Analyzing the Security and Privacy of Cloud-based Video Surveillance Systems

In the area of the Internet of Things, cloud-based camera surveillance systems are ubiquitously available for industrial and private environments. However, the sensitive nature of the surveillance use case imposes high requirements on privacy/confidentiality, authenticity, and availability of such systems. In this work, we investigate how currently available mass-market camera systems comply with these requirements. Considering two attacker models, we test the cameras for weaknesses and analyze for their implications. We reverse-engineered the security implementation and discovered several vulnerabilities in every tested system. These weaknesses impair the users' privacy and, as a consequence, may also damage the camera system manufacturer's reputation. We demonstrate how an attacker can exploit these vulnerabilities to blackmail users and companies by denial-of-service attacks, injecting forged video streams, and by eavesdropping private video data - even without physical access to the device. Our analysis shows that current systems lack in practice the necessary care when implementing security for IoT devices.