Abstract
The introduction of the Internet of Things (IoT), i.e., the interconnection of embedded devices over the Internet, has changed the world we live in from the way we measure, make calls, print information and even the way we get energy in our offices or homes. The convenience of IoT products, like closed circuit television (CCTV) cameras, internet protocol (IP) phones, and oscilloscopes, is overwhelming for end users. In parallel, however, security issues have emerged and it is essential for infrastructure providers to assess the associated security risks. In this paper, we propose a novel method to detect IoT devices and identify the manufacturer, device model, and the firmware version currently running on the device using the page source from the web user interface. We performed automatic scans of the large-scale network at the European Organization for Nuclear Research (CERN) to evaluate our approach. Our tools identified 233 IoT devices that fell into eleven distinct device categories and included 49 device models manufactured by 26 vendors from across the world.
Highlights
IntroductionFor 2020, the installed base of Internet of Things devices is forecast to grow to almost 31 billion worldwide [1]
The Internet of Things has become the latest trend in today’s world
We elaborate on the results of the Web-Internet of Things (IoT) Detection (WID) tool
Summary
For 2020, the installed base of Internet of Things devices is forecast to grow to almost 31 billion worldwide [1]. IoT devices do not have the traditional host-centric security solutions like antiviruses, firewalls, or any safety feature to detect malware. Instead, they run on certain firmware that is hardware-specific, and each type of device has a different protocol on whose principles it runs. As the IoT devices collect a lot of data, these firmwares should be developed by the manufacturers in a secured style, but is rarely the case. Access to the data collected and stored by these devices can aid criminals to gain a lot of sensitive information, like patients’ healthcare data or video footage of the cameras
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