Bank of america corporation (20240346240). Personal Data Discovery simplified abstract
Contents
Personal Data Discovery
Organization Name
Inventor(s)
Moncef El Ouriaghli of Charlotte NC (US)
Nishitha Kakani of Mint Hill NC (US)
Sriram Mohanraj of Charlotte NC (US)
Yanghong Shao of Charlotte NC (US)
Timothy L. Atwell of Huntersville NC (US)
Personal Data Discovery - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240346240 titled 'Personal Data Discovery
The abstract of the patent application describes a computer-implemented process using artificial intelligence to predict whether personal data may be present in structured software based on metadata fields.
- Natural language processing is used to preprocess input strings corresponding to metadata fields into normalized input sequences.
- Individual characters in the sequences are embedded into fixed-dimension vectors of real numbers.
- Bidirectional LSTM or other machine-learning algorithms generate forward and backward contextualizations.
- Neural network outputs are provided based on element-wise averaging or feed forwarding to predict if value fields may contain personal data.
Potential Applications: - Data privacy protection in software systems - Compliance with data protection regulations - Automated data classification and identification
Problems Solved: - Identifying personal data in structured software - Enhancing data security measures - Streamlining data processing workflows
Benefits: - Improved data privacy and security - Efficient data classification and management - Enhanced compliance with data protection laws
Commercial Applications: Title: "AI-Powered Data Privacy Solution for Software Systems" This technology can be used by software companies, data management firms, and organizations handling sensitive information to ensure compliance with data protection regulations and enhance data security measures.
Questions about the technology: 1. How does this technology compare to traditional methods of identifying personal data in software systems? 2. What are the potential limitations of using artificial intelligence for data privacy protection in software?
Original Abstract Submitted
artificial-intelligence computer-implemented processes and machines predict whether personal data may be present in structured software based on metadata field(s) contained therein. natural language processing preprocesses input strings corresponding to the metadata field(s) into normalized input sequence(s). individual characters in the sequence(s) are embedded into fixed-dimension vectors of real numbers. bidirectional lstm(s) or other machine-learning algorithm(s) are utilized to generate forward and backward contextualization(s). neural network output(s) are provided based on element-wise averaging or feed forwarding based on the contextualization(s) in order to predict whether one or more value fields corresponding to the metadata field(s) may contain personal data.
