Abstract
Nowadays, the rapid growth of cloud computing and IoT enabled services among multiple organizations brings both promising prospects and security & privacy challenges. IP cameras have become a top target for hackers because of their relatively high computing power and throughput. To understand the risks of these threats requires learning about IP cameras–where are they, how many are there? Active scanning is considered to be an effective way, like SHODAN. However, deployment of smart cameras in the network address translation (NAT) environments with dynamic locations is usually desired. To find these Invisible Cameras, CamHunter: (i) introduces three statements of smart cameras when they are online, (ii) concludes the most popular smart cameras in China have very similar communication patterns, (iii) proposes a model to detect smart cameras in a passive way constructed by nineteen feature sets, and (iv) raises alarms for IoT manufacturers. Our real-world experiments demonstrate the effectiveness of CamHunter in finding smart cameras even if they are behind NATs and using encrypted connections like SSL/TLS or private protocols. We argue that CamHunter represents an important view of IoT security and privacy, and it can guide the effort of designing and protecting smart cameras.
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