This class provides the functionality of a secret (symmetric) key generator.

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When you develop some applications in Java or on Android platform, you can sometimes need to generate a random alpha-numeric String to generate a session id, a unique temporary id or simply to generate sample string data. Use cases are multiples and to make that there are a lot of possibilities. I've been looking for a simple Java algorithm to generate a pseudo-random alpha-numeric string. In my situation it would be used as a unique session/key identifier that would 'likely' be unique over 500K+ generation (my needs don't really require anything much more sophisticated). The Java KeyGenerator class (javax.crypto.KeyGenerator) is used to generate symmetric encryption keys. A symmetric encryption key is a key that is used for both encryption and decryption of data, by a symmetric encryption algorithm. In this Java KeyGenerator tutorial I will show you how to generate symmetric encryption keys. Javascript Key Codes The following are javascript key codes. When a keydown, keyup, or keypress event occurs, JavaScript records the key code of the key that was pressed or released. This is stored in the event object. JQuery normalizes the.which property of the eventObj so you can reliably use it to retrieve the key code. To generate secrete key we can use Java KeyGenerator class which provides the functionality of a secret (symmetric) key generator. Key generators are constructed using one of the getInstance class methods of this class.

Key generators are constructed using one of the getInstance class methods of this class.

KeyGenerator objects are reusable, i.e., after a key has been generated, the same KeyGenerator object can be re-used to generate further keys.

There are two ways to generate a key: in an algorithm-independent manner, and in an algorithm-specific manner. The only difference between the two is the initialization of the object:

• Algorithm-Independent Initialization

  All key generators share the concepts of a keysize and a source of randomness. There is an init method in this KeyGenerator class that takes these two universally shared types of arguments. There is also one that takes just a keysize argument, and uses the SecureRandom implementation of the highest-priority installed provider as the source of randomness (or a system-provided source of randomness if none of the installed providers supply a SecureRandom implementation), and one that takes just a source of randomness.

  Since no other parameters are specified when you call the above algorithm-independent init methods, it is up to the provider what to do about the algorithm-specific parameters (if any) to be associated with each of the keys.

• Algorithm-Specific Initialization

  For situations where a set of algorithm-specific parameters already exists, there are two init methods that have an AlgorithmParameterSpec argument. One also has a SecureRandom argument, while the other uses the SecureRandom implementation of the highest-priority installed provider as the source of randomness (or a system-provided source of randomness if none of the installed providers supply a SecureRandom implementation).

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In case the client does not explicitly initialize the KeyGenerator (via a call to an init method), each provider must supply (and document) a default initialization.

Every implementation of the Java platform is required to support the following standard KeyGenerator algorithms with the keysizes in parentheses:

• AES (128)
• DES (56)
• DESede (168)
• HmacSHA1
• HmacSHA256

These algorithms are described in the KeyGenerator section of the Java Cryptography Architecture Standard Algorithm Name Documentation. Consult the release documentation for your implementation to see if any other algorithms are supported.

Today we’ll look at creating generators. In simple terms, a generator is a function which returns the next value in a sequence. Unlike an iterator, it generates the next value when needed, rather than returning the next item of a pre-generated collection. Some languages such as Python support generators natively via keywords such as yield. When a generator’s next value is requested in Python, the generator function continues to run until the next yield statement, where a value is returned. The generator function is able to continue where it left off which can be quite confusing for the uninitiated. So how to do something similar in Java?

We saw in the last article that we can use an IntStream to generate a simple set of numbers, but we had to generate them all up front. That’s fine if we know how many we’re going to need. What if we don’t, and we want to be able to get the next whenever we like? This is where a generator comes in.

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Let’s choose a simple infinite sequence, the square numbers. In a standard Java implementation we’d end up with something like the following:

This prints the first three square numbers. Note we could have gone further and implemented this as an iterator.

What we have here is an example of lazy evaluation in a non-functional style. Wikipedia defines lazy evaluation as: ‘In programming language theory, lazy evaluation, or call-by-need is an evaluation strategy which delays the evaluation of an expression until its value is needed’. Lazy evaluation is useful because we don’t need to worry about infinite sequences, performing computationally expensive operations up-front, and about storage.

Let’s expand on the example to allow getting a batch of results. This is easy – create a nextN function which calls next() a number of times and returns the results in say a List:

A few points:

• Notice in the nextN function there is the empty diamond in the new ArrayList statement. This was added in Java 7 to save having to state the type both on the left and the right hand side; the compiler now works it out.
• List is an Iterable, and Iterable now has a forEach() method which was added in Java 8. We could use stream() as before to create a stream, but if all we want to do is pass the contents to a function forEach() does nicely.

Now, to save having to write nextN for every sequence we make, we could create a new type which extends Iterator providing the nextN function.

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The only problem we face here is that we have to save the batch in a list before we can operate on it. Java 8 provides another way. Let’s go back and start again with the following code:

This uses IntStream to get the indexes of the sequence in a stream and calls map to convert them into their squares. The problem is that to get more squares than the tenth we need to duplicate the pipeline and start it off from the right place. Let’s look at another way without using a range:

This also generates the first 10 square numbers. This time it uses the iterate function. This takes two parameters, the first is our initial value, and the second is a function defining how to get to the next value from the previous. It’s a good place to use a lambda function. We can even dispense of the map function since we can undo squaring easily in iterate to get what the last index was:

This solves one of the problems of having to buffer beforehand. However, we need to use the limit operator on the stream to limit it to 10 items, otherwise it would keep on going. Unfortunately this is a problem, since once we’ve got the 10 the stream is ‘operated on’ and we can’t use it again to generate more. If we try, we get an IllegalStateException. We’d have to create another stream to get more.

So how do we get around the problem of the stream being used up? Instead of using IntStream’s iterate function, we can use generate instead. IntStream’s generate function takes an instance of an IntSupplier. IntSupplier has a getAsInt() function which returns the next int in the sequence which is very much like our next() function. Here is an example that prints the first 20 square numbers in two batches:

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Again we’re using limit to stop the stream continuing indefinitely. However unlike last time, although the stream is used up, the generator still survives and can be used again. No buffering needed either, just keeping hold of the supplier. The only downside vs the old Java way is that we have to use Streams to get sequence members, although this comes with other benefits such as parallelism which we’ll see in a later article.

Overall, there are several ways to generate a sequence and which we chose may depend on our needs. Using an IntSupplier is a good way to integrate with the rest of the Java 8 functional programming support.