Abstract: A method for enhancing detection of fraudulent authentication data is provided that includes obtaining within a window of time from one or more sensors a plurality of signals. Each signal includes data for a biometric modality of a person. Moreover, the method includes determining whether the biometric modality data in the obtained signals was captured contemporaneously. If so, a feature vector is computed for the biometric modality data in each of the plurality of signals, each feature vector is encoded into a corresponding qubit register using an encoding algorithm, and a multi-qubit entangled state is generated from the qubit registers. An entanglement indicator value is also generated for the multi-qubit entangled state and the entanglement indicator value is compared against a threshold value. When the entanglement indicator value satisfies the threshold value, the obtained biometric modality data is determined to be of a live person.

Abstract: A method for enhancing detection of morphed biometric modality data is provided that includes the steps of receiving, by an electronic device, biometric modality data of a person and extracting, using a trained machine learning model operated by the electronic device, high dimensionality feature vectors from the received biometric modality data. Moreover, the method includes the steps of generating a distribution from the high-dimensionality feature vectors, calculating a deviation between the generated distribution and a corresponding record high-dimensionality feature vector distribution of the person, and comparing the calculated deviation against a threshold deviation value. In response to determining the deviation satisfies the threshold deviation value, the method includes the step of determining the received biometric modality data was morphed.

Abstract: A method of maintaining behavioral integrity of an artificial intelligence (AI) agent includes capturing AI agent execution signals. The AI agent is bound to a person. Moreover, the method includes calculating similarity scores from the execution signals and an agent similarity score from the similarity scores, verifying runtime attestation of an execution environment hosting the artificial intelligence agent, and calculating an attestation conformity score from the runtime attestation. Furthermore, the method includes calculating an integrity score by combining the similarity and attestation conformity scores and evaluating policy-as-code at one or more policy checkpoints to yield a decision outcome. The policy checkpoints include discover, invoke, and runtime. The method also includes comparing the integrity score against a threshold value.

Abstract: A method for enhancing detection of multimedia data generated using artificial intelligence is provided that includes the step of receiving, by an electronic device operated by a user, multimedia data. The multimedia data includes at least one of one or more images and voice data. Moreover, the method includes the step of analyzing, using a trained machine learning model, the one or more images for artifacts indicating the use of artificial intelligence in generating the one or more images, and determining, using a synthetic speech detection algorithm, whether the voice data includes artifacts indicating the use of artificial intelligence in generating the voice data. In response to determining the one or more images includes at least one artifact or the voice data includes at least one artifact, the multimedia data is determined to be fraudulent and originating from artificial intelligence generation.

Abstract: A method for enhancing the security of voice biometric data is provided that includes receiving, by an electronic device, voice biometric data of a user captured while the user was speaking and analyzing the context in which the received voice biometric data was captured. The context includes environmental and situational factors. The method also includes analyzing characteristics of the received voice biometric data to detect anomalies associated with synthetic speech, and conducting a biometric authentication transaction based on the voice biometric data in response to determining the received voice biometric data is free of anomalies. In response to successfully authenticating the user, the method includes updating record voice biometric data of the user with the received voice biometric data. Moreover, the method includes modifying the updated record voice biometric data and securely storing the modified updated record voice biometric data.

Abstract: A method for enhancing detection of morphed biometric modality data is provided that includes receiving, by an electronic device, biometric modality data of a person, extracting feature vectors from the biometric modality data, normalizing the feature vectors, encoding the normalized feature vectors into qubits, and expanding, using at least one quantum algorithm, the normalized feature vectors into a high-dimensional space. Moreover, the method includes generating a distribution from the high-dimensional space based on the qubits, calculating a deviation between the generated distribution and a corresponding record high-dimensionality feature vector distribution of the person, and comparing the calculated deviation against a threshold deviation value. In response to determining the deviation satisfies the threshold deviation value, the method determines the received biometric modality data was morphed.

