Many security issues have come to the fore with the increasingly widespread adoption of Internet-of-Things (IoT) devices. The Mirai attack on Dyn DNS service, in which vulnerable IoT devices such as IP cameras, DVRs and routers were infected and used to propagate large-scale DDoS attacks, is one of the more prominent recent examples. IoT botnets, consisting of hundreds-of-thousands of bots, are currently present in-the-wild'' at least and are only expected to grow in the future, with the potential to cause significant network downtimes and financial losses to network companies. We propose, therefore, to build testbeds for evaluating IoT botnets and design suitable mitigation techniques against them. A DETERlab-based IoT botnet testbed is presented in this work. The testbed is built in a secure contained environment and includes ancillary services such as DHCP, DNS as well as botnet infrastructure including CnC and scanListen loading servers. Developing an IoT botnet testbed presented us with some unique challenges which are different from those encountered in non-IoT botnet testbeds and we highlight them in this paper. Further, we point out the important features of our testbed and illustrate some of its capabilities through experimental results.
Measurement and analysis of modern malware systems such as botnets relies crucially on execution of specimens in a setting that enables them to communicate with other systems across the Internet. Ethical, legal, and technical constraints however demand containment of resulting network activity in order to prevent the malware from harming others while still ensuring that it exhibits its inherent behavior. Current best practices in this space are sorely lacking: measurement researchers often treat containment superficially, sometimes ignoring it altogether. In this paper we present GQ, a malware execution "farm" that uses explicit containment primitives to enable analysts to develop containment policies naturally, iteratively, and safely. We discuss GQ's architecture and implementation, our methodology for developing containment policies, and our experiences gathered from six years of development and operation of the system.  Botnets constitute a serious security problem. A lot of effort has been invested towards understanding them better, while developing and learning how to deploy effective counter-measures against them. Their study via various analysis, modelling and experimental methods are integral parts of the development cycle of any such botnet mitigation schemes. It also constitutes a vital part of the process of understanding present threats and predicting future ones. Currently, the most popular of these techniques are "in-the-wild" botnet studies, where researchers interact directly with real-world botnets. This approach is less than ideal, for many reasons that we discuss in this paper, including scientific validity, ethical and legal issues. Consequently, we present an alternative approach employing "in the lab" experiments involving at-scale emulated botnets. We discuss the advantages of such an approach over reverse engineering, analytical modelling, simulation and in-the-wild studies. Moreover, we discuss the requirements that facilities supporting them must have. We then describe an experiment in which we emulated a 3000-node, fully-featured version of the Waledac botnet, complete with an emulated command and control (C&C) infrastructure. By observing the load characteristics and yield (rate of spamming) of such a botnet, we can draw interesting conclusions about its real-world operations and design decisions made by its creators. Furthermore, we conducted experiments with sybil attacks launched against it and verified their viability. However, we were able to determine that mounting such attacks is not so simple: high resource consumption can cause havoc and partially neutralise them. Finally, we were able to repeat the attacks with varying parameters, in an attempt to optimise them. The merits of this experimental approach is underlined since by the fact that it would have been difficult to obtain these results by other methods.