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[Windows Develop] pittner-prng-cipher-3.c DL : 0: 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.
Date : 2008-10-13 Size : 11.1kb User : 成名
[Other] PGP DL : 0: 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
Date : 2008-10-13 Size : 14.12kb User : nicmaters
[Windows Develop] pittner-prng-cipher-3.c DL : 0: 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.
Date : 2025-07-01 Size : 11kb User :
[Other] PGP DL : 0: 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
Date : 2025-07-01 Size : 14kb User : nicmaters
[Applications] PRNG DL : 0: thie document give the three different design for generating a random number
Date : 2025-07-01 Size : 13kb User : Jiajie Cen
[Crack Hack] PRNG_Project DL : 0: 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.
Date : 2025-07-01 Size : 12kb User : majid
[Other] TestU01-1.2.4 DL : 0: 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.
Date : 2025-07-01 Size : 3.08mb User : zhaoxue
[Crack Hack] fprng10 DL : 0: 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.
Date : 2025-07-01 Size : 7kb User : Alexander Myasnikov
[Crack Hack] a-new-fast-stream-cipher--20110914 DL : 0: 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)
Date : 2025-07-01 Size : 1.31mb User : 陳曉慧
[Linux-Unix] rng_get_bytes DL : 0: portable way to get secure random bits to feed a PRNG (Tom St Denis).
Date : 2025-07-01 Size : 2kb User : qiebuira
[Linux-Unix] sprng DL : 0: 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.
Date : 2025-07-01 Size : 1kb User : qinzangzei
[Video Capture] PRNG DL : 0: 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
Date : 2025-07-01 Size : 2kb User : 李辛
[VHDL-FPGA-Verilog] prng DL : 0: 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
Date : 2025-07-01 Size : 2kb User : pyc
[Linux-Unix] elf_user DL : 0: Pseudo Random Number Generator Based on NIST Recommended PRNG From ANSI X9.31 Appendix A.2.4 using AES 128 cipher for Linux.
Date : 2025-07-01 Size : 4kb User : delepeng
[Linux-Unix] prng DL : 0: creates new seeds Source Code for Linux.
Date : 2025-07-01 Size : 1kb User : fernengxiu
[Linux-Unix] prng DL : 0: 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.
Date : 2025-07-01 Size : 2kb User : kaivonkao
[Linux-Unix] qcom-prng DL : 0: An MCS like lock especially tailored for optimistic spinning for sleeping lock implementations (mutex, rwsem, etc).
Date : 2025-07-01 Size : 2kb User : jnzunxie
[Linux-Unix] prng DL : 0: single, global prng structure.
Date : 2025-07-01 Size : 3kb User : crqentj
[matlab] MATLAB_CODE_TO_GENERATE_A_PSEUDO_NOISE_SEQUENCE.z DL : 0: 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.
Date : 2025-07-01 Size : 9kb User : rajendra
[Other] armabrut_alg2 DL : 0: Tool for doing analysis on the Armadillo PRNG.
Date : 2025-07-01 Size : 15kb User : mrexodia