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Investigating IoT malware characteristics to improve network security

Dzulqarnain, Dzulqarnain (2019) Investigating IoT malware characteristics to improve network security.

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Abstract:The Internet of Things (IoT) revolution offers not only interconnected a whole generation of devices but also brought to the Internet plague of billions of poorly protected and easily hackable devices. Not surprisingly, this sudden flooding of fresh and insecure devices fueled threats, such as IoT malware. IoT malware that keeps evolving brings the importance of analyzing techniques that can be used to keep up with the growth of IoT Malware. In this research, we present a set of techniques to analyze the malware in order to understand and block its activity. We develop a hybrid approach that combines with machine learning to classify the malware family based on the network traffic. We have evaluated our solution in a set of 1700 malware collected during one year. As a result, we show that our approach can identify the malware with the accuracy of 92\%.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Internet Science and Technology MSc (60032)
Link to this item:http://purl.utwente.nl/essays/79355
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