4.8 Article

A Quantitative Study of DDoS and E-DDoS Attacks on WiFi Smart Home Devices

Journal

IEEE INTERNET OF THINGS JOURNAL
Volume 8, Issue 8, Pages 6282-6292

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2020.3026023

Keywords

Computer crime; Smart homes; Wireless fidelity; Energy consumption; Internet of Things; Switches; Association; disconnection; energy consumption; Internet of Things (IoT); security

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This article analyzes the impact of DDoS and E-DDoS attacks on WiFi smart home devices, finding that the minimum DDoS attack rate causing service disruptions varies among different IoT smart home devices and buffer overflow within the victim device is critical. The group key updating process of WiFi may facilitate DDoS attacks by causing faster victim disconnections, and a higher E-DDoS attack rate sent by the attacker may not necessarily lead to a victim's higher energy consumption.
Internet of Things (IoT) has facilitated the prosperity of smart environments such as smart homes. Meanwhile, WiFi is a broadly used technology for the wireless connectivity of IoT devices. However, smart home IoT devices are often vulnerable to various security attacks. This article quantifies the impact of distributed denial of service (DDoS) and energy-oriented DDoS attacks (E-DDoS) on WiFi smart home devices and explores the underlying reasons from the perspective of attacker, victim device, and access point (AP). Compared to the existing work, which primarily focus on DDoS attacks launched by compromised IoT devices against servers, our work focuses on the connectivity and energy consumption of IoT devices when under attack. Our key findings are threefold. First, the minimum DDoS attack rate causing service disruptions varies significantly among different IoT smart home devices, and buffer overflow within the victim device is validated as critical. Second, the group key updating process of WiFi may facilitate DDoS attacks by causing faster victim disconnections. Third, a higher E-DDoS attack rate sent by the attacker may not necessarily lead to a victim's higher energy consumption. Our study reveals the communication protocols, attack rates, payload sizes, and victim devices' ports state as the vital factors to determine the energy consumption of victim devices. These findings facilitate a thorough understanding of IoT devices' potential vulnerabilities within a smart home environment and pave solid foundations for future studies on defense solutions.

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