We present our ongoing work on SPIN, a muchneeded open source measurement platform that enables researchers and other users to easily analyze the security features of devices in the "Internet of Things" (IoT), specifically in-home networks. SPIN accomplishes this by mapping and enhancing network-level measurements in the home network and by making them available through a well-defined interface. This enables all kinds of new applications for research and commercial purposes, such as privacy managers for consumers that visualize insecure IoT devices and their connections, and new algorithms that automatically block botnet traffic to protect the public Internet against IoT-powered DDoS attacks. SPIN is a flexible distributed system that runs in the home network and that keeps users in control. We have validated SPIN in our lab through prototype implementations.

Hidden behind domain names, there are lucrative (and ingenious) business models that misuse/abuse the DNS namespace and employ a diversified form of monetization. To curb some of those abuses, many research works have been proposed. However, while having a clear contribution and advancing the state-of-the-art, these works are constrained by their limited datasets and none of them present a survey on the forms of DNS abuse. In this paper, we address these limitations by presenting a case study in one top-level domain (TLD) operator (.nl) with diverse longitudinal datasets.We then cover eight business models that DNS abusers employ and their respective monetization form, and discuss how TLD operators can employ these datasets to detect these forms of abuse.