Network Intrusion Detection for IoT Security Based on Learning Techniques
Centre National de la Recherche Scientifique · Université de Bordeaux · +3 more institutions
Abstract
Pervasive growth of Internet of Things (IoT) is visible across the globe. The 2016 Dyn cyberattack exposed the critical fault-lines among smart networks. Security of IoT has become a critical concern. The danger exposed by infested Internet-connected Things not only affects the security of IoT but also threatens the complete Internet eco-system which can possibly exploit the vulnerable Things (smart devices) deployed as botnets. Mirai malware compromised the video surveillance devices and paralyzed Internet via distributed denial of service attacks. In the recent past, security attack vectors have evolved bothways, in terms of complexity and diversity. Hence, to identify and prevent or detect novel attacks, it…
Citation impact
- FWCI
- 78.97
- Percentile
- 100%
- References
- 147
Authors
5- NCNadia ChaabouniCorresponding
Centre National de la Recherche Scientifique, Université de Bordeaux, Institut Polytechnique de Bordeaux
- MMMohamed Mosbah
Centre National de la Recherche Scientifique, Université de Bordeaux, Laboratoire Bordelais de Recherche en Informatique, Institut Polytechnique de Bordeaux
- AZAkka Zemmari
Centre National de la Recherche Scientifique, Université de Bordeaux, Laboratoire Bordelais de Recherche en Informatique, Institut Polytechnique de Bordeaux
- CSCyrille Sauvignac
Atos (France)
- PFParvez Faruki
Topics & keywords
- Computer science
- Botnet
- Computer security
- Exploit
- Intrusion detection system
- Malware
- Context (archaeology)
- Denial-of-service attack