Convert a SID to String with Java

A security identifier (SID) is an unique identifier, commonly used in Microsoft’s systems. For example, it’s used to identify users within Windows, or, more generally, within an Active Directory.

The SID is a binary value, with a variable length, that can be also be represented as a string. This conversion is implemented by the function called ConvertSidToStringSid, provided by the library Advapi32.dll, available only in Windows.

Hence, if you need to perform this conversion, you can procede with one of these two paths:

  • Use Advapi32 (only in Windows)
  • Rewrite the conversion
Thus, it’s very useful to have that implementation in a particular language (in our case Java), to be used everywhere. I noticed that, after a research in Internet, all the implementations are wrong, despite they work in general. Therefore, I decided to write my own implementation, thoroughly tested to prove you its correctness.

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Ruzzle Solver Algorithm

With the success of Ruzzle Solver, a lot of users have asked me to publish more informations about it. Some of them were interested to know more about it for an university exam. In this post, I will talk about some methods to realize this type of algorithms. Surely, in the future, I will talk more about its implementation.

The following tests have been executed with algorithms written in C, and with a MacBook Pro with an Intel Core i5 at 2.3 Ghz; with other implementation the results may obviously change, but I expect that the ratios between them will be the same.

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Artificial Intelligence: Markov Decision Process

In AI, sometimes, you need to plan a sequence of action that lead you to your goal. In stochastic environment, in those situation where you can’t know the outcomes of your actions, a sequence of actions is not sufficient: you need a policy.

Markov Decision Process is a mathematical framework that helps to build a policy in a stochastic environment where you know the probabilities of certain outcomes.

In this post, I give you a breif introduction of Markov Decision Process. Then, I’ll show you my implementation, in python, of the most important algorithms that can help you to find policies in stocastic enviroments. You can fine a more detailed description of the Markov Decision Process in my my slides that I’ve used for a seminar at University.

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