Proposal / Submission Type
Peer Reviewed Paper
Abstract
Smart homes are becoming more common as more people integrate IoT devices into their home environment. As such, these devices have access to personal data on their homeowners’ networks. One of the advantages of IoT devices is that they are compact. However, this limits the incorporation of security measures in their hardware. Misconfigured IoT devices are commonly the target of malicious attacks. Additionally, distributed denial-of-service attacks are becoming more common due to applications and software that provides users with easy-to-use user interfaces. Since one vulnerable device is all an attacker needs to launch an attack on a network, in regards to IoT devices, there is a need for businesses and homeowners to find out methods of predicting incoming DDoS attacks. The earlier a DDoS attack is discovered, the earlier mitigation and prevention techniques can be applied. One way to predict incoming DDoS attacks is from emerging patterns. To discover these patterns, we constructed a home IoT environment and conducted LOIC and Slow Loris DDoS attacks against this environment. This setup led to the discovery of five distinct patterns that emerged when the IoT devices were being DDoS-ed. In this paper, we will discuss the DDoS attack used, home IoT environment, normal vs attacked traffic patterns, and make recommendations for future research.
Scholarly Commons Citation
Ho, Samuel; Greeson, Hope; and Karabiyik, Umit, "Smart Home Forensics: Identifying Ddos Attack Patterns on Iot Devices" (2022). Annual ADFSL Conference on Digital Forensics, Security and Law. 6.
https://commons.erau.edu/adfsl/2022/presentations/6
Included in
Aviation Safety and Security Commons, Computer Law Commons, Defense and Security Studies Commons, Forensic Science and Technology Commons, Information Security Commons, National Security Law Commons, OS and Networks Commons, Other Computer Sciences Commons, Social Control, Law, Crime, and Deviance Commons
Smart Home Forensics: Identifying Ddos Attack Patterns on Iot Devices
Smart homes are becoming more common as more people integrate IoT devices into their home environment. As such, these devices have access to personal data on their homeowners’ networks. One of the advantages of IoT devices is that they are compact. However, this limits the incorporation of security measures in their hardware. Misconfigured IoT devices are commonly the target of malicious attacks. Additionally, distributed denial-of-service attacks are becoming more common due to applications and software that provides users with easy-to-use user interfaces. Since one vulnerable device is all an attacker needs to launch an attack on a network, in regards to IoT devices, there is a need for businesses and homeowners to find out methods of predicting incoming DDoS attacks. The earlier a DDoS attack is discovered, the earlier mitigation and prevention techniques can be applied. One way to predict incoming DDoS attacks is from emerging patterns. To discover these patterns, we constructed a home IoT environment and conducted LOIC and Slow Loris DDoS attacks against this environment. This setup led to the discovery of five distinct patterns that emerged when the IoT devices were being DDoS-ed. In this paper, we will discuss the DDoS attack used, home IoT environment, normal vs attacked traffic patterns, and make recommendations for future research.
