A pseudorandom number generator (PRNG), also known as a deterministic random bit generator (DRBG), 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 an initial value, called the PRNG's seed. 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.
A stream cipher is a symmetric key cipher where plaintext digits are combined with a pseudorandom cipher digit stream (keystream). In a stream cipher, each plaintext digit is encrypted one at a time with the corresponding digit of the keystream, to give a digit of the ciphertext stream. Since encryption of each digit is dependent on the current state of the cipher, it is also known as state cipher. In practice, a digit is typically a bit and the combining operation is an exclusive-or (XOR).
The Yarrow algorithm is a family of cryptographic pseudorandom number generators (CSPRNG) devised by John Kelsey, Bruce Schneier, and Niels Ferguson and published in 1999. The Yarrow algorithm is explicitly unpatented, royalty-free, and open source; no license is required to use it. An improved design from Ferguson and Schneier, Fortuna, is described in their book, Practical Cryptography
In cryptography, a block cipher mode of operation is an algorithm that uses a block cipher to provide information security such as confidentiality or authenticity. A block cipher by itself is only suitable for the secure cryptographic transformation of one fixed-length group of bits called a block. A mode of operation describes how to repeatedly apply a cipher's single-block operation to securely transform amounts of data larger than a block.
In computing, a hardware random number generator (HRNG), true random number generator (TRNG), non-deterministic random bit generator (NRBG), or physical random number generator is a device that generates random numbers from a physical process capable of producing entropy, unlike the pseudorandom number generator that utilizes a deterministic algorithm and non-physical nondeterministic random bit generators that do not include hardware dedicated to generation of entropy.
A cryptographically secure pseudorandom number generator (CSPRNG) or cryptographic pseudorandom number generator (CPRNG) is a pseudorandom number generator (PRNG) with properties that make it suitable for use in cryptography. It is also loosely known as a cryptographic random number generator (CRNG).
Niels T. Ferguson is a Dutch cryptographer and consultant who currently works for Microsoft. He has worked with others, including Bruce Schneier, designing cryptographic algorithms, testing algorithms and protocols, and writing papers and books. Among the designs Ferguson has contributed to is the AES finalist block cipher algorithm Twofish as well as the stream cipher Helix and the Skein hash function.
A cryptographic hash function (CHF) is a hash algorithm that has special properties desirable for a cryptographic application:
In Unix-like operating systems, /dev/random and /dev/urandom are special files that serve as cryptographically secure pseudorandom number generators (CSPRNGs). They allow access to a CSPRNG that is seeded with entropy from environmental noise, collected from device drivers and other sources. /dev/random typically blocks if there was less entropy available than requested; more recently it usually blocks at startup until sufficient entropy has been gathered, then unblocks permanently. The /dev/urandom device typically was never a blocking device, even if the pseudorandom number generator seed was not fully initialized with entropy since boot. Not all operating systems implement the same methods for /dev/random and /dev/urandom.
In cryptography, nothing-up-my-sleeve numbers are any numbers which, by their construction, are above suspicion of hidden properties. They are used in creating cryptographic functions such as hashes and ciphers. These algorithms often need randomized constants for mixing or initialization purposes. The cryptographer may wish to pick these values in a way that demonstrates the constants were not selected for a nefarious purpose, for example, to create a backdoor to the algorithm. These fears can be allayed by using numbers created in a way that leaves little room for adjustment. An example would be the use of initial digits from the number π as the constants. Using digits of π millions of places after the decimal point would not be considered trustworthy because the algorithm designer might have selected that starting point because it created a secret weakness the designer could later exploit.
The security of cryptographic systems depends on some secret data that is known to authorized persons but unknown and unpredictable to others. To achieve this unpredictability, some randomization is typically employed. Modern cryptographic protocols often require frequent generation of random quantities. Cryptographic attacks that subvert or exploit weaknesses in this process are known as random number generator attacks.
Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols that cannot be reasonably predicted better than by random chance is generated. This means that the particular outcome sequence will contain some patterns detectable in hindsight but impossible to foresee. True random number generators can be hardware random-number generators (HRNGs), wherein each generation is a function of the current value of a physical environment's attribute that is constantly changing in a manner that is practically impossible to model. This would be in contrast to so-called "random number generations" done by pseudorandom number generators (PRNGs), which generate numbers that only look random but are in fact pre-determined—these generations can be reproduced simply by knowing the state of the PRNG.
The Microsoft Windows platform specific Cryptographic Application Programming Interface is an application programming interface included with Microsoft Windows operating systems that provides services to enable developers to secure Windows-based applications using cryptography. It is a set of dynamically linked libraries that provides an abstraction layer which isolates programmers from the code used to encrypt the data. The Crypto API was first introduced in Windows NT 4.0 and enhanced in subsequent versions.
CryptGenRandom is a deprecated cryptographically secure pseudorandom number generator function that is included in Microsoft CryptoAPI. In Win32 programs, Microsoft recommends its use anywhere random number generation is needed. A 2007 paper from Hebrew University suggested security problems in the Windows 2000 implementation of CryptGenRandom. Microsoft later acknowledged that the same problems exist in Windows XP, but not in Vista. Microsoft released a fix for the bug with Windows XP Service Pack 3 in mid-2008.
GBDE, standing for GEOM Based Disk Encryption, is a block device-layer disk encryption system written for FreeBSD, initially introduced in version 5.0. It is based on the GEOM disk framework. GBDE was designed and implemented by Poul-Henning Kamp and Network Associates Inc..
The following outline is provided as an overview of and topical guide to cryptography:
In cryptography, a sponge function or sponge construction is any of a class of algorithms with finite internal state that take an input bit stream of any length and produce an output bit stream of any desired length. Sponge functions have both theoretical and practical uses. They can be used to model or implement many cryptographic primitives, including cryptographic hashes, message authentication codes, mask generation functions, stream ciphers, pseudo-random number generators, and authenticated encryption.
NIST SP 800-90A is a publication by the National Institute of Standards and Technology with the title Recommendation for Random Number Generation Using Deterministic Random Bit Generators. The publication contains the specification for three allegedly cryptographically secure pseudorandom number generators for use in cryptography: Hash DRBG, HMAC DRBG, and CTR DRBG. Earlier versions included a fourth generator, Dual_EC_DRBG. Dual_EC_DRBG was later reported to probably contain a kleptographic backdoor inserted by the United States National Security Agency (NSA).
A counter-based random number generation is a kind of pseudorandom number generator that uses only an integer counter as its internal state. They are generally used for generating pseudorandom numbers for large parallel computations.
