A Study on Smart Online Frame Forging Attacks against Video Surveillance
System
release_nqjtwih4ynhnrpzmc2svwqz27q
by
Deeraj Nagothu, Jacob Schwell, Yu Chen, Erik Blasch, Sencun Zhu
2019
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.
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