Optimized Degree-Aware Random Patching for Thwarting IoT Botnets

The massive number of Device-to-Device (D2D) communication links and lack of protective programming cause Internet of Things (IoT) networks to be vulnerable to malware attacks. Botnets are formed when large number of devices get infected and controlled by the attacker. Controlled devices can be used...

Full description

Saved in:
Bibliographic Details
Published in:IEEE networking letters 2023-03, Vol.5 (1), p.1-1
Main Authors: Mohamed, Munzir, ElSawy, Hesham, Mesbah, Wessam
Format: Article
Language:English
Subjects:
Botnet
Correlation
Denial of service attacks
Device-to-device communication
Internet of Things
Malware
Optimization
Security
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The massive number of Device-to-Device (D2D) communication links and lack of protective programming cause Internet of Things (IoT) networks to be vulnerable to malware attacks. Botnets are formed when large number of devices get infected and controlled by the attacker. Controlled devices can be used by the attacker to launch denial of service (DoS) attacks. In the literature, population dynamics were used to model the malware propagation in IoT networks. In this paper the model is modified to include the spatial degree correlation between neighboring devices, and the defender optimization problem is updated to acquire different patching rates.
ISSN:2576-3156
2576-3156
DOI:10.1109/LNET.2023.3241867