V dnešnej dobe sú wifi siete široko rozšírenou technológiou, ktorú používa väčšina notebookov a mobilných zariadení. Ochrana týchto sietí z vonkajšej strany je väčšinou zabezpečená protokolom WPA2 a silným šifrovacím algoritmom AES. Avšak, zamysleli ste sa niekedy nad tým, ako sú tieto siete zabezpečené z vnútornej strany? 

A novel behavioral detection framework is proposed to detect zero day buffer overflow vulnerabilities (based on network behavioral signatures) using zero-day exploits, instead of the signature-based or anomaly-based detection solutions currently available for IDPS techniques. At first we present the detection model that uses shadow honeypot. Our system is used for the online processing of network attacks and generating a behavior detection profile. The detection profile represents the dataset of 112 types of metrics describing the exact behavior of malware in the network. In this paper we present the examples of generating behavioral signatures for two attacks – a buffer overflow exploit on FTP server and well known Conficker worm. We demonstrated the visualization of important aspects by showing the differences between valid behavior and the attacks. Based on these metrics we can detect attacks with a very high probability of success, the process of detection is however, very expensive.