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ANALYSIS sample , liveness detection technology helps defend against deepfake attacks and ensures the integrity of the authentication process .
• Behavioural biometrics : This involves analysing patterns in an individual ’ s behaviour , such as typing speed , mouse movements and swipe patterns on a touchscreen device . These behavioural patterns are unique to each individual and can be used to verify their identity . When applied to deepfake detection , behavioural biometrics can help identify anomalies in user behaviour that may indicate a video or image has been manipulated .
• Voice recognition : By analysing various aspects of a person ’ s voice , such as volume , tone and cadence , voice recognition systems can verify the validity of an identity . In the context of deepfake detection , this method can help identify unnatural or inconsistent speech patterns that may indicate a video or audio recording has been manipulated .
Deepfakes can be weaponised in disinformation campaigns to manipulate public opinion .
• Multimodal biometrics : This involves combining multiple biometric authentication methods to increase security . By using a combination of facial recognition , voice recognition and behavioural biometrics , for example , it is possible to achieve a more robust defence against deepfake threats . By requiring multiple forms of biometric authentication , these systems can make it more difficult for malicious actors to create convincing deepfakes .
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