Članovi Zavoda za IKP objavili su znanstveni rad pod naslovom „Boosting-based DDoS Detection in Internet of Things Systems“ u prestižnom znanstvenom časopisu IEEE Internet of Things autora I. Cvitić, D. Peraković, B. B. Gupta i K. K. R. Choo.
Prestiž i važnost časopisa vidljiv je kroz faktor odjeka IF(2020) = 9.936 te pripadnost Q1 kvartilu prema SCImago.
Objavljeni rad rezultat je opsežnog istraživanja u okviru projekta Sveučilišta u Zagrebu „Izazovi informacijsko-komunikacijskih mreža I tehnologija, usluga i korisničke opreme pri uspostavi okruženja Society 5.0“ kao i kvalitetne suradnje sa kolegama iz Indije i SAD-a.
Abstract— Distributed denial of service (DDoS) attacks remain challenging to mitigate in existing systems, including in-home networks that comprise different Internet of Things (IoT) devices. In this paper, we present a DDoS traffic detection model that uses a boosting method of logistic model trees for different IoT device classes. Specifically, a different version of the model will be generated and applied for each device class, since the characteristics of the network traffic from each device class may have subtle variation(s). As a case study, we explain how devices in a typical smart home environment can be categorized into four different classes (and in our context, Class 1 – very high level of traffic predictability, Class 2 – high level of traffic predictability, Class 3 – medium level of traffic predictability, and Class 4 – low level of traffic predictability). Findings from our evaluations show that the accuracy of our proposed approach is between 99.92% and 99.99% for these four device classes. In other words, we demonstrate that we can use device classes to help us more effectively detect DDoS traffic.