Abstract: A method of maintaining fidelity of a bond between a person and an artificial intelligence agent bound to the person includes capturing data for behavioral modalities of a person, calculating a score for each behavioral modality, calculating a similarity score from the calculated scores, and comparing the similarity score against the threshold value. In response to determining the similarity score fails to satisfy the threshold value, the method substitutes a snapshot of a Baseline Persona Model of the person for the Baseline Persona Model. The Baseline Persona Model is a machine learning model that encodes the behavioral modality data of a person over time. The snapshot is a copy of the Baseline Persona Model at an instant in time. Subsequently data for the behavioral modalities of the person is captured over time. The Baseline Persona Model is retrained using a set of the subsequently captured data approved by the person.

Abstract: A method for enhancing detection of fraudulent authentication data includes receiving, by an electronic device, data during an authentication transaction, computing a feature vector from the received data, and normalizing the feature vector. The method also includes encoding the normalized feature vector into qubits, expanding, using at least one quantum algorithm, the normalized feature vector into a high-dimensional space, and detecting in the high-dimensional space anomalies indicative of fraud based on the qubits. Furthermore, the method includes calculating, based on the detected anomalies, a confidence score reflecting a likelihood that the received data is genuine and comparing the confidence score against a threshold value. In response to determining the confidence score fails to satisfy the threshold value, the method determines that the received data requires secondary authentication.

Abstract: A method for enhancing detection of multimedia data generated using artificial intelligence is provided that includes the step of receiving, by an electronic device operated by a user, multimedia data. The multimedia data includes at least one of one or more images and voice data. Moreover, the method includes the step of analyzing, using a trained machine learning model, the one or more images for artifacts indicating the use of artificial intelligence in generating the one or more images, and determining, using a synthetic speech detection algorithm, whether the voice data includes artifacts indicating the use of artificial intelligence in generating the voice data. In response to determining the one or more images includes at least one artifact or the voice data includes at least one artifact, the multimedia data is determined to be fraudulent and originating from artificial intelligence generation.

Abstract: The present disclosure provides a method for determining the authenticity of an identity document that includes receiving, by an electronic device, an image of an identity document. The document image includes facial image data and personal data of a person associated with the identity document and an identity document number. Moreover, the method includes extracting the personal data and the document number from the identity document image. The extracted personal data includes at least a surname and the extracted identity document number includes groups of characters that represent personal data and information about an entity. Furthermore, the method includes decoding a first group of the characters using a soundex coding algorithm, identifying a surname that corresponds to the decoded first group of characters, comparing the identified surname against the surname in the extracted personal data, and determining the authenticity of the identity document using a result of the comparison.

Abstract: A method for enhancing detection of synthetic voice data is provided that includes converting, by an electronic device, monophonic voice data into stereophonic voice data. The stereophonic voice data includes a first channel signal and a second channel signal. Moreover, the method includes decomposing, by a trained machine learning model, the stereophonic voice data into a mid-signal and a side signal. The method also includes determining artifacts indicative of synthetic generation in the structured and secondary artifacts, calculating, based on the determined artifacts, a probability score reflecting the likelihood the monophonic voice data was synthetically generated, and comparing the probability score against a threshold value. When the probability score satisfies the threshold value, there is a high likelihood that the monophonic voice data includes synthetic artifacts, and an alert is generated indicating the monophonic voice data is potentially fraudulent.

Abstract: The present disclosure provides a method for determining the authenticity of an identity document that includes receiving, by an electronic device, an image of an identity document. The document image includes facial image data and personal data of a person associated with the identity document and an identity document number. Moreover, the method includes extracting the personal data and the document number from the identity document image. The extracted personal data includes at least a surname and the extracted identity document number includes groups of characters that represent personal data and information about an entity. Furthermore, the method includes decoding a first group of the characters using a soundex coding algorithm, identifying a surname that corresponds to the decoded first group of characters, comparing the identified surname against the surname in the extracted personal data, and determining the authenticity of the identity document using a result of the comparison.

Abstract: A method for determining the authenticity of an identity document is provided that includes capturing, by an electronic device, image data of an identity document. The identity document has a first side and a second side. The image data includes an image of the first side and an image of the second side. The first side includes data about a person associated with the identity document and second side includes a PDF417 barcode which has features. The method also includes determining a class of the identity document. The features of the PDF417 barcode adhere to criteria established for the determined class of the identity document. Moreover, the method includes analyzing the features of the PDF417 barcode for anomalies. In response to determining the features of the PDF417 barcode are free of anomalies, the identity document is determined to be authentic. Otherwise, the identity document is determined to be fraudulent.

