Detect and Classify IoT Camera Traffic

Deployment of IoT cameras in an organization threatens security and privacy policies, and the classification of network traffic without using IP addresses and port numbers has been challenging. In this paper, we have designed, implemented and deployed a system called iCamInspector to classify network traffic arising from IoT camera in a mixed networking environment. We have collected a total of about 36GB of network traffic containing video data from three different types of applications (four online audio/video conferencing applications, two video sharing applications and six IoT camera from different manufacturers) in our IoT laboratory. We show that with the help of a limited number of flow-based features, iCamInspector achieves an average accuracy of more than 98 testing phase of the system. A real deployment of our system in an unseen environment achieves a commendable performance of detecting IoT camera with an average detection probability higher than 0.9.


Network Traffic Characteristics of IoT Devices in Smart Homes

Understanding network traffic characteristics of IoT devices plays a cri...

Vulnerability Assessment and Penetration Testing on IP cameras

IP cameras have always been part of the Internet of Things (IoT) and are...

IoT Security: An End-to-End View and Case Study

In this paper, we present an end-to-end view of IoT security and privacy...

Securing Smart Homes via Software-Defined Networking and Low-Cost Traffic Classification

IoT devices have become popular targets for various network attacks due ...

Elixir: A system to enhance data quality for multiple analytics on a video stream

IoT sensors, especially video cameras, are ubiquitously deployed around ...

Spying on the Spy: Security Analysis of Hidden Cameras

Hidden cameras, also called spy cameras, are surveillance tools commonly...

Please sign up or login with your details

Forgot password? Click here to reset