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.
@cite_3 , the authors described the implementation and deployment of a honeypot based on a number of real, vulnerable web applications. They hosted all the web applications in seven isolated virtual machines running on a VMWare Server. In order to limit the attack surface, the authors let the exposed services run as a non privileged user. They then analyzed the collected data to study attackers' behavior on the web applications during pre and post exploitation. In contrast, we work with real physical IoT devices to set up a high-interaction honeypot.
@cite_3
1531027799
Web attacks are nowadays one of the major threats on the Internet, and several studies have analyzed them, providing details on how they are performed and how they spread. However, no study seems to have sufficiently analyzed the typical behavior of an attacker after a website has been compromised. This paper presents the design, implementation, and deployment of a network of 500 fully functional honeypot websites, hosting a range of different services, whose aim is to attract attackers and collect information on what they do during and after their attacks. In 100 days of experiments, our system automatically collected, normalized, and clustered over 85,000 files that were created during approximately 6,000 attacks. Labeling the clusters allowed us to draw a general picture of the attack landscape, identifying the behavior behind each action performed both during and after the exploitation of a web application.