Location:
Search - PRNG
Search list
Description: 应用密码学的应用，实现密码算法，用C语言实现。-application of cryptography applications, password algorithm, using C language.
Platform: |
Size: 11362 |
Author: 成名 |
Hits:
Description: PGP的安全
■内容提要■
◎ 前言
◎ IDEA 的安全性问题
◎ RSA 的安全性问题
● 选择密文攻击
● 过小的加密指数 e
● RSA的计时攻击法
● 其他对RSA的攻击法
◎ MD5 的安全性问题
● 对MD5的普通直接攻击
● 对MD5的生日攻击
● 其他对MD5的攻击
● 口令长度和信息论
◎ 随机数的安全性问题
● ANSI X9.17 PRNG
● 用户击键引入随机性
● X9.17 用MD5进行预洗
● randseed.bin 的后洗操作
Platform: |
Size: 14457 |
Author: nicmaters |
Hits:
Description: 应用密码学的应用，实现密码算法，用C语言实现。-application of cryptography applications, password algorithm, using C language.
Platform: |
Size: 11264 |
Author: |
Hits:
Description: PGP的安全
■内容提要■
◎ 前言
◎ IDEA 的安全性问题
◎ RSA 的安全性问题
● 选择密文攻击
● 过小的加密指数 e
● RSA的计时攻击法
● 其他对RSA的攻击法
◎ MD5 的安全性问题
● 对MD5的普通直接攻击
● 对MD5的生日攻击
● 其他对MD5的攻击
● 口令长度和信息论
◎ 随机数的安全性问题
● ANSI X9.17 PRNG
● 用户击键引入随机性
● X9.17 用MD5进行预洗
● randseed.bin 的后洗操作
-PGP security Summary ■ ■ ◎ ◎ IDEA foreword security issue ◎ RSA security issue chosen ciphertext attack ● ● too small e ● RSA encryption index of the timing attack ● Other attacks on the RSA method ◎ MD5 security ● MD5 issues common to a direct attack on the MD5 ● ● birthday attack other attacks on the MD5 password length and information theory ● ◎ random number of security issues ● ANSI X9.17 PRNG ● user keystrokes to introduce randomness ● X9.17 MD5 pre-washed with ● randseed.bin post-wash operation
Platform: |
Size: 14336 |
Author: nicmaters |
Hits:
Description: thie document give the three different design for generating a random number
Platform: |
Size: 13312 |
Author: Jiajie Cen |
Hits:
Description: this the PRNG routine for the prime field and large numbers for ECC or RSA algorithms. with IAR version 5 or above.-this is the PRNG routine for the prime field and large numbers for ECC or RSA algorithms. with IAR version 5 or above.
Platform: |
Size: 12288 |
Author: majid |
Hits:
Description: TestU01随机测试套件TestU01 provides a general and extensive library for statistical testing of PRNGs. -TestU01 provides a general and extensive library for statistical testing of PRNGs.
It implements a larger variety of tests than any other test-suites like DIEHARD , NIST
etc. In fact TestU01 is chosen as it is
the most comprehensive test suite available and
it encompasses most of the other public domain
tests.
Thus, the proposed PRNG is tested using
TestU01 for its statistical pseudorandomness.
Platform: |
Size: 3229696 |
Author: zhaoxue |
Hits:
Description: AMPRNG rev 1.0 - strong and fast PRNG with 80-512 bit key and 80-512 bit IV, based on permutations and one-way functions.
Platform: |
Size: 7168 |
Author: Alexander Myasnikov |
Hits:
Description: A new fast stream cipher, MAJE4 is designed and
developed with a variable key size of 128-bit or 256-bit. The
randomness property of the stream cipher is analysed by using
the statistical tests. The performance evaluation of the stream
cipher is done in comparison with another fast stream cipher
called JEROBOAM. The focus is to generate a long
unpredictable key stream with better performance, which can
be used for cryptographic applications.
Keywords- cryptography, stream cipher, pseudo random
number generator (PRNG)
Platform: |
Size: 1374208 |
Author: 陳曉慧 |
Hits:
Description: portable way to get secure random bits to feed a PRNG (Tom St Denis).
Platform: |
Size: 2048 |
Author: qiebuira |
Hits:
Description: A secure PRNG using the RNG functions. Basically this is a wrapper that allows you to use a secure RNG as a PRNG in the various other functions.
Platform: |
Size: 1024 |
Author: qinzangzei |
Hits:
Description: 基于FPGA伪随机序列产生器，GOLLMANN级联F-FCSR，产生伪随机序列-FPGA-based pseudo-random sequence generator, GOLLMANN cascade F-FCSR, generating pseudo-random sequence
Platform: |
Size: 2048 |
Author: 李辛 |
Hits:
Description: 采用线性同余法的素数模乘同余发生器产生随机数,采用5级流水线设计-Using a linear congruential method prime modulus multiplicative congruential random number generator, using five pipeline design
Platform: |
Size: 2048 |
Author: pyc |
Hits:
Description: Pseudo Random Number Generator Based on NIST Recommended PRNG From ANSI X9.31 Appendix A.2.4 using AES 128 cipher for Linux.
Platform: |
Size: 4096 |
Author: delepeng |
Hits:
Description: creates new seeds Source Code for Linux.
Platform: |
Size: 1024 |
Author: fernengxiu |
Hits:
Description: First it creates new seeds the previous seeds. Then it generates a new pseudo random number for use.
-First it creates new seeds the previous seeds. Then it generates a new pseudo random number for use.
Platform: |
Size: 2048 |
Author: kaivonkao |
Hits:
Description: An MCS like lock especially tailored for optimistic spinning for sleeping lock implementations (mutex, rwsem, etc).
Platform: |
Size: 2048 |
Author: jnzunxie |
Hits:
Description: single, global prng structure.
Platform: |
Size: 3072 |
Author: crqentj |
Hits:
Description: A pseudorandom number generator (PRNG), also known as a deterministic random bit generator (DRBG),[1] is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers. The PRNG-generated sequence is not truly random, because it is completely determined by a relatively small set of initial values, called the PRNG s seed (which may include truly random values). Although sequences that are closer to truly random can be generated using hardware random number generators, pseudorandom number generators are important in practice for their speed in number generation and their reproducibility.[2]
PRNGs are central in applications such as simulations (e.g. for the Monte Carlo method), electronic games (e.g. for procedural generation), and cryptography. Cryptographic applications require the output not to be predictable earlier outputs, and more elaborate algorithms, which do not inherit the linearity of simpler PRNGs, are needed.-A pseudorandom number generator (PRNG), also known as a deterministic random bit generator (DRBG),[1] is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers. The PRNG-generated sequence is not truly random, because it is completely determined by a relatively small set of initial values, called the PRNG s seed (which may include truly random values). Although sequences that are closer to truly random can be generated using hardware random number generators, pseudorandom number generators are important in practice for their speed in number generation and their reproducibility.[2]
PRNGs are central in applications such as simulations (e.g. for the Monte Carlo method), electronic games (e.g. for procedural generation), and cryptography. Cryptographic applications require the output not to be predictable earlier outputs, and more elaborate algorithms, which do not inherit the linearity of simpler PRNGs, are needed.
Platform: |
Size: 9216 |
Author: rajendra |
Hits:
Description: Tool for doing analysis on the Armadillo PRNG.
Platform: |
Size: 15360 |
Author: mrexodia |
Hits: