Detection of Threats to IoT Devices using Scalable VPN-forwarded Honeypots

Tambe, Amit and Aung, Yan Lin and Sridharan, Ragav and Ochoa, Martin and Tippenhauer, Nils Ole and Shabtai, Asaf and Elovici, Yuval
(2019) Detection of Threats to IoT Devices using Scalable VPN-forwarded Honeypots.
In: ACM Conference on Data and Application Security and Privacy (CODASPY).
Conference: None | Not Set
(In Press)


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Attacks on Internet of Things (IoT) devices, exploiting inherent vulnerabilities, have intensified over the last few years. Recent large-scale attacks, such as Persirai, Hakai, etc. corroborate concerns about the security of IoT devices. In this work, we propose an approach that allows easy integration of commercial off-the-shelf IoT devices into a general honeypot architecture. Our approach projects a small number of heterogeneous IoT devices (that are physically at one location) as many (geographically distributed) devices on the Internet, using connections to commercial and private VPN services. The goal is for those devices to be discovered and exploited by attacks on the Internet, thereby revealing unknown vulnerabilities. For detection and examination of potentially malicious traffic, we devise two analysis strategies: (1) given an outbound connection from honeypot, backtrack into network traffic to detect the corresponding attack command that caused the malicious connection and use it to download malware, (2) perform live detection of unseen URLs from HTTP requests using adaptive clustering. We show that our implementation and analysis strategies are able to detect recent large-scale attacks targeting IoT devices (IoT Reaper, Hakai, etc.) with overall low cost and maintenance effort.


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