Journal
TELECOMMUNICATION SYSTEMS
Volume 73, Issue 1, Pages 3-25Publisher
SPRINGER
DOI: 10.1007/s11235-019-00599-z
Keywords
IoT; DDoS; Botnet; Malware detection; Machine learning
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Internet-of-things has emerged out as an important invention towards employing the tremendous power of wireless media in the real world. We can control our surroundings by interacting with numerous smart applications running independently on different platforms, almost everywhere in the world. IoT, with such a ubiquitous popularity often serve itself as a potential platform for escalating malicious entities. These entities get an access to the legitimate devices by exploiting IoT vulnerabilities which results from several constraints like limited resources, weaker security, etc. and can further take form of various attacks. Distributed Denial-of-service (DDoS) in IoT network is an attack which targets the availability of the servers by flooding the communication channel with impersonated requests coming from distributed IoT devices. Defending DDoS in IoT has now become an exigent area of research due to the recent incidents of demolishment of some renowned servers, reported in previous few years. In this paper, we discuss the concept of malware and botnets working behind 'Distributed' DoS in IoT. The various DDoS defence techniques are broadly described and compared in order to identify the security gaps present in them. Moreover, we list out the open research issues and challenges that need to be addressed for a stronger as well as smarter DDoS defence.
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