Using SEIRS Epidemic Models for IoT Botnets Attacks

Konferenz: DRCN 2017 – Design of Reliable Communication Networks - 13th International Conference
08.03.2017 - 10.03.2017 in München, Deutschland

Tagungsband: DRCN 2017 – Design of Reliable Communication Networks

Seiten: 8Sprache: EnglischTyp: PDF

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Autoren:
Gardner, M. Todd; Beard, Cory; Medhi, Deep (University of Missouri–Kansas City, Kansas City, Missouri 64110-2499, USA)

Inhalt:
The spread of Internet of Things (IoT) botnets like those utilizing the Mirai malware were successful enough to power some of the most powerful DDoS attacks that have been seen thus far on the Internet. Two such attacks occurred on October 21, 2016 and September 20, 2016. Since there are an estimated three billion IoT devices currently connected to the Internet, these attacks highlight the need to understand the spread of IoT worms like Mirai and the vulnerability that they create for the Internet. In this work, we describe the spread of IoT worms using a proposed model known as the IoT Botnet with Attack Information (IoT-BAI), which utilizes a variation of the Susceptible-Exposed-Infected-Recovered-Susceptible (SEIRS) epidemic model [14]. The IoT-BAI model has shown that it may be possible to mitigate the frequency of IoT botnet attacks with improved user information which may positively affect user behavior. Additionally, the IoT-BAI model has shown that increased vulnerability to attack can be caused by new hosts entering the IoT population on a daily basis. Models like IoT-BAI could be used to predict user behavior after significant events in the network like a significant botnet attack.