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- W3080473790 abstract "DNS server is one of the most important Internet infrastructures in modern society. DNS Tunnel technology is firstly used to get free WiFi, more and more security incidents using DNS protocol to transmit information or illegal commands in recently advanced persistent threat attacks. Most security products such as firewalls, intrusion detection systems and intrusion prevention systems rarely detect DNS communication, which provides naturally command and control communication channel for attackers. The traditional detection methods only focus on the network communication feature for DNS tunnel tools, such as iodine, dnscat2 and dns2tcp. Then many machine learning detection methods are introduced to automatically learn the abstract features and classify the illegal communication method, but the detection result is not still satisfied with high accurate and low false positive. In order to solve this issue, the paper proposed an automatically detecting methods based on session behaviors and random forest algorithm. The experiments proved the method could achieve high accuracy (99.79%) with recall (98.67%), which is higher than other general algorithms." @default.
- W3080473790 created "2020-09-01" @default.
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- W3080473790 date "2020-07-01" @default.
- W3080473790 modified "2023-10-14" @default.
- W3080473790 title "Detecting DNS Tunnels Using Session Behavior and Random Forest Method" @default.
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- W3080473790 doi "https://doi.org/10.1109/dsc50466.2020.00015" @default.
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