What is audio deepfake detection?
Deepfakes pose a serious threat to cybersecurity. Companies are scrambling to protect their customers’ data against such emerging threats. That’s why deepfake detection has become of paramount importance, especially in industries where customer authentication is necessary, such as contact centers.
Given the inherent risks related to identity verification in contact centers, it’s become quite important for organizations to protect themselves by using audio deepfake detection techniques.
The looming threat of audio deepfakes
An audio deepfake is the replication and manipulation of a person’s vocal likeness to make it appear as if that person is saying something they never actually did.
The technology behind audio deepfakes relies on sophisticated machine learning algorithms, particularly deep learning models like Generative Adversarial Networks (GANs).
Using a sufficient amount of audio data from the targeted individual, these models can be trained to generate new audio that mimics the person’s unique vocal characteristics, intonations, and speech patterns.
Once generated, these deepfakes can be incredibly convincing, posing risks in various domains like politics, finance, and personal security.
In fact, there’s a very real risk that someone could create an audio deepfake of an individual’s voice, and use that to gain access to their personal accounts. For contact centers that don’t have a sound strategy against deepfakes, this could be a serious problem.
Interest in audio deepfake detection continues to rise. At Pindrop, we understand the concerns of our clients, and offer audio deepfake detection with PindropⓇ PulseTM technology.
How audio deepfake detection works
Deep learning analysis
Deep learning imitates the way that humans think using multi-layered neural networks. As IBM explains, “‘Nondeep,’ traditional machine learning models use simple neural networks with one or two computational layers. Deep learning models use three or more layers—but typically hundreds or thousands of layers—to train the models.” These models can be taught to detect genuine and synthetic audio, which can help detect fraudulent behavior.
Biometric voice analysis
A person’s voice is made up of an array of attributes, like sound waves, pitch, and speech patterns. According to the Biometric Institute, “These elements enable [a] system to create a reference template of the voice (known as a ‘voice print’ or ‘voice model’) that can be used to authenticate the speaker in subsequent transactions.” In the case of deepfakes, biometric voice analysis can be used to determine if the voice is human or synthetic–helping spot potentially fraudulent behavior.
Understanding audio deepfake detection technology
Audio deepfakes are often created using AI, which means that AI can often be used to spot these instances of synthetic speech.
The impact of audio deepfakes on businesses
As deepfakes rise and evolve, the impact on businesses continues to grow. It’s imperative to stay up-to-date on the latest tactics employed by fraudsters, so you implement measures to help protect your business.
Impersonation fraud
Impersonation of large businesses and government agencies is “one of the top frauds reported to the FTC’s Consumer Sentinel Network,” according to a recent article by the Federal Trade Commission. The FTC also warned that losses from this type of fraud reached over $1.1 billion in 2023 alone.
Social engineering attacks
Social engineering attacks use human psychology to deceive individuals into exposing personal information or compromising security. Fraudsters may use audio deepfakes to impersonate trusted individuals, making it easier to carry out deception.
Disruption of operations
Audio deepfakes of organizations can cause disruption in business operations, as resources are diverted to verifying the authenticity of different pieces of communication.
Brand damage
Brand reputation and customer trust can be seriously compromised when business executives’ voices are impersonated and made to say false or misleading statements. This can have long-term consequences on brand credibility and customer loyalty.
Financial fraud
Replicating the voice of a person–whether a consumer or a public figure–leaves the door open for fraudsters to trick and deceive individuals into giving personal information that compromises security to financial accounts. Recovering from a deepfake incident can also be costly.
Learn about PindropⓇ PulseTM technology today and help combat deepfakes
Pindrop Pulse technology and Pindrop Pulse Inspect are solutions that combat the damaging effects of rising deepfakes. To learn more about our product suite, request a demo.
