A Study on Smart Online Frame Forging Attacks against Video Surveillance System

TL;DR

This paper investigates real-time frame forging attacks on smart video surveillance systems, demonstrating their feasibility and proposing a detection method using electrical network frequency analysis.

Contribution

It introduces a novel real-time frame duplication attack on smart VSS and proposes a detection technique based on electrical network frequency matching.

Findings

Feasibility of real-time frame forgery demonstrated

Attack can be triggered remotely via QR code or face detection

Proposed ENF-based detection method shows potential effectiveness

Abstract

Video Surveillance Systems (VSS) have become an essential infrastructural element of smart cities by increasing public safety and countering criminal activities. A VSS is normally deployed in a secure network to prevent access from unauthorized personnel. Compared to traditional systems that continuously record video regardless of the actions in the frame, a smart VSS has the capability of capturing video data upon motion detection or object detection, and then extracts essential information and send to users. This increasing design complexity of the surveillance system, however, also introduces new security vulnerabilities. In this work, a smart, real-time frame duplication attack is investigated. We show the feasibility of forging the video streams in real-time as the camera's surroundings change. The generated frames are compared constantly and instantly to identify changes in the pixel values that could represent motion detection or changes in light intensities outdoors. An attacker (intruder) can remotely trigger the replay of some previously duplicated video streams manually or automatically, via a special quick response (QR) code or when the face of an intruder appears in the camera field of view. A detection technique is proposed by leveraging the real-time electrical network frequency (ENF) reference database to match with the power grid frequency.