Random Key Generation In Cryptography
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Definition
I want to use encryption algorithm available in.Net Security namespace, however I am trying to understand how to generate the key, for example AES algorithm needs 256 bits, that 16 bytes key,.
Represents the abstract class from which all implementations of cryptographic random number generators derive.
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- Derived
- Attributes
- Implements
Remarks
Cryptographic random number generators create cryptographically strong random values.
To create a random number generator, call the Create() method. This is preferred over calling the constructor of the derived class RNGCryptoServiceProvider, which is not available on all platforms.
Constructors
| RandomNumberGenerator() | Initializes a new instance of RandomNumberGenerator. |
Methods
| Create() | Creates an instance of the default implementation of a cryptographic random number generator that can be used to generate random data. |
| Create(String) | Creates an instance of the specified implementation of a cryptographic random number generator. |
| Dispose() | When overridden in a derived class, releases all resources used by the current instance of the RandomNumberGenerator class. |
| Dispose(Boolean) | When overridden in a derived class, releases the unmanaged resources used by the RandomNumberGenerator and optionally releases the managed resources. |
| Equals(Object) | Determines whether the specified object is equal to the current object. (Inherited from Object) |
| Fill(Span<Byte>) | Fills a span with cryptographically strong random bytes. |
| GetBytes(Byte[]) | When overridden in a derived class, fills an array of bytes with a cryptographically strong random sequence of values. |
| GetBytes(Byte[], Int32, Int32) | Fills the specified byte array with a cryptographically strong random sequence of values. |
| GetBytes(Span<Byte>) | Fills a span with cryptographically strong random bytes. |
| GetHashCode() | Serves as the default hash function. (Inherited from Object) |
| GetInt32(Int32) | Generates a random integer between 0 (inclusive) and a specified exclusive upper bound using a cryptographically strong random number generator. |
| GetInt32(Int32, Int32) | Generates a random integer between a specified inclusive lower bound and a specified exclusive upper bound using a cryptographically strong random number generator. |
| GetNonZeroBytes(Byte[]) | When overridden in a derived class, fills an array of bytes with a cryptographically strong random sequence of nonzero values. |
| GetNonZeroBytes(Span<Byte>) | Fills a byte span with a cryptographically strong random sequence of nonzero values. |
| GetType() | Gets the Type of the current instance. (Inherited from Object) |
| MemberwiseClone() | Creates a shallow copy of the current Object. (Inherited from Object) |
| ToString() | Returns a string that represents the current object. (Inherited from Object) |
Applies to
See also
Key generation is the process of generating keys in cryptography. A key is used to encrypt and decrypt whatever data is being encrypted/decrypted.
A device or program used to generate keys is called a key generator or keygen.
Generation in cryptography[edit]
Modern cryptographic systems include symmetric-key algorithms (such as DES and AES) and public-key algorithms (such as RSA). Symmetric-key algorithms use a single shared key; keeping data secret requires keeping this key secret. Public-key algorithms use a public key and a private key. The public key is made available to anyone (often by means of a digital certificate). A sender encrypts data with the receiver's public key; only the holder of the private key can decrypt this data.
Since public-key algorithms tend to be much slower than symmetric-key algorithms, modern systems such as TLS and SSH use a combination of the two: one party receives the other's public key, and encrypts a small piece of data (either a symmetric key or some data used to generate it). The remainder of the conversation uses a (typically faster) symmetric-key algorithm for encryption.
Computer cryptography uses integers for keys. In some cases keys are randomly generated using a random number generator (RNG) or pseudorandom number generator (PRNG). A PRNG is a computeralgorithm that produces data that appears random under analysis. PRNGs that use system entropy to seed data generally produce better results, since this makes the initial conditions of the PRNG much more difficult for an attacker to guess. Another way to generate randomness is to utilize information outside the system. veracrypt (a disk encryption software) utilizes user mouse movements to generate unique seeds, in which users are encouraged to move their mouse sporadically. In other situations, the key is derived deterministically using a passphrase and a key derivation function.
Many modern protocols are designed to have forward secrecy, which requires generating a fresh new shared key for each session.
Classic cryptosystems invariably generate two identical keys at one end of the communication link and somehow transport one of the keys to the other end of the link.However, it simplifies key management to use Diffie–Hellman key exchange instead.
The simplest method to read encrypted data without actually decrypting it is a brute-force attack—simply attempting every number, up to the maximum length of the key. Therefore, it is important to use a sufficiently long key length; longer keys take exponentially longer to attack, rendering a brute-force attack impractical. Currently, key lengths of 128 bits (for symmetric key algorithms) and 2048 bits (for public-key algorithms) are common.
Generation in physical layer[edit]
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Wireless channels[edit]
A wireless channel is characterized by its two end users. By transmitting pilot signals, these two users can estimate the channel between them and use the channel information to generate a key which is secret only to them.[1] The common secret key for a group of users can be generated based on the channel of each pair of users.[2]
Random Key Generation Algorithm
Optical fiber[edit]
A key can also be generated by exploiting the phase fluctuation in a fiber link.[clarification needed]
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See also[edit]
Private Key Cryptography
- Distributed key generation: For some protocols, no party should be in the sole possession of the secret key. Rather, during distributed key generation, every party obtains a share of the key. A threshold of the participating parties need to cooperate to achieve a cryptographic task, such as decrypting a message.
References[edit]
- ^Chan Dai Truyen Thai; Jemin Lee; Tony Q. S. Quek (Feb 2016). 'Physical-Layer Secret Key Generation with Colluding Untrusted Relays'. IEEE Transactions on Wireless Communications. 15 (2): 1517–1530. doi:10.1109/TWC.2015.2491935.
- ^Chan Dai Truyen Thai; Jemin Lee; Tony Q. S. Quek (Dec 2015). 'Secret Group Key Generation in Physical Layer for Mesh Topology'. 2015 IEEE Global Communications Conference (GLOBECOM). San Diego. pp. 1–6. doi:10.1109/GLOCOM.2015.7417477.