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IPPS
2007
IEEE

Recurrent neural networks towards detection of SQL attacks

10 years 6 months ago
Recurrent neural networks towards detection of SQL attacks
In the paper we present a new approach based on application of neural networks to detect SQL attacks. SQL attacks are those attacks that take advantage of using SQL statements to be performed. The problem of detection of this class of attacks is transformed to time series prediction problem. SQL queries are used as a source of events in a protected environment. To differentiate between normal SQL queries and those sent by an attacker, we divide SQL statements into tokens and pass them to our detection system, which predicts the next token, taking into account previously seen tokens. In the learning phase tokens are passed to recurrent neural network (RNN) trained by backpropagation through time (BPTT) algorithm. Teaching data are shifted by one token forward in time with relation to input. The purpose of the testing phase is to predict the next token in the sequence. All experiments were conducted on Jordan and Elman networks using data gathered from PHP Nuke portal. Experimental resu...
Jaroslaw Skaruz, Franciszek Seredynski
Added 03 Jun 2010
Updated 03 Jun 2010
Type Conference
Year 2007
Where IPPS
Authors Jaroslaw Skaruz, Franciszek Seredynski
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