TECHNICAL FIELD

This disclosure relates generally to information security. More specifically, this disclosure relates to a user security profile for multi-media identity verification.

BACKGROUND

User authentication may be requested before a user is granted access to secure information and/or services. The purpose of user authentication is to determine that the user is an authorized individual who should be granted access to the secure information and/or services. For example, a user may be requested to provide a username and password to access a secure service. Additionally, biometric features—visual appearance, voice, fingerprint etc.—that are unique to a user may be used to authenticate a user's identity. When prompted, the user may record a video, submit a photo, or record an audio message for the computer to analyze and compare with the authentic user's features.

The use of many such authentication mechanisms is complicated by the rise of synthetic media (i.e., media that is artificially produced, manipulated, and/or modified). Synthetic media can be used to fool biometric authentication mechanisms by inputting a computer-generated media sample instead of actually recording information related to the individual trying to bypass the authentication mechanism. Synthetic media, often referred to as “deepfakes,” are generated using generative machine learning. The algorithms employed improve at a rapid pace, making it more difficult to distinguish deepfakes from authentic media.

SUMMARY OF THE DISCLOSURE

According to one embodiment, a system includes a memory and a processor. The memory is configured to store a hash function. The hash function is configured to generate hash values based on one or more elements of a media sample. The processor is configured to receive a media sample. The processor is further configured to identify a critical portion of the media sample. The critical portion of the media sample is a segment of the media sample that a user has designated to be used as a unique identifier of the user. The processor is also configured to split the media sample into a verification sample. The verification sample is a subset of the media sample that comprises the critical portion of the media sample. The processor is also configured to decompose the verification sample into a first and second layer. The first layer comprises a first separable code element of the verification sample. The second layer comprises a second separable code element of the verification sample. The processor is further configured to generate a first hash value based on the first layer by applying the hash function to the first separable code element of the verification sample. Additionally, the processor is configured to generate a second hash value based on the second layer by applying the hash function to the second separable code element of the verification sample. The processor is then configured to generate a blockchain transaction comprising a profile associated with the user. The profile includes the first and second hash values. Finally, the processor is configured to store the blockchain transaction as a block in a blockchain ledger.

Certain embodiments provide one or more technical advantages. As an example, an embodiment improves the accuracy of an authentication method by enabling multi-layer analysis of input media samples. Simple single-layer analysis of media samples is more likely to miss subtle differences between synthetic media and genuine samples that the synthetic media aims to replicate. Additionally, some embodiments generate a unique signature that can be stored in a blockchain ledger. The signature comprises selected portions of a media sample that are designated as critical, and authentication requires comparing the selected portions of the media to reference data that only matches those portions of the media sample. Thus, even if a synthetic media sample were to achieve perfect matching with reference media, the authentication sample would ferret out an entity submitting the synthetic media sample because the authentication system would require the entity to select a portion of their submitted media sample that correlates precisely with the reference media sample. As another example, an embodiment is capable of detecting differences between synthetic media and a reference media sample by comparing hash values generated from the two media samples. If any portion of the media samples deviate from each other, then the hash values will not match.

The system described in this disclosure may be integrated into a practical application of an identity verification tool to limit access to physical locations, electronic data, online user accounts, or individual internet transactions. For example, the disclosed system may be integrated into an authentication mechanism for logging into a user account for a mobile application. Additionally, the disclosed system may be deployed as a second authentication factor in a two-factor authentication scheme. The disclosed system and methods may further be deployed to verify individual internet data transfers by using camera and microphone inputs of a user device to observe who is making the transaction and confirm that synthetic media is not being submitted to circumvent the authentication measures.

Certain embodiments of this disclosure may include some, all, or none of these advantages. These advantages and other features will be more clearly understood from the following detailed description taken in conjunction with the accompanying drawings and claims.

