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Denial of Service (DoS) attacks are some of the biggest problems for computer security. Detection and early alert of these attacks would be helpful information which could be used to make appropriate decisions in order to minimize their negative impact. This paper proposes a new approach based on SOM-type unsupervised artificial neural networks for detection of this type of attacks at an early stage. We present a SOM-based Computational Intelligent System for DoS Attacks Detection (CISDAD) and a new representation scheme for information. A study has been carried out on real traffic from a healthcare environment based on web technologies. Results show effectiveness in the detection of toxic traffic and congestion regarding abuse in communication networks.