2013
Flow-based Monitoring of Honeypots
HUSÁK, Martin a Martin DRAŠARZákladní údaje
Originální název
Flow-based Monitoring of Honeypots
Název česky
Monitorování honeypotů pomocí toků
Autoři
Vydání
Brno, Security and Protection of Information 2013, od s. 63-70, 8 s. 2013
Nakladatel
Univerzita obrany
Další údaje
Jazyk
angličtina
Typ výsledku
Stať ve sborníku
Obor
10201 Computer sciences, information science, bioinformatics
Stát vydavatele
Česká republika
Utajení
není předmětem státního či obchodního tajemství
Forma vydání
tištěná verze "print"
Označené pro přenos do RIV
Ano
Kód RIV
RIV/00216224:14610/13:00065721
Organizační jednotka
Ústav výpočetní techniky
ISBN
978-80-7231-922-0
ISSN
Klíčová slova anglicky
honeypot;monitoring;NetFlow;NfSen;dictionary attack
Příznaky
Mezinárodní význam, Recenzováno
Změněno: 27. 4. 2018 05:05, RNDr. Martin Husák, Ph.D.
Anotace
V originále
Honeypots are known as an effective tools for discovering new attacks and for observing activity of the attackers. However, they are often seen as a research-oriented tools for security professionals that require constant supervision. We have created an incident detection system based on a combination of honeypots and flow-based monitoring that takes the best of both without additional complexity. In this paper we present deployment of both low-interaction and high-interaction honeypots and their monitoring based on network flows. We show how honeypots can be used as an automatic detection tool in the production network. We present a plug-in called honeyscan for widely-used NetFlow collector NfSen that was developed to monitor and evaluate network activity of the honeypot and to report security incidents. This plug-in processes traffic destined to honeypots, stores credentials from authentication attempts, and observes attacker's activity in the protected network. The plug-in has been deployed in the network of Masaryk University and has become one of the most contributory detection tools with tens of reported incidents per month. We support this claim by doing a comparison with other detection tool and by exploring applications of recorded data.
Návaznosti
| VG20132015103, projekt VaV |
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