Abstract: A method for enhancing liveness detection of image data is provided that includes receiving image data of a person and using multi-resolution convolution and octave convolution techniques to extract first and second frequency components from the received image data. The method also includes comparing the first frequency component against data in a first frequency map and comparing the second frequency component against data in a second frequency map. Furthermore, the method includes determining whether the first frequency component satisfies matching criteria with data in the first frequency map and determining whether the second frequency component satisfies matching criteria with data in the second frequency map. In response to determining the first and second frequency components fail to satisfy the data in the respective frequency map, the method concludes that the received image data was not taken of a live person.

Abstract: A method for enhancing user liveness detection is provided that includes receiving image data of a user that includes items of metadata. Moreover, the method includes comparing each item of metadata associated with the received image data against a corresponding item of metadata associated with record image data of the user, and determining whether each item of metadata associated with the received image data matches the corresponding item of metadata. In response to determining at least one item of metadata associated with the received image data does not match the corresponding item of metadata, the method deems the received image data to be genuine and from a live person. In response to determining all items of metadata associated with the received image match the corresponding item of metadata, the method deems the received image data to be fraudulent and not from a living person.

Abstract: A method for determining the authenticity of an identity document is provided that includes capturing, by an electronic device, image data of an identity document, determining a class of the identity document, and extracting, using multi-resolution convolution and octave convolution techniques, first and second frequency components from the captured image data. The first and second frequency components correspond to different spatial frequency ranges. Moreover, the method includes determining whether the first and second frequency components satisfy matching criteria with data in corresponding frequency maps. The frequency maps are created from verified documents belonging to the determined class of document. In response to determining at least one of the first and second frequency components satisfies the matching criteria, determining the identity document is genuine.

Abstract: A method for determining the authenticity of an identity document is provided that includes the steps of capturing, by an electronic device, image data of a PDF417 barcode, where the PDF417 barcode is located on an identity document including textual data. Moreover, the method includes the steps of extracting data from the PDF417 barcode, determining a class to which the identity document belongs using the extracted data, and identifying in the extracted data, data unique to the determined class. The unique data is in addition to the textual data. Furthermore, the method includes the steps of comparing the identified unique data against unique data of any authenticated identity document belonging to the determined class, calculating an authenticity score based on the comparison, and determining the identity document is authentic in response to determining the authenticity score satisfies a threshold score.

Abstract: A method for determining the authenticity of an identity document is provided that includes capturing, by an electronic device, image data of an identity document. The identity document has a first side and a second side. The image data includes an image of the first side and an image of the second side. The first side includes data about a person associated with the identity document and second side includes a PDF417 barcode which has features. The method also includes determining a class of the identity document. The features of the PDF417 barcode adhere to criteria established for the determined class of the identity document. Moreover, the method includes analyzing the features of the PDF417 barcode for anomalies. In response to determining the features of the PDF417 barcode are free of anomalies, the identity document is determined to be authentic. Otherwise, the identity document is determined to be fraudulent.

Abstract: A method for determining the authenticity of an identity document is provided that includes capturing, by an electronic device, image data of an identity document. The identity document has a first side and a second side. The image data includes an image of the first side and an image of the second side. The first side includes data about a person associated with the identity document and second side includes a PDF417 barcode which has features. The method also includes determining a class of the identity document. The features of the PDF417 barcode adhere to criteria established for the determined class of the identity document. Moreover, the method includes analyzing the features of the PDF417 barcode for anomalies. In response to determining the features of the PDF417 barcode are free of anomalies, the identity document is determined to be authentic. Otherwise, the identity document is determined to be fraudulent.

Abstract: The present solution is directed to methods and systems for storing personal identifiable information. In some implementations, the information is collected during the authentication of identification (ID) documents. The personal identifiable information can be useful in processes such as client enrollment, mobile device management, identification processes, and transaction audits. However, the data can be a target for bad actors. The present solution includes a one-way hashing and cryptographic function that converts unique personal identifiable information into a unique digest which can be securely stored on a mobile device and rendered as an original state digital image for proof of ID.