Now that, Internet has become a part of our life. Online security has become more important than ever before in the era of the internet.
Privacy is a hot topic in the world of the Internet. In fact, its subtopics are diverse. And they include ones such as anonymity, NSA controversies, and cyber-attacks. There is an often ignored or less spoken topic, Deepfake, a method of voice/face swapping.
Why? It is because this is a recent technology, and it hasn’t been developed thoroughly (until recent times). And it does call for concern. After all, “Deepfake” is a tool that can be misused for a variety of purposes.
Below, we’ll breakdown Deepfakes technology. Specifically, we’ll look at…
So let’s get started.
Deepfake technology is a result of advances in artificial Intelligence. And these advances put the technology in constant expansion and improvement. The technology is based on a large database of experience, and it’s constantly in development and correction.
Deepfake is a technology that’s used for the creation of “fake media.” This form of the technology enables users to alter visual and graphical information (in video/audio) – thus modifying faces and voices in content. And it does so by manipulating subtleties in how two AI technologies interact, those being the discriminator and generator.
In AI technologies, discriminators filter identifiers and information in media content. From there, they decide if the content is real or fake.
Discriminators normally provide detailed reports on why pieces of content are fake. But since Deepfake is a form of AI, it can adapt itself to different identifiers.
Deepfake can use and reverse engineer the results of discriminator reports. They can learn how a discriminator works, thus upgrading their functions to alter media undetected. And as a result, a Deepfake can improve their ability to fake faces and voice, passing detection with high levels of accuracy.
They are numerous, and almost all impacts are negative.
Videos are normally a reliable source of news. After all, they show faces and voices in motion (a feat hard to mimic naturally). Plus, it’s hard to put together a fake video (unlike a fake picture). And that’s because each frame and second of the audio needs to be modified.
This isn’t the case with Deepfake.
Any face can be plastered on the most controversial of videos. And the same applies to voices, which can be modified for different audio outlets. And this creates the possibility of creating controversial news – while supplying fake evidence to frame certain individuals.
Phone calls are often used as evidence in media reports, where again – certain mannerisms of speech and voices are hard to swap.
Deepfake can change those.
They can switch the sounds of each speaker (including certain nuances like accent) to imply that a different individual is talking.
It sure is. At an advanced enough level, Deepfake can be used to place people in videos or conversations they never had. In fact, Deepfake can easily be used as a tool to create public scandals.
Political scandals are at the top of that list. Deepfake can be used to ruin a politician’s career. It can be used to disrupt elections or spread misinformation, causing millions of dollars in damages.
In fact, Deepfake can be used to outright end someone’s career in any field.
And that’s not all…
If Deepfake gets advanced to a level of difficult detection – then using audio/video material in courts might be difficult. Media won’t be a reliable source of evidence in case or trial. If Deepfake becomes too widespread, visual evidence might lead to a delay in cases. And that delay will come from the need to process authenticity to the smallest details. The result leads to higher costs for legal settlements – which is a negative for the average citizen.
Since Deepfake can alter voice and faces, it can be used for security breaches. However, it won’t be used for normal security systems. It will normally be for security measures that use voice and facial identifiers. As a result, those systems won’t be in development. Instead, securing products might shift to older methods, like written passwords.
How? It can be used to fake record prominent business leaders – then spreading misinformation about such individuals. This can be done to fake information about a competing company. It can also be done as a way to put down a new product.
While Deepfakes does threaten to ruin business (and individual security) – there’s a way to combat its influence. It all comes down to the right setup and even better consumer habits.
The biggest threats of Deepfakes are political. And the best way to avoid fake political news is by following announcements from their origins.
For example, if you hear that an announcement was made by someone from the government or senate, be sure to check their social media. That’s where the announcements tend to first go.
Also, when hearing a rumour about certain announcements made by personnel, look at multiple sources. Check multiple news outlets. See what each has to say, and wait for official responses.
The number one business risk of Deepfake is the impersonation of upper management (which might be your position). You can risk having a fraud impersonate your identity while making demands to employees for money transfers.
You can avoid those impersonation attempts by restricting important decisions to physical meetings. Also, we recommend trying the idea of visual e-conferences (where multiple individuals are attending), and you’ve set the schedule beforehand.
We mentioned audio recognition as a system that’s compromised through Deepfake. If that’s a part of your business activities (for product/resource/money storage), then be sure to use liveness detection. What that does is, it checks whether the person trying to access is physically present. And it does so through spoof detection, ensuring that the person is there. If not, the access attempt is treated as an illegitimate attack (which might prompt even harsher security measures).
Some services now require you to put the information about your “physical ID” to benefit from the service or subscribe. Your business can apply similar measures if your business handles both credit card info and constant online purchases.
For example, you might be running an online service that is pay-to-use, and with a variety of sub-services. Customers will need to pay to continue using your service monthly. Or, they might want to make special purchases as they use the service. Verification should exist with each purchase. It ensures that a real person is buying, and not a bot/fraud using Deepfake!
And you don’t need excessively advanced methods to do so. While it is a worldwide problem, proper consumer choices and security protocols go a long way. All you have to do is set up a good security plan and put it to practice!
By Uma Raj
By Uma Raj
By Abishek Balakumar
Pradeep is a Content Writer and Digital Marketing Specialist at Indium Software with a demonstrated history of working in the information technology and services industry.