Deepfake in Cyber Security – Understand The New Emerging Threat

Recent surveys on cyberattacks show that a new cyber threat named ‘deep fake’ is topping the list. Where cyber criminals incorporate advanced AI-powered attack methods to evade security controls. In most cases, email is preferred as the delivery method for executing the attack. Who are their targets, if you ask, then both individuals and businesses Hence, to stay safe from this emerging attack, it’s crucial to have an in-depth understanding of what’s deepfake in cybersecurity, how it works, and most importantly how can you spot it.

Without further ado, let’s dive in.

What’s Deepfake Attack?

Deepfake is a type of cyber attack that uses artificial intelligence technology to create fake images, sounds, and videos. If you go by the term “deep fake” then it combines the idea of deep learning with something fake. 

In other words, deepfake technology combines hoaxed images and sounds. Further, compiles them together using machine-learning algorithms. The end result is so accurate that it’s hard to find any difference between the real and fake. 

Other than that, with this tech, cybercriminals have the capability to bring people and events into existence that don’t actually exist or didn’t even happen. Why do they do it? Well, there is a nefarious purpose behind it i.e. to mislead the public by spreading wrong information. For instance, let’s say a politician is running an election campaign. To shift public opinion or spread fake news, opponents may hire someone to create deepfake videos that could show the politician saying something they have not said.

Not just that, deep fake technology is used to fulfill various purposes.

Deepfake in Cyber Security – Where is it Used?

Deepfake attack targets different areas. Based on that it can be categorized as follows.

1. Societal

Typically politicians and celebrities are the main targets. And, the primary intention here is to stock social unrest and political polarization. Celebrity pornography, election manipulation, etc are a few instances.

2. Legal

To save culprits, especially cybercriminals, from the hands of justice, respondents usually take the help of deepfake technology for falsifying electronic evidence.

3. Personal

Deepfake in cyber security is not limited to causing damage to famous figures. Additionally, they prey on people through non-consensual pornography, bullying, and online child exploitation. This results in emotional and psychological harm.

Above all, deep fake technology poses a great threat to cyber security. Let’s explore that.

Understand the Darkside of Deepfake in Cyber Security

Deepfake technology has the capacity to damage many systems and pose serious cybersecurity dangers. Here are several scenarios in which deep fakes can harm cybersecurity:

• Social engineering attacks: Deepfakes can be used to produce incredibly convincing films or audio recordings of somebody pretending to be someone else, like a trusted coworker or a senior CEO. These deepfakes can be used in email fraud and social engineering attacks to trick targets into disclosing private information, sending money, or allowing unauthorized access.

• Business email compromise (BEC): Here online fraudsters pretend to be senior executives in organizations by manipulating voice or video recordings. Attackers might coerce staff members into doing activities that jeopardize the company’s security by imitating their voices or appearance, such as approving fraudulent transactions or divulging sensitive information.

• Identity theft and fraud: These are made possible by the use of deepfake technology, which can be used to construct false identities with the help of lifelike pictures, videos, and even voice recordings. By doing so, hackers may be able to steal people’s identities, pass themselves off as others, or produce fake proof of their involvement in shady transactions like creating bank accounts, applying for loans, or engaging in other types of financial fraud.
• Spreading malware: Email fraud campaigns can utilize deep fakes as bait, according to cybercriminals. In malicious emails or social media posts, they might, for instance, embed deep false films or photographs. Users may unwittingly download malware onto their computers when they click on these ostensibly innocent media files, which could result in data breaches, ransomware assaults, or other cyber-attacks.

How Deepfakes Are Made?

There are different methods used for creating deepfake and GAN (Generative Adversarial Networks) is the most popular one. A crucial technology used to create fake news and other synthetic media. 

A GAN uses two machine learning networks in an adversarial process to create artificial content. This first network is called the “generator.” It is fed data that represents the kind of content that will be produced so that it may ‘learn’ the properties of that kind of material. The generator then makes an effort to produce new instances of that data that share the same traits as the original data. The second machine learning network is then shown these generated samples after it has likewise been trained (though using a slightly different methodology) to “learn” to detect the features of that sort of data.

Now, the question comes;

Is it Easy to Spot Deepfakes in Cyber Security?

In simple words, it’s difficult to spot but possible. You can detect deepfakes by recognizing unusual activities. Such as Strange Eye Movement, A Lack of Blinking, Unnatural Facial Expressions, Hair color, body shape, abnormal skin color, etc.

Conclusion

The availability of the technology required to create them as well as the developing sophistication of deepfakes could have significant effects on security protocols. Biometrics has emerged as a reliable method of identity validation as passwords are becoming less and less used. It is logical. Security personnel and individuals must both be aware that deepfakes could be used against them. Hence, better to watch out for these potential cybersecurity threats.

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FAQs

Q- What is Deepfake?
A deepfake is a modified or synthesized media that is made by artificial intelligence (AI) methods, such as deep learning. It usually takes the form of audio or video. These artificial intelligence-generated media can accurately portray people saying or doing things they have never done.
Q- How Deepfakes are created?
Generative adversarial networks, or GANs, are deep learning algorithms that are used to construct deepfakes. A discriminator assesses the legitimacy of the generated content, while a generator produces it, making up a GAN. The generator improves its ability to produce realistic content via an ongoing feedback loop.
Q- How can cyberattacks employ Deepfakes?
Convincing Phishing scams can be made by cybercriminals using deepfakes, tricking victims into divulging personal information. To trick staff into performing unauthorized acts, deepfakes can also be used for CEO fraud. These techniques involve producing convincing audio or video communications.
Q- Does making and disseminating deepfakes have legal repercussions?
Development and dissemination of deepfakes are prohibited by law in many places, particularly when employed for nefarious intent like harassment, fraud, or defamation. The seriousness of the offense will determine the legal implications, which could include fines, jail time, or other sanctions.