Lessons Learned from Honeypots - Statistical Analysis of Logins and Passwords

Abstract : Honeypots are unconventional tools to study methods, tools and goals of attackers. In addition to IP addresses, timestamps and count of attacks, these tools collect combinations of login and password. Therefore, analysis of data collected by honeypots can bring different view of logins and passwords. In paper, advanced statistical methods and correlations with spatial-oriented data were applied to find out more detailed information about the logins and passwords. Also we used the Chi-square test of independence to study difference between login and password. In addition, we study agreement of structure of password and login using kappa statistics.
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A Min Tjoa; Li Da Xu; Maria Raffai; Niina Maarit Novak. 10th International Conference on Research and Practical Issues of Enterprise Information Systems (CONFENIS), Dec 2016, Vienna, Austria. Springer International Publishing, Lecture Notes in Business Information Processing, LNBIP-268, pp.112-126, 2016, Research and Practical Issues of Enterprise Information Systems. 〈10.1007/978-3-319-49944-4_9〉
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Soumis le : mardi 7 novembre 2017 - 17:26:54
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Pavol Sokol, Veronika Kopčová. Lessons Learned from Honeypots - Statistical Analysis of Logins and Passwords. A Min Tjoa; Li Da Xu; Maria Raffai; Niina Maarit Novak. 10th International Conference on Research and Practical Issues of Enterprise Information Systems (CONFENIS), Dec 2016, Vienna, Austria. Springer International Publishing, Lecture Notes in Business Information Processing, LNBIP-268, pp.112-126, 2016, Research and Practical Issues of Enterprise Information Systems. 〈10.1007/978-3-319-49944-4_9〉. 〈hal-01630533〉

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