchers with interests both in algebra and computation, many parts may be read by anyone with a basic abstract algebra course.

Computational methods in commutative algebra and algebraic geometry

Twofish is a 128-bit block cipher that accepts a variable-length key up to 256 bits. The cipher is a 16-round Feistel network with a bijective F function made up of four key-dependent 8-by-8-bit S-boxes, a fixed 4-by-4 maximum distance separable matrix over GF(2), a pseudo-Hadamard transform, bitwise rotations, and a carefully designed key schedule. A fully optimized implementation of Twofish encrypts on a Pentium Pro at 17.8 clock cycles per byte, and an 8-bit smart card implementation encrypts at 1660 clock cycles per byte. Twofish can be implemented in hardware in 14000 gates. The design of both the round function and the key schedule permits a wide variety of tradeoffs between speed, software size, key setup time, gate count, and memory. We have extensively cryptanalyzed Twofish; our best attack breaks 5 rounds with 2 chosen plaintexts and 2 effort.

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Twofish : A 128-bit block cipher

Since the proposal of differential cryptanalysis and linear cryptanalysis in 1991 and 1993, respectively, the resistance to these cryptanalysis has been studied. In FSE2, Knudsen proposed a method of attacking block ciphers that used the higher order differential, and in FSE4, Jakobsen and Knudsen applied it to a cipher proposed by Nyberg and Knudsen. Their approach, however, requires large complexity of running time. In this paper, we improve this attack and show that our improved algorithm requires much fewer chosen texts and much less complexity than those of previous works. key words: block cipher, higher order differential attack, KN cipher, algebraic equation

Improved Higher Order Differential Attack and Its Application to Nyberg-Knudsen's Designed Block Cipher

In 2009, Gentry first proposed a concrete method for constructing a fully homomorphic encryption FHE scheme, which supports arbitrary operations on encrypted data. The construction of the FHE scheme starts from a somewhat homomorphic encryption SHE scheme, which only supports limited operations but can be much faster than the FHE scheme. The Gentry's scheme is based on ideal lattices, and Chen and Nguyen estimated that it needs at least 10,000 lattice dimension to make the FHE scheme secure. In contrast, the security of the SHE scheme can be guaranteed for lower lattice dimensions, depending on the possible operations which are determined by key parameters. The aim of this paper is to classify which key parameters are feasible to be solved. We attack the lattice problem of lower dimensions by practical lattice reduction algorithms, and estimate the key parameters which can be solved in practice.

Analysis of Lattice Reduction Attack against the Somewhat Homomorphic Encryption Based on Ideal Lattices

The low-density attack proposed by Lagarias and Odlyzko is a powerful algorithm against the subset sum problem. The improvement algorithm due to Coster et al. would solve almost all the problems of density < 0.9408... in the asymptotical sense. On the other hand, the subset sum problem itself is known as an NP-hard problem, and a lot of efforts have been paid to establish public-key cryptosystems based on the problem. In these cryptosystems, densities of the subset sum problems should be higher than 0.9408... in order to avoid the low-density attack. For example, the Chor-Rivest cryptosystem adopted subset sum problems with relatively high densities. In this paper, we further improve the low-density attack by incorporating an idea that integral lattice points can be covered with polynomially many spheres of shorter radius and of lower dimension. As a result, the success probability of our attack can be higher than that of Coster et al.’s attack for fixed dimensions. The density bound is also improved for fixed dimensions. Moreover, we numerically show that our improved low-density attack makes the success probability higher in case of low Hamming weight solution, such as the Chor-Rivest cryptosystem, if we assume SVP oracle calls.

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Low-Density Attack Revisited.

The RSA cryptosystem and elliptic curve cryptography (ECC) have been used practically and widely in public key cryptography. The security of RSA and ECC respectively relies on the computational hardness of the integer factorization problem (IFP) and the elliptic curve discrete logarithm problem (ECDLP). In this paper, we give an estimate of computing power required to solve each problem by state-of-the-art of theory and experiments. By comparing computing power required to solve the IFP and the ECDLP, we also estimate bit sizes of the two problems that can provide the same security level.

Computational hardness of IFP and ECDLP

An encrypted first polynomial that is obtained by encrypting, in a homomorphic encryption method that handles a polynomial processing, a first polynomial, is received from another computer. The first polynomial is represented by using, as coefficients, components of a first binary vector generated from first data in first order that is either ascending order or descending order with respect to degree of the first polynomial. Then, a predetermined processing in an encrypted text space is performed by using the encrypted first polynomial and an encrypted second polynomial that is obtained by encrypting a second polynomial in the homomorphic encryption method. The second polynomial is represented by using, as coefficients, components of a second binary vector generated from second data in second order that is different from the first order with respect to degree of the second polynomial. Then, a result of the predetermined processing is sent back.

Takeshi Shimoyama

Papers

Improved Higher Order Differential Attack and Its Application to Nyberg-Knudsen's Designed Block Cipher

Analysis of Lattice Reduction Attack against the Somewhat Homomorphic Encryption Based on Ideal Lattices

Low-Density Attack Revisited.

Computational hardness of IFP and ECDLP

Information processing technique for secure pattern matching