In recent years, the emerging Internet-of-Things (IoT) has led to rising concerns about the security of networked embedded devices. In this work, we focus on the adaptation of Honeypots for improving the security of IoTs. Low-interaction honeypots are used so far in the context of IoT. Such honeypots are limited and easily detectable, and thus, there is a need to find ways how to develop high-interaction, reliable, IoT honeypots that will attract skilled attackers. In this work, we propose the SIPHON architecture - a Scalable high-Interaction Honeypot platform for IoT devices. Our architecture leverages IoT devices that are physically at one location and are connected to the Internet through so-called wormholes distributed around the world. The resulting architecture allows exposing few physical devices over a large number of geographically distributed IP addresses. We demonstrate the proposed architecture in a large scale experiment with 39 wormhole instances in 16 cities in 9 countries. Based on this setup, six physical IP cameras, one NVR and one IP printer are presented as 85 real IoT devices on the Internet, attracting a daily traffic of 700MB for a period of two months. A preliminary analysis of the collected traffic indicates that devices in some cities attracted significantly more traffic than others (ranging from 600 000 incoming TCP connections for the most popular destination to less than 50000 for the least popular). We recorded over 400 brute-force login attempts to the web-interface of our devices using a total of 1826 distinct credentials, from which 11 attempts were successful. Moreover, we noted login attempts to Telnet and SSH ports some of which used credentials found in the recently disclosed Mirai malware.
Honeypots are a common measure to understand attacker activities in computer networks. The authors of @cite_1 provide a taxonomy of honeypots, and differentiate between low and high interaction honeypots. Both low and high interaction honeypots are compared in @cite_4 , and the authors conclude that high interaction honeypots provide more insights on attacker behavior than low interaction ones.
@cite_1 @cite_4
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Honeynet research has become more important as a way to overcome the limitations imposed by the use of individual honeypots. A honeynet can be defined as a network of honeypots following certain topology. Although there are at present many existing honeynet solutions, no taxonomies have been proposed in order to classify them. In this paper, we propose such taxonomy, identifying the main criteria used for its classification and applying the classification scheme to some of the existing honeynet solutions, in order to quickly get a clear outline of the honeynet architecture and gain insight of the honeynet technology. The analysis of the classification scheme of the taxonomy allows getting an overview of the advantages and disadvantages of each criterion value. We later use this analysis to explore the design space of honeynet solutions for the proposal of a future optimized honeynet solution. This paper presents an experimental study and the lessons learned from the observation of the attackers when logged on a compromised machine. The results are based on a six months period during which a controlled experiment has been run with a high interaction honeypot. We correlate our findings with those obtained with a worldwide distributed system of lowinteraction honeypots.