Abstract: A system and method for encoding data utilizing mismatch probability estimates. A training data set can be statistically analyzed to calculate a mismatch probability estimate which is the estimated frequency at which a data packet received during system runtime is not part of (i.e., a mismatch) the training data set. A plurality of tokens may be created, based on the mismatch probability estimate, to represent potential mismatched data that may be encountered during runtime, and an entropy encoder may generate codewords for the tokens using the mismatch probability estimate. An opcode, indicating a mismatch, may be generated and appended to the generated codewords to form a mismatch codeword. During runtime when a mismatch occurs, the system can retrieve a mismatch codeword and assign it to the mismatched data, making the encoder system robust against previously unencountered data.

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.

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.

Abstract: A system and method for file type identification involving extraction of a file-print of a file, the file-print being a unique or practically-unique representation of statistical characteristics associated with the distribution of bits in the binary contents of the file, similar to a fingerprint. The file-print is then passed to a machine learning algorithm that has been trained to recognize file types from their file-prints. The machine learning algorithm returns a predicted file type and, in some cases, a probability of correctness of the prediction. The file may then be encoded using an encoding algorithm chosen based on the predicted file type.

Abstract: A system and method for data storage, transfer, synchronization, and security using automated system efficacy monitoring and model training, wherein statistical analyses of test datasets are used to determine if the probability distribution of two datasets are within a pre-determined range, and responsive to that determination new encoding and decoding algorithms may be retrained in order to produce new data chunklets. The new data chunklets may then be processed and assigned new codewords which are compiled into an updated codebook which may be distributed back to encoding and decoding systems and devices.

Abstract: A system and method for highly efficient encoding of data that includes extended functionality for asymmetric encoding/decoding and network policy enforcement. In the case of asymmetric encoding/decoding the original data is encoded by an encoder according to a codebook and sent to a decoder, but the output of the decoder depends on data manipulation rules applied at the decoding stage to transform the decoded data, into a different data set from the original data. In the case of network pokey enforcement, a behavior appendix into the codebook, such that the encoder and/or decoder at each node of the network comply with network behavioral rules, limits, and policies during encoding and decoding.

Abstract: A system and method for file type identification involving extraction of a file-print of a file, the file-print being a unique or practically-unique representation of statistical characteristics associated with the distribution of bits in the binary contents of the file, similar to a fingerprint. The file-print is then passed to a machine learning algorithm that has been trained to recognize file types from their file-prints. The machine learning algorithm returns a predicted file type and, in some cases, a probability of correctness of the prediction. The file may then be encoded using an encoding algorithm chosen based on the predicted file type.

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.

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.

Abstract: A system and methods for secure storage for data deduplication comprising a data deconstruction engine, a data reconstruction engine, a library manager, a reference codebook, and a codeword storage which performs simultaneous compaction and deduplication of data sets. A data set may be comprised of one or more sourcepackets which may be optimally deconstructed into a plurality of sourceblocks and wherein each sourceblock may be compared against a reference codebook that contains key-value pairs of a sourceblock and its associated reference code in order to determine if a received sourceblock is a duplicate of data already stored within the reference codebook. Non-duplicate sourceblocks can have a reference code algorithmically created and stored in the reference codebook, thereby ensuring that when a duplicate sourceblock is received, it will not be stored as duplicated data.

Abstract: A system and methods for bandwidth-efficient encoding of genome and bioinformatic sequence datasets comprising a sequence analyzer configured to: analyze a received sequence dataset to determine a sequence dataset file type, scan the sequence dataset to maintain a count of unique characters contained therein, identify positions where the unique character count increases by a power of two, deconstruct the sequence dataset into a plurality of sourceblocks at the identified positions, and encode the plurality of sourceblocks using a data deconstruction engine and library management module to assign each sourceblock a reference code.

Abstract: A system and methods for bandwidth-efficient cryptographic data transfer, utilizing an encoding endpoint device, a decoding endpoint device, a reference codebook, and a plurality of data to encode and decode, which may use specific algorithms on top of block cipher encryption to achieve higher data security and ease the burden on users with regards to computational power, complexity, and bandwidth for communication.

Abstract: A system and method for highly efficient encoding of data that includes extended functionality for asymmetric encoding/decoding and network policy enforcement. In the case of asymmetric encoding/decoding the original data is encoded by an encoder according to a codebook and sent to a decoder, but the output of the decoder depends on data manipulation rules applied at the decoding stage to transform the decoded data, into a different data set from the original data. In the case of network pokey enforcement, a behavior appendix into the codebook, such that the encoder and/or decoder at each node of the network comply with network behavioral rules, limits, and policies during encoding and decoding.

Abstract: A system and method for file type identification involving extraction of a file-print of a file, the file-print being a unique or practically-unique representation of statistical characteristics associated with the distribution of bits in the binary contents of the file, similar to a fingerprint. The file-print is then passed to a machine learning algorithm that has been trained to recognize file types from their file-prints. The machine learning algorithm returns a predicted file type and, in some cases, a probability of correctness of the prediction. The file may then be encoded using an encoding algorithm chosen based on the predicted file type.

Abstract: A system and methods for bandwidth-efficient cryptographic data transfer, utilizing an encoding endpoint device, a decoding endpoint device, a reference codebook, and a plurality of data to encode and decode, which may use specific algorithms on top of block cipher encryption to achieve higher data security and ease the burden on users with regards to computational power, complexity, and bandwidth for communication.

Abstract: A system and method for data storage, transfer, synchronization, and security using automated system efficacy monitoring and model training, wherein statistical analyses of test datasets are used to determine if the probability distribution of two datasets are within a pre-determined range, and responsive to that determination new encoding and decoding algorithms may be retrained in order to produce new data chunklets. The new data chunklets may then be processed and assigned new codewords which are compiled into an updated codebook which may be distributed back to encoding and decoding systems and devices.

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.

Abstract: A system and method for error-resilient data reduction, utilizing a phase detector, a data requestor, a multi-phase trainer, a reconstruction engine, a deconstruction engine, and one or more reference codebooks. A multi-phase trainer may be used to train the reconstruction and deconstruction engines on various phase sourceblocks in order recover quickly from corrupted data files that cause the phase alignment of the sourceblocks to become out of phase. A phase detector may determine when the sourceblocks get out of phase and when the return to in-phase by checking if a predetermined threshold probability of correct encoding is met. Data requestor may request for retransmission only the data that was received out of phase.

Abstract: A system and method for fast communication between processors on complex chips using encoding, wherein a training data set is used to find patterns and associated smaller indices, or codewords, which are stored in a reference codebook library, and where reconstruction and deconstruction algorithms are used to encode and decode data as it is received. The codebook and algorithms may be stored in the firmware of a semiconductor which enable reduced resources and cost when transmitting data between or among devices that utilize such semiconductors.

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.