With the help of today’s technology, virtually anyone can create a passable deepfake—a manipulated image, video, or audio recording that seems real. All that is required is a consumer-grade computer or smartphone and an internet connection. Without question, we are fast approaching an era where audiovisual content is no longer inherently trustworthy.
In fact, a recent Dimension Market Research report reveals that the global deepfake AI market is expected to reach a value of $79 million by the end of this year, and a market value of nearly $1.4 million by 2033.
Damages Posed by Deepfakes
Undetected deepfakes can be used in multiple ways to target and compromise businesses, spread misinformation, disrupt markets, business operations, and supply chains. For example, they can be used to impersonate executives in fake video calls, or audio recordings, tricking employees into taking action, like revealing sensitive information or transferring funds. Deepfakes can also be used to generate phony social media content intended to damage a company, its reputation, or stock price, or to doctor product images and videos as part of counterfeiting operations. In addition, they can be used to make fraudulent transactions by spoofing biometric security systems with fake facial impressions and voice prints as well as synthetic identities. These events threaten privacy and security by enabling fraudulent accounts and transactions.
The potential financial and reputational damage posed by deepfakes is significant. Fraudulent wire transfers from a single deep-faked executive video could cost a business millions of dollars. And viral, deep-faked social media posts could undermine consumer trust and market value.
One particularly alarming example of a successful deepfake attack occurred at an international company based in Hong Kong. According to an article in the South China Morning Post, attackers successfully stole $25 million from the company by organizing a video meeting that was faked using deepfake technology. A company employee received a phishing email from the CFO (so he thought), requesting a funds transfer. Thinking it was legitimate, the employee was tricked into joining a video call, which included the employee and deepfaked versions of the other participants, including the fake CFO, who instructed the employee on how to make 15 different transfers totaling $25 million. Unfortunately, it took several days for the employee to realize the entire event was a scam.
Keys to Defense: Swift Decisive Actions
While deepfakes might seem impossible to identify on the surface, there are several ways to spot them.
AI-based detection systems can identify fakes across large datasets by analyzing unusual movements, visual artifacts, audio distortions, contextual inaccuracies, and other signatures. However, it remains an arms race as deepfake creators learn to overcome imperfections. Some experts estimate detectors will be unreliable within 12-18 months.
Metaphorically, spotting deepfakes is like playing the world’s most challenging game of “spot the difference.” The fakes have become so sophisticated that the inconsistencies are often nearly invisible, especially to the untrained eye. It requires constant vigilance and the ability to question the authenticity of audiovisual content, even when it looks or sounds completely convincing.
Recognizing threats and taking decisive actions are crucial for mitigating the effects of an attack. Establishing well-defined policies, reporting channels, and response workflows in advance is imperative. Think of it like a citywide defense system responding to incoming missiles. Early warning radars (monitoring) are necessary to detect the threat; anti-missile batteries (AI scanning) are needed to neutralize it; and emergency services (incident response) are essential to quickly handle any impacts. Each layer works in concert to mitigate harm.
It’s important to take a multi-pronged approach when dealing with deepfakes. An effective strategy should include employee training in awareness and identification and strict authentication measures for sensitive requests. It should also include designated secure channels for executive communications, monitoring for suspicious assets, AI-based scanning of incoming media content, and a healthy incident response plan. The key is to act swiftly and decisively.
Reversing Deepfake Damage
If a deepfake attack succeeds, organizations should immediately notify stakeholders of the fake content, issue corrective statements, and coordinate efforts to remove the offending content. They should also investigate the source, implement additional verification measures, and provide updates to rebuild trust and consider legal action. It’s crucial for leadership to get ahead of the narrative. They must be transparent and accountable and take concrete corrective actions to mitigate long-term financial loss and reputational harm.
The more that false information goes unchecked, the more damage it can do. Having a rapid response playbook ready is essential to a good defense.
The Future of Audio and Visual Communications
In addition to direct attacks, enterprises must also prepare for deepfakes to be weaponized across other domains, such as politics, regulations, and social unrest. Deepfakes not only raise security concerns but also pose harmful enterprise risks.
As synthetic media becomes more widespread, video and audio may lose their inherent credibility. Consequently, enterprises need to shift communication and authentication approaches, relying less on audiovisual content and more on cryptographically secure channels.
It’s important to note, however, that not all synthetic media is malicious. For instance, “Shallowfakes” and virtual avatars are being adopted more often for legitimate uses in industries like entertainment and education. Regardless, as generative AI technologies become more and more sophisticated, companies should act now to establish explicit policies that distinguish between permissible and prohibited uses.
About the Author
Arik Atar is a senior threat intelligence researcher at Radware, where he helps identify security vulnerabilities, thwart attacks in real time, and proactively mitigate potential attacks for clients. He brings a wealth of experience in cyber threat hunting, combining strategic cyber threat analysis with social psychology. Before Radware, Arik worked at PerimeterX, where he focused on researching underground bot-for-hire marketplaces, leveraging his expertise in threat hunting to mitigate Denial-Of-Inventory and Account-Take-Over attacks. Before that, he joined Bright Data where he led investigations against high-profile proxy users, uncovering and addressing cyber adversaries’ tactics, particularly in DDoS and bot attacks. Arik has delivered keynote speeches at conferences such as Defcon, APIParis, and “The-Fraud -Fighters’ Cyber Defenders” meetups. Arik studied counterterrorism and international relations at IDC University, which assisted in shaping the strategic macro perspective he uses in threat actor research.
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