Don’t Be Fooled: 5 Strategies to Defeat Deepfake Fraud

It sounds like science fiction, but AI-created videos and audio fool employees into sending millions to scammers. For companies today, this isn’t fantasy, it’s a new reality. Digital technologies are on the ascendancy. While Deepfake technology is doing wonders in creative industries it is becoming a tool at the hands of criminals using it for malicious purposes. Hence it  is becoming a serious cyber menace. AI-created videos and audio recordings can impersonate real individuals with uncanny accuracy, making them nearly indistinguishable from authentic communication.

The distinctive threat of deepfakes lies in their dual nature:

• Firstly, deepfakes are utilized for social engineering and misinformation. This is accomplished by mimicking familiar faces and voices to deceive employees into performing risky tasks such as money transfers and posting disinformation on social media
• Secondly, they are used to spoof identity verification systems by bypassing facial recognition and biometric security systems. The risk of such identity proofing measures is higher in remote identity proofing.

Businesses need to ensure security against both of these risks by assessing their vulnerability. 

The Following are five strategies that are like a shield against both types of deepfake fraud, with some real-world implementation.

The First three strategies are aimed at countering and detecting deepfakes employed to disseminate misinformation, the remaining two strategies are aimed at detecting and preventing deep fakes powered spoofing attacks launched at identity verification systems.

1. Deepfake Awareness Training 

Technology alone will not rescue a business if its people don’t know about impending threats. The staff need to be educated to identify voice or video communication anomalies. In the case where most of the cybercriminals have been using deepfake audio or videos, they pretend to be senior executives to manipulate employees into sharing sensitive data or making urgent payments.

Companies have to create deepfake awareness training across teams via:

• Quarterly training with simulated deepfakes employed to spread misinformation
• Distributing current threat bulletins by email or internal sites.
• Also, establishing a feedback loop allowing suspicious messages to be reported without retribution.

2. Restrict Informal Communication for Official Transactions

Very often deepfake attacks are executed through informal, unsolicited messages, such as WhatsApp texts from the CEO or a voice note from an external legal consultant. These communication channels are hard to secure and simple to spoof.

Proofpoint reported a case where An international manufacturing firm had a policy against granting requests through personal emails or messaging services. When an impersonator tried to fake a board member’s voice through an email spoof, the request was disregarded and escalated due to protocol.

These restrictions on informal communication should be followed by:

• Using official channels for communication.
• Mandating policies against the use of personal communication tools for company business.
• Regularizing audit executives’ communications for irregularities.
• Promoting the use of visual deepfake detection software in E-meetings to assist in the detection of impersonation attempts.

3. Minimize Executive Media Exposure 

Deepfakes require training data: huge collections of authentic images, videos, or audio files that train AI systems to learn the way a person’s  face, voice, or expression can be imitated.  Public video or audio recordings of executives provide an easier target for attackers to copy faces and voices.

The deepfake threat can be mitigated by minimizing executives’ media exposures and protecting public content by : 

• Reviewing online content with company leadership
• Adding Watermark or use dynamic backgrounds for videos
• Asking executives to break up static speaking habits and background silence.
• Using the  deepfake detection tools to detect possible  fake  and manipulated videos of executives on various public forums.

4. Implement Multi-Factor Authentication(MFA) with Facial Biometric

Deepfake scams are successful in the  cases when an employee rushes to act on a voice or video message from a senior executive. If an attacker can fake an identity, the whole system collapses. Multi-factor authentication is strengthened by facial biometrics.

Multi-factor authentication using facial biometrics can be ensured by: 

• Integrating facial biometrics as a part of MFA
• Enforcing secondary approvals on large-value transfers or sensitive requests.
• Enforcing MFAs with facial biometric solutions such as Liveness detection
• Establishing high-risk requests that always require multi-layer authentication.

5. Implement AI-powered deepfake detection tools

AI-created media is usually unperceivable by the human eye or ear. Detection tools examine voice patterns, eye movement, and pixel irregularities to identify fake content in real time.

 To mitigate AI-powered deepfake detection, it is necessary to : 

• Implementing AI filters to screen voice calls and video messages with sensitive requests
• Tracking internal communications for out-of-pattern biometric signals.
• Integrating detection technology in the endpoint security or communications stack.

How Facia Future-Proofs Your Business from Deepfake Fraud

As the deepfake technology keeps evolving, the threats related to it are also increasing. Businesses need to evaluate the capacity in which they may face deepfake threat. Facia provides exactly that.

Facia brings together  liveness detection and industry-leading Face accuracy to prevent deepfakes from detecting deepfake videos used in whaling attacks and successfully detects deepfake attacks during Remote Identity Verification.

Facia ensures accurate identity verification for sectors requiring higher levels of assurance in authentication by minimizing   less than 1%  False Rejection Rate (FRR) and False Acceptance Rate(FAR) of almost 0%  to optimum levels. Which ensures each identity is confirmed accurately. 

Facia’s higher level of assurance in offsite deepfake detection coupled with advanced 3d liveness detection for remote identity verification provides a strong safeguard for detecting deep fakes during E-meetings. 

Further, its accuracy in deepfake detection, as proven, is a strong defense. Facia’s algorithm has been tested on Meta’s DFDC dataset and it showed 100% accuracy, whereas the in-house dataset, the accuracy achieved was 89.01%. ensures prevention of misinformation through deepfakes helping businesses comply with Anti-Deepfake laws.

With Facia , organizations can stay one step ahead of emerging threats , and save billions in scams and keep their reputation intact. 

In a time when  seeing isn’t always believing, Facia’s deepfake detection and deepfake attack detection tools help prevent misinformation and secure remote identity verification processes.