- java.lang.Object
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- io.github.mmm.crypto.CryptoConfig
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- io.github.mmm.crypto.algorithm.CryptoAlgorithmConfig
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- io.github.mmm.crypto.random.RandomConfig
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- All Implemented Interfaces:
CryptoAlgorithm
- Direct Known Subclasses:
RandomConfigSha1Prng
public class RandomConfig extends CryptoAlgorithmConfig
- Since:
- 1.0.0
- Author:
- Joerg Hohwiller (hohwille at users.sourceforge.net)
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Field Summary
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Fields inherited from class io.github.mmm.crypto.algorithm.CryptoAlgorithmConfig
algorithm
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Fields inherited from class io.github.mmm.crypto.CryptoConfig
provider
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Constructor Summary
Constructors Constructor Description RandomConfig(String algorithm)
The constructor.RandomConfig(String algorithm, int reseedCount)
The constructor.RandomConfig(String algorithm, int reseedCount, SecurityProvider provider)
The constructor.RandomConfig(String algorithm, SecurityProvider provider)
The constructor.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description int
getReseedCount()
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Methods inherited from class io.github.mmm.crypto.algorithm.CryptoAlgorithmConfig
getAlgorithm
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Methods inherited from class io.github.mmm.crypto.CryptoConfig
getProvider
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Constructor Detail
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RandomConfig
public RandomConfig(String algorithm)
The constructor.- Parameters:
algorithm
- thehash algorithm
.
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RandomConfig
public RandomConfig(String algorithm, int reseedCount)
The constructor.- Parameters:
algorithm
- thehash algorithm
.reseedCount
- there-seed count
.
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RandomConfig
public RandomConfig(String algorithm, SecurityProvider provider)
The constructor.- Parameters:
algorithm
- thehash algorithm
.provider
- theSecurityProvider
.
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RandomConfig
public RandomConfig(String algorithm, int reseedCount, SecurityProvider provider)
The constructor.- Parameters:
algorithm
- thehash algorithm
.reseedCount
- there-seed count
.provider
- theSecurityProvider
.
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Method Detail
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getReseedCount
public int getReseedCount()
- Returns:
- the number of calls to
RandomCreator.nextRandom(int)
after which the underlyingSecureRandom
is re-seeded (a smaller random number of random seeds are skipped to reduce predictability even stronger).
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