Abstract

The number of IoT consumer devices (eg, security cameras, projectors, refrigerators etc) connected to the Internet is constantly increasing. It has been estimated that 3.9 billion IoT consumer devices were in use in 2016 and that by 2020 up to 12.8 billion devices will be deployed.1 This trend, combined with the fact that most of the owners still lack cyber-security awareness, has established a breeding ground for new malware families targeting IoT devices. An example is the Mirai botnet that was responsible for the biggest DDoS attack ever detected in the history of the Internet.2 The size of the Internet of Things (IoT) is rapidly increasing. By 2020 up to 12.8 billion devices will be deployed. This has established a breeding ground for new malware families targeting IoT devices. Filippo Lauria of the Institute of Informatics and Telematics at the Italian National Research Council explains why mapping and classifying compromised IoT nodes is a challenging task. And he proposes a software infrastructure that could be used to remotely footprint, report and (if possible) secure compromised IoT devices.

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