Management and analytical software for data gathered from HoneyPot system

The paper describes details concerning systems used for analysis and the result of data gathered from two various HoneyPot systems, implemented at Institute of Computer Science. The first system uses data mining techniques for the automatic discovery of interesting patterns in connections directed to the HoneyPot. The second one is responsible for the collection and the initial analysis of attacks dedicated to the Web applications, which nowadays is becoming the most interesting target for cybercriminals. The paper presents results from almost a year of usage, with implemented prototypes, which prove it's practical usefulness. The person performing analysis improves effectiveness by using potentially useful data, which is initially filtered from noise, and automatically generated reports. The usage of data mining techniques allows not only detection of important patterns in rapid manner, but also prevents from overlooking interesting patterns in vast amounts of other irrelevant data.