Abstract: Systems, methods, and software can be used for securing in-tunnel messages. One example of a method includes obtaining a parsed file that comprises two or more sub-feature trees, and each of the two or more sub-feature trees comprise at least one feature layer that comprises features. The method further includes generating a feature vector that identifies the features in the at least one feature layer for each of the two or more sub-feature trees. The method yet further includes mapping the features in the at least one feature layer for each of the one or more sub-feature trees to a corresponding position in the feature vector. By converting features in the parsed file into a feature vector, the method provides an applicable format of the feature vector in wide applications for the parsed file.

Abstract: Systems and methods are provided herein for redaction of artificial intelligence (AI) training documents. Data comprising an unredacted document is received. The unredacted document comprises a plurality of objects arranged according to a first topology. The unredacted document is parsed to identify objects either directly or relationally containing user sensitive information using a predetermined rule set based on the first topology. The user sensitive information within the unredacted document is substituted with placeholder information to generate a redacted document having a second topology. The second topology is substantially identical to the first topology. In some variations, the redacted document is provided to an AI model for training.

Abstract: A method and computing device for statistical data fingerprinting and tracing data similarity of documents. The method comprises applying a statistical function to a subset of text in a first document thereby generating a first fingerprint; applying the statistical function to a subset of text in a second document thereby generating a second fingerprint; comparing the first fingerprint to the second fingerprint; and determining that the subset of text in the first document matches the subset of text in the second document based on the first fingerprint threshold matching the second fingerprint, wherein the statistical function is a measure of randomness of a count of each character in a subset of text against an expected distribution of said characters.

Abstract: A method and computing device for statistical data fingerprinting and tracing data similarity of documents. The method comprises applying a statistical function to a subset of text in a first document thereby generating a first fingerprint; applying the statistical function to a subset of text in a second document thereby generating a second fingerprint; comparing the first fingerprint to the second fingerprint; and determining that the subset of text in the first document matches the subset of text in the second document based on the first fingerprint threshold matching the second fingerprint, wherein the statistical function is a measure of randomness of a count of each character in a subset of text against an expected distribution of said characters.

Abstract: In accordance with one embodiment of the present disclosure, a method for determining the similarity between a first data set and a second data set is provided. The method includes performing an entropy analysis on the first and second data sets to produce a first entropy result, wherein the first data set comprises data representative of a first one or more computer files of known content and the second data set comprises data representative of a one or more computer files of unknown content; analyzing the first entropy result; and if the first entropy result is within a predetermined threshold, identifying the second data set as substantially related to the first data set.

Abstract: In accordance with one embodiment of the present disclosure, a method for determining the similarity between a first data set and a second data set is provided. The method includes performing an entropy analysis on the first and second data sets to produce a first entropy result, wherein the first data set comprises data representative of a first one or more computer files of known content and the second data set comprises data representative of a one or more computer files of unknown content; analyzing the first entropy result; and if the first entropy result is within a predetermined threshold, identifying the second data set as substantially related to the first data set.

Abstract: In accordance with one embodiment of the present disclosure, a method for determining the similarity between a first data set and a second data set is provided. The method includes performing an entropy analysis on the first and second data sets to produce a first entropy result, wherein the first data set comprises data representative of a first one or more computer files of known content and the second data set comprises data representative of a one or more computer files of unknown content; analyzing the first entropy result; and if the first entropy result is within a predetermined threshold, identifying the second data set as substantially related to the first data set.

Abstract: Systems and methods are provided herein for redaction of artificial intelligence (AI) training documents. Data comprising an unredacted document is received. The unredacted document comprises a plurality of objects arranged according to a first topology. The unredacted document is parsed to identify objects either directly or relationally containing user sensitive information using a predetermined rule set based on the first topology. The user sensitive information within the unredacted document is substituted with placeholder information to generate a redacted document having a second topology. The second topology is substantially identical to the first topology. In some variations, the redacted document is provided to an AI model for training.

Abstract: In accordance with one embodiment of the present disclosure, a method for determining the similarity between a first data set and a second data set is provided. The method includes performing an entropy analysis on the first and second data sets to produce a first entropy result, wherein the first data set comprises data representative of a first one or more computer files of known content and the second data set comprises data representative of a one or more computer files of unknown content; analyzing the first entropy result; and if the first entropy result is within a predetermined threshold, identifying the second data set as substantially related to the first data set.

Abstract: In accordance with one embodiment of the present disclosure, a method for determining the similarity between a first data set and a second data set is provided. The method includes performing an entropy analysis on the first and second data sets to produce a first entropy result, wherein the first data set comprises data representative of a first one or more computer files of known content and the second data set comprises data representative of a one or more computer files of unknown content; analyzing the first entropy result; and if the first entropy result is within a predetermined threshold, identifying the second data set as substantially related to the first data set.

Abstract: A system, method, and computer program product are provided for applying a regular expression to content based on required strings of the regular expression. In use, all required strings included in a regular expression are identified, the required strings including strings required by the regular expression. Additionally, it is determined whether the required strings match content. Furthermore, the regular expression is applied to the content, based on the determination.

Abstract: In accordance with one embodiment of the present disclosure, a method for determining the similarity between a first data set and a second data set is provided. The method includes performing an entropy analysis on the first and second data sets to produce a first entropy result, wherein the first data set comprises data representative of a first one or more computer files of known content and the second data set comprises data representative of a one or more computer files of unknown content; analyzing the first entropy result; and if the first entropy result is within a predetermined threshold, identifying the second data set as substantially related to the first data set.

Abstract: A system, method, and computer program product are provided for applying a regular expression to content based on required strings of the regular expression. In use, all required strings included in a regular expression are identified, the required strings including strings required by the regular expression. Additionally, it is determined whether the required strings match content. Furthermore, the regular expression is applied to the content, based on the determination.