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Active Profiling of Physical Devices at Internet Scale

Authors: Xuan Feng 0005; Qiang Li 0007; Qi Han 0001; Hongsong Zhu; Yan Liu 0021; Jie Cui; Limin Sun 0001;

Active Profiling of Physical Devices at Internet Scale

Abstract

Nowadays, more and more physical devices embed computing and networking capabilities and are visible on the Internet. These devices include webcams, net-printers, and industrial control equipments, etc. Collecting information about these devices is crucial to preserve cyber-security and facilitate security auditing for system administrators. In this paper, we propose a scalable framework for physical device profiling. It leverages banner grabbing to identify device types and running services, and uses clock skew to determine a device ID. Our framework scales well. We implement a prototype system and use it to profile Webcams and industrial control device. The results show that our system can effectively profile and identify Webcams in real time. We deploy it on the cloud server and use it to detect 4 billion IP addresses to profile 1.2 million Webcams and more than 60 thousand industrial control devices in 20 hours.

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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Top 10%
Top 10%
Average
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