SYSTEM AND METHOD FOR RANDOM-ACCESS MANIPULATION OF COMPACTED DATA FILES

    公开(公告)号:US20220335014A1

    公开(公告)日:2022-10-20

    申请号:US17734052

    申请日:2022-04-30

    Abstract: A system and method for random-access manipulation of compacted data files, utilizing a reference codebook, a random-access engine, a data deconstruction engine, and a data deconstruction engine. The system may receive a data query pertaining to a data read or data write request, wherein the data file to be read from or written to is a compacted data file. A random-access engine may facilitate data manipulation processes by accessing a reference codebook associated with the compacted data file, a frequency table used to construct the reference codebook, and data query details. A data read request is supported by random-access search capabilities that may enable the locating and decoding of the bits corresponding to data query details. A random-access engine facilitates data write processes. The random-access engine may encode the data to be written, insert the encoded data into a compacted data file, and update the codebook as needed.

    System and method for data compaction and security using multiple encoding algorithms

    公开(公告)号:US11385794B2

    公开(公告)日:2022-07-12

    申请号:US17404699

    申请日:2021-08-17

    Abstract: A system and method for encoding data using a plurality of encoding libraries. Portions of the data are encoded by different encoding libraries, depending on which library provides the greatest compaction for a given portion of the data. This methodology not only provides substantial improvements in data compaction over use of a single data compaction algorithm with the highest average compaction, but provides substantial additional security in that multiple decoding libraries must be used to decode the data. In some embodiments, each portion of data may further be encoded using different sourceblock sizes, providing further security enhancements as decoding requires multiple decoding libraries and knowledge of the sourceblock size used for each portion of the data. In some embodiments, encoding libraries may be randomly or pseudo-randomly rotated to provide additional security.

    SYSTEM AND METHOD FOR DATA COMPACTION AND SECURITY USING MULTIPLE ENCODING ALGORITHMS

    公开(公告)号:US20210373776A1

    公开(公告)日:2021-12-02

    申请号:US17404699

    申请日:2021-08-17

    Abstract: A system and method for encoding data using a plurality of encoding libraries. Portions of the data are encoded by different encoding libraries, depending on which library provides the greatest compaction for a given portion of the data. This methodology not only provides substantial improvements in data compaction over use of a single data compaction algorithm with the highest average compaction, but provides substantial additional security in that multiple decoding libraries must be used to decode the data. In some embodiments, each portion of data may further be encoded using different sourceblock sizes, providing further security enhancements as decoding requires multiple decoding libraries and knowledge of the sourceblock size used for each portion of the data. In some embodiments, encoding libraries may be randomly or pseudo-randomly rotated to provide additional security.

    System and method for encrypted data compression

    公开(公告)号:US12237848B2

    公开(公告)日:2025-02-25

    申请号:US18503135

    申请日:2023-11-06

    Abstract: A system and method for encrypted data compression, which uses frequency analysis on data blocks within an input data stream to produce a prefix table, representing a first layer of transformation, and which applies a Burrow's-Wheeler transform (BWT) to the data inside the prefix table, representing a second layer of transformation, and which compresses the transformed data. In some implementations, the system and method may further include applying the BWT to a conditioned stream of genomic data, wherein the conditioned stream of data is accompanied by an error stream comprising the differences between the original data and the encrypted data.

    DATA COMPRESSION WITH SIGNATURE-BASED VERIFIABLE INTRUSION DETECTION AND PREDICTION

    公开(公告)号:US20250047298A1

    公开(公告)日:2025-02-06

    申请号:US18919468

    申请日:2024-10-18

    Abstract: A system and method for intrusion detection with prediction and validation subsystems powered by machine learning. The system analyzes real-time codeword streams and historical data to predict potential intrusions before they fully manifest. It employs various machine learning models to extract features, identify patterns, and validate detected anomalies. The system continuously learns from validated events and false positives, improving its accuracy over time. An integrated encryption module secures sensitive data using a dyadic distribution-based algorithm, combining compression and encryption. This approach significantly reduces false positives, enhances threat detection capabilities, and provides robust data protection for cybersecurity applications.

    Data compression with signature-based intrusion detection

    公开(公告)号:US12191889B2

    公开(公告)日:2025-01-07

    申请号:US18436045

    申请日:2024-02-08

    Abstract: A system and method for data compression with intrusion detection, that measures in real-time the probability distribution of an encoded data stream, compares the probability distribution to a reference probability distribution, and uses one or more statistical algorithms to determine the divergence between the two sets of probability distributions to determine if an unusual distribution is the result of a data intrusion. The system further comprises a signature generating component which correlates anomalous event data with known vulnerabilities and exploits to create a signature based on statistical information of the anomalous event. Computed statistics may be compared against a signature database to determine if a data intrusion has occurred.

    EVENT-DRIVEN DATA TRANSMISSION USING CODEBOOKS WITH PROTOCOL PREDICTION AND TRANSLATION

    公开(公告)号:US20240429939A1

    公开(公告)日:2024-12-26

    申请号:US18827741

    申请日:2024-09-07

    Abstract: A system and method for event-driven data communication using codebooks with protocol prediction and translation. This invention presents an advanced adaptive communication system that dynamically optimizes network protocols using machine learning-driven prediction and translation modules. The system analyzes real-time traffic patterns and historical data to anticipate communication needs, proactively switching to optimal protocols when beneficial. A sophisticated translation module, powered by large language models, enables seamless communication between systems using different protocols, including legacy systems. This approach enhances network efficiency, ensures backward compatibility, and future-proofs communication infrastructures, 5 10 making it particularly valuable in complex, heterogeneous network environments.

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