POSTER: DNS Traffic Analysis for Malicious Domains Detection

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F15%3A00080508" target="_blank" >RIV/00216224:14330/15:00080508 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

POSTER: DNS Traffic Analysis for Malicious Domains Detection

Popis výsledku v původním jazyce

The web has become the medium of choice for people to search for information, conduct business, and enjoy entertainment. At the same time, the web has also become the primary platform used by miscreants to attack users. For example, drive-by-download attacks are a popular choice among bot herders to grow their botnets. In this poster we present our methodology for detecting any connection to malicious domain. Our detection method is based on a blacklist of malicious domains. We process the network traffic, particularly DNS traffic. We analyze all DNS requests and match the query with the blacklist. The blacklist of malicious domains is updated automatically and the detection is in the real time. We applied our methodology on a packet capture (pcap) file which contains traffic to malicious domains and we proved that our methodology can successfully detect the connections to malicious domains.

Název v anglickém jazyce

POSTER: DNS Traffic Analysis for Malicious Domains Detection

Popis výsledku anglicky

The web has become the medium of choice for people to search for information, conduct business, and enjoy entertainment. At the same time, the web has also become the primary platform used by miscreants to attack users. For example, drive-by-download attacks are a popular choice among bot herders to grow their botnets. In this poster we present our methodology for detecting any connection to malicious domain. Our detection method is based on a blacklist of malicious domains. We process the network traffic, particularly DNS traffic. We analyze all DNS requests and match the query with the blacklist. The blacklist of malicious domains is updated automatically and the detection is in the real time. We applied our methodology on a packet capture (pcap) file which contains traffic to malicious domains and we proved that our methodology can successfully detect the connections to malicious domains.

Druh

O - Ostatní výsledky

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/OFMASUN201301" target="_blank" >OFMASUN201301: CIRC - Mobilní dedikované zařízení pro naplňování schopností reakce na počítačové incidenty</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů