CLI-DOS: Collaborative Counteraction against Denial of Service in the Internet of Things

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Sammanfattning

Internet of Things (IoT) is the next generation of network scenario where billions of devices are connected to the internet and capable to communicate with each other. However, they are especially vulnerable to Denial of Service (DoS) attack, which typically launched by overloading the server with bogus messages. Hence, unnecessary computation is performed by the IoT units, which can seriously worsen their performance or even make them unable to serve legitimate requests. Existing mechanisms for the detection and prevention of DoS attacks only either make it more difficult to perform massive DoS attacks or completely block the legitimate requests to be served. In this paper, we present CLI-DOS, a collaborative mechanism between Gateway and IoT units to counteract Denial of Service attacks. CLI-DOS combines an efficient attack-detection principle using short MAC value with a more effective defense strategy. In an under attack situation, we leverage the IoT gateway for preventing the attack messages to make contact with the IoT units while opening up possibilities to set-up connection with legitimate external entities. We evaluate the performance of our proposal from several standpoints. In conclusion, CLI-DOS offers a lower resource utilization in an under attack IoT units while preserving service availability to the best possible extent.

Originalspråkengelska
Titel på gästpublikation2020 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2020
FörlagIEEE - Institute of Electrical and Electronics Engineers Inc.
ISBN (elektroniskt)9781728147161
DOI
StatusPublished - 2020
Evenemang2020 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2020 - Austin, USA
Varaktighet: 2020 mar 232020 mar 27

Konferens

Konferens2020 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2020
Land/TerritoriumUSA
OrtAustin
Period2020/03/232020/03/27

Ämnesklassifikation (UKÄ)

  • Datavetenskap (datalogi)

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