Home video surveillance camera-
According to a recently published study, a select amount of popular home video surveillance cameras are able to permit potential burglars to determine when you’re not home.
The international study that was conducted by researchers affiliated from Queen Mary University of London and the Chinese Academy of Science, which used data that was provided by a large Chinese manufacturer of Internet Protocol security cameras included information from the same researchers that found that they were able to tell if anyone was in a home, as well as what they were doing inside a home. This was done simply by viewing data that was uploaded by the camera, as well as without monitoring the actual video footage itself.
Cameras such as these are able to permit users to remotely monitor their homes through a video feed via the internet; however, according to the researchers, the traffic that is generated by the actual devices is able to reveal information that can compromise the privacy of the customers who actually own the devices.
One of the study authors, Gareth Tyson, went on record of stating that data uploads of all of the encrypted data actually increase whenever a camera starts to record something that is moving, meaning that an attacker will be able to tell if a camera is actually uploading footage of an individual in motion, as well as other various types of motion such as sitting and/or running.
Tyson also had the following to say in regards to one of the major risks to this:
“The risk is that someone who is specifically targeting an individual household rocks up outside with a device to try and start passively monitoring traffic.”
Furthermore, Tyson stated that an attacker would end up requiring an advanced level of technical knowledge in order to monitor the data on their own; however, there is always the chance that someone would be able to develop some sort of a program that is able to do this before selling it online. Additionally, while he hasn’t personally seen any kind of direct evidence of this type of attack occurring, one possible use could be if an individual wanted to commit a burglary:
“They monitor the camera traffic over an extended period of time, and by looking at the patterns that are generated by those cameras over maybe a week, they then start predicting the following week when you’re most likely to be in the house.”
It’s believed that the best way to reduce the overall risk of privacy is to have companies randomly inject data into their systems as a way to help make it harder for attackers to spot any kind of a pattern. Currently, Tyson and his team are attempting to extend all of their research in order to work out how to maintain overall camera performance while, at the same time, reducing the risks of privacy:
“What we want to do is have a more intelligent system that allows the camera to understand what that motion is, assess the level of risk, and only upload it and alert the user in a case where the camera feels that it’s worthy doing.”
This is said to be the very first study to investigate all of the risks posed by video streaming traffic that is generated by the cameras, and while the study authors didn’t analyze data from various brands, there were able to determine that cameras from those brand did present the same exact privacy risk.