Abstract: A method of automatically manipulating a lifecycle of a honeyfile on a file system, includes: implementing a learning algorithm on a file system; identifying a real file; training the learning algorithm by observing temporal events involving the real file; training a model with the learning algorithm; implementing a user agent on the file system; creating a honeyfile on the file system; deploying the honeyfile on the file system; using the trained model to generate user agent actions; evaluating the honeyfile; and either: deleting the honeyfile; or re-using the trained model to generate user agent actions to automatically modify the honeyfile.

Abstract: The present disclosure is directed to systems and methods for creating, managing, and storing synthetic data that is designed to be placed within databases having real data to deceive, attract, detect and/or track unauthorized access thereof. The synthetic data can be stored as a honeyrecord in a database table that is interspersed with real data such that the honeyrecord is indistinguishable from real data or combined to form a honeytable having multiple honeyrecords therein. In some embodiments, the synthetic data can be used to create a user persona having one or more parameters to construct a profile or an identity honeyrecord of an individual. The parameters can include private information such as name, sex, passport number, social security number, bank account or credit card details, biometric details, passwords, and other information that is attractive to hackers and other data thieves.

Abstract: A method for automatically creating a honeyfile for a file system, includes the steps of: surveying a file set of the file system to identify tokenisable data in the file set, tokenising the identified tokenisable data to form a plurality of token sequences, and either selecting one of the plurality of token sequences or generating a token sequence to operate as an exemplar token sequence; applying a substitution method to substitute the tokens of the exemplar token sequence with replacement tokenisable data; and packaging the replacement tokenisable data into a honeyfile.

Abstract: A method for automatically creating a honeyfile for a file system, includes the steps of: surveying a file set of the file system to identify tokenisable data in the file set, tokenising the identified tokenisable data to form a plurality of token sequences, and either selecting one of the plurality of token sequences or generating a token sequence to operate as an exemplar token sequence; applying a substitution method to substitute the tokens of the exemplar token sequence with replacement tokenisable data; and packaging the replacement tokenisable data into a honeyfile.

Abstract: A method of automatically manipulating a lifecycle of a honeyfile on a file system, includes: implementing a learning algorithm on a file system; identifying a real file; training the learning algorithm by observing temporal events involving the real file; training a model with the learning algorithm; implementing a user agent on the file system; creating a honeyfile on the file system; deploying the honeyfile on the file system; using the trained model to generate user agent actions; evaluating the honeyfile; and either: deleting the honeyfile; or re-using the trained model to generate user agent actions to automatically modify the honeyfile.

Abstract: The present disclosure is directed to systems and methods for creating, managing, and storing synthetic data that is designed to be placed within databases having real data to deceive, attract, detect and/or track unauthorized access thereof. The synthetic data can be stored as a honeyrecord in a database table that is interspersed with real data such that the honeyrecord is indistinguishable from real data or combined to form a honeytable having multiple honeyrecords therein. In some embodiments, the synthetic data can be used to create a user persona having one or more parameters to construct a profile or an identity honeyrecord of an individual. The parameters can include private information such as name, sex, passport number, social security number, bank account or credit card details, biometric details, passwords, and other information that is attractive to hackers and other data thieves.

Abstract: A method for automatically creating a honeyfile for a file system, includes the steps of: surveying a file set of the file system to identify tokenisable data in the file set, tokenising the identified tokenisable data to form a plurality of token sequences, and either selecting one of the plurality of token sequences or generating a token sequence to operate as an exemplar token sequence; applying a substitution method to substitute the tokens of the exemplar token sequence with replacement tokenisable data; and packaging the replacement tokenisable data into a honeyfile.

Abstract: A method for automatically creating a honeyfile for a file system, includes the steps of: surveying a file set of the file system to identify tokenisable data in the file set, tokenising the identified tokenisable data to form a plurality of token sequences, and either selecting one of the plurality of token sequences or generating a token sequence to operate as an exemplar token sequence; applying a substitution method to substitute the tokens of the exemplar token sequence with replacement tokenisable data; and packaging the replacement tokenisable data into a honeyfile.

Abstract: A method for automatically creating a honeyfile for a file system, includes the steps of: surveying a file set of the file system to identify tokenisable data in the file set, tokenising the identified tokenisable data to form a plurality of token sequences, and either selecting one of the plurality of token sequences or generating a token sequence to operate as an exemplar token sequence; applying a substitution method to substitute the tokens of the exemplar token sequence with replacement tokenisable data; and packaging the replacement tokenisable data into a honeyfile.