Deepfake Injection Attacks: A Bitter Truth Backed By a Devious Lie

We have seen politicians morph into their rivals, celebrities endorsing products without them being paid a single dollar of royalty, we see revenge porn destroying the lives of innocent people, and all of it is indistinguishable from the real thing. What if these incidents were just the tip of the iceberg? What if the next deepfake is yours, targeting you in one of the above-mentioned ways? Would you let someone steal your identity and wreak havoc in your bank account, distort your face, which then force you into doing something really dangerous? Today’s blog is about the Deepfake injection attack, continue reading to know more about it and how presentation attack detection helps in steering clear of such attacks.

What is a Deepfake?

A deepfake is a sort of AI-generated or exploited visual content, images, or videos combined with audio content that is very realistic. This technology can change an individual’s face and voice which may be in the video or audio. This technology usually runs widely on the internet, for example: 

• Barack Obama’s speech video
• Tom Cruise impersonation 
• Katy Perry’s fake images while attending Met Gala 2024
• Former Indonesian President Soeharto showed up in the 2024 election time. 

Though these videos seem amusing at first because they are made to entertain large masses, deepfakes are turning out to be a strong tool for fraudsters to play with biometric verification systems.

Biometric verification systems observe different aspects of a person’s body, which include fingerprinting, face identification, and retina. Besides that, selfie verification is one of the major compositions of biometric authentication, which has turned out to be an important component in e-commerce transactions and mobile banking transfers.

All of the above-mentioned detail shows how deepfake technology impersonates the systems acting as you but are real fraudsters. This, for a reason, has made this technology a strong tool for cybercrime.

Deepfake Injection Attacks & Their Working Mechanism

Deepfake injection attacks are a type of cyber-attack whereby individuals use deepfakes to inject fake visuals and audio during live streams with the intention of misleading viewers and systems. In addition, such types of attacks have very serious consequences on the level of both the individual and the organization. Fraudsters then take advantage of general AI and third-party tools to create an attractive deepfake that looks and sounds like the person. It allows for reducing appearance barriers to fraud control, making it easier to access, closer to the user, and with low technical demands.

Working mechanism

The mechanism of a digital injection attack starts by inserting fake videos into the stream to impersonate someone. Such attacks can be made for a variety of reasons and are wrong, including but not limited to,

• Deceiving Identity Verification Systems
• Performing fraudulent transactions
• Misleading people at a video call by showing an improper view.

Deepfakes of social media platforms are simple, real-time deepfake injection attacks that are created and injected at fast speed during any live events. Live streams and video calls are the prime targets of such attacks, which require automation by experts and advanced methods to pull off successfully. Due to these kinds of warnings, most recent studies and reports teach developers to avoid injection attacks by improving the safety of video and image verification systems.  

AI Deepfakes Causes $25 Million Scams

A recent example is the case of British Engineering Group Arup, which lost up to $25 million. In this case, fraudsters managed to use AI-generated deepfakes to impersonate the group’s CFO during the video call conference. The case raises concern over how video injection attacks can be the cause of important financial scams and underlines the growing threat they pose to businesses worldwide.

Besides, the recent Biometric Update webinar showed how easily available software can manipulate people to believe that somebody is impersonating another person. This webinar’s poll also unveiled that every organization either had suffered from an injection attack or would suffer from it sooner or later. 

Selfie Verification Vulnerabilities Due to Deepfake Injection Attacks

Digital injection attacks are increasingly targeting selfie verification systems, thereby making identity verification methods more and more complex. In any case, such an attack manipulates safety gaps in recognition verification software, giving a chance for the attackers to detour checks by using AI-generated selfies that seem real. For instance, systems relying completely on liveness detection through video retention are risky since attackers can insert existing videos or images.

Besides that, the verification flow lets the user transfer images or videos instead of retaining them. It is specifically vulnerable to deepfake selfie verification attacks. This is one process where the attackers can use the latest deepfake technology and add fake documents and images.

This is now one of the main challenges for KYC systems and other verification mechanisms reliant on biometric data. In combat, identity verification facilitators are under compulsion to implement stronger safety estimations to check and protect against deepfake selfie verification frauds. 

Video Call and Video Injection Attacks

Remember the scene from Ocean’s Eleven, where Danny Ocean and his crew commit a robbery by splicing already-prepared footage of an empty vault onto the monitors displaying a live feed of a vault in the casino? The security team remained uninformed as they watched the mock footage while a robbery was ongoing.

This example serves to show what video injection attacks look like and their operating systems. Hollywood didn’t dream about video injection deepfakes, but they are real and gain more fame. These injections also involve the use of forged video footage within a live stream to deceive viewers or to fool security estimations. Companies should detect the types of breaches in their observation and data systems to protect them from deepfake injection attacks.

Types of Deepfake Injection Attacks

The injection attacks associated with identity verification can easily manipulate the methods of managing the application multimedia inserts like images, videos, and audio. Let’s discuss some of the important types of injection attacks in the below table:

Method to Protect & Fight Against DeepFake Injection Attacks

To fight against deepfake attacks, applications should execute strong input acceptance, clean all interactive media inputs, engage the safe information data to process multimedia files, and use extensive security estimations. Here are some important methods to protect and fight against injection attack detection: 

API Safety: 

The use of strong safety implementation to protect illegal API citations—could be utilized to insert hostile content. These safety measures involve API-key employment, and IP filtering, among different latest safety conventions. 

Online Camera Detection:

Also, the system can check if fake cameras have been used, such as virtual cameras. This capacity confirms that images or videos are inserted in the systems via virtual cameras as if they are retained by a real camera, identified, and blocked. 

Business Intelligence Techniques: 

There are more than one parameters that ensure the identity verification process’s integrity. However, these checks guarantee that methods are implemented alongside similar devices, protecting any proof from being directly inserted into the system. 

Deepfake Detection:

The employment of trained artificial algorithms to examine and check the images, videos, or voices that are artificially produced. However, these algorithms distinguish between real content from fake, guarantee that only real images, voices, and videos are handled. 

Ways to Businesses Can Prevent Deepfake Attacks

It is reported that $35 million audio deepfake scams occurred in 2020 revealing that deepfake technology endangering financial fraud. Furthermore, criminals are using deepfake systems to impersonate high-ranking officials, causing unlawful payments, and data breaches. However, these attacks shelter the real systems, for instance, facial and voice recognition underlining the deepfake fraud protection significance. Deepfakes are now more accessible, and companies need to adopt secure measurements to protect such warnings. 

Tips to Mitigate These Attacks

Deepfake injection attacks have currently started targeting businesses. Now, let’s discuss some of the preventative measures that protect businesses from deepfake attacks:

Final Thoughts

Moreover, these deepfake injection attacks are rapidly growing while highlighting some of the important concerns about biometric systems. However, FACIA technology prevents institutes, government organizations, social forums, and independent companies from deepfakes. Technology is believed to be among the most exact, which leads to perfect industries in detecting deep fake videos and images. Such technologies can check minor details, such as eye and lip movement, facial shadows, and surrounding reflections.