| CPC G06F 21/31 (2013.01) | 20 Claims |
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1. A method for authenticating digital data against manipulations, the method comprising the steps of:
receiving digital data from users through an omnichannel input process, wherein the digital data includes at least one of a video file, an audio file, or a textual content file, the omnichannel input process facilitating reception of data via various platforms including mobile applications, Internet of Things (IoT) devices, web interfaces, and online services, thereby accommodating a broad spectrum of user interaction modes;
standardizing format of the received digital data for analysis through a preprocessing process, including operations such as converting formats to a unified standard format, adjusting resolution to meet analysis requirements, filtering noise to enhance clarity, and segmenting the data into manageable parts for efficient processing, thereby preparing the data for detailed analysis;
associating preprocessed digital data with a unique smart contract to secure data integrity and authenticity throughout an authentication process, using a smart contract association process that involves generating a unique identifier for the data via cryptographic hashing and embedding this identifier within a blockchain-based smart contract, ensuring an immutable record of the data's authenticity;
retrieving historical data corresponding to the user or type of digital data for use as a benchmark in the authentication process, through a historical data retrieval process that leverages content delivery networks (CDNs) and optimized data storage solutions to quickly access extensive datasets of authenticated data, providing a robust framework for comparison;
generating an engineered mesh representation of the preprocessed digital data, mapping out key features and expressions pertinent to the data's authenticity, using an engineered mesh generation process that creates a detailed structural model for video data or a spectral graph for audio data, enabling a comprehensive analysis of data originality;
extracting specific features from the engineered mesh for manipulation detection analysis, using a feature extraction process that employs deep neural networks to identify and isolate features indicative of potential manipulations, focusing on anomalies in facial expressions, voice modulation, and textual consistency;
comparing the extracted features against the historical data and identifying discrepancies indicative of manipulations through a manipulation detection analysis process, utilizing advanced artificial intelligence (AI) and machine learning models trained on datasets of both authentic and manipulated content, ensuring high accuracy in detecting deepfake technology and other forms of digital tampering;
reinterpreting the features or expressions of the digital data in various contexts to uncover subtle manipulations, through a model paraphrasing process that includes linguistic analysis for textual data and dynamic analysis for video and audio data, allowing for the detection of manipulations that may not be apparent in a static analysis;
making a decision on the authenticity of the digital data based on the manipulation detection analysis and model paraphrasing, using an authentication decision process that incorporates a confidence scoring mechanism to evaluate a degree of similarity between current data and historical benchmarks, setting thresholds for automatically flagging potential manipulations;
updating the associated smart contract with the outcome of the authentication decision, securing a record of the process and its result, through a smart contract update process that includes recording the decision on the blockchain, thereby ensuring transparency and non-repudiation of the authentication outcome; and
outputting the authentication decision and triggering security protocols if manipulation is detected, using an output process that involves notifying the user via multiple communication channels, including email and SMS, and implementing a multi-factor authentication process to verify user identity and intent, ensuring a secure and user-informed response to detected manipulations.
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