Truata Limited

Other

Heystaks Technology Limited

Maurice Coyle

Michael Fenton

Imran Khan

Barry Joseph Smyth

Peter Briggs

Barry Smyth

Dave Fagan

Noel Rogers

Aydin Ulas

A system and method for guiding privacy-enhancing transformations are described. The system and method include a recommendation engine configured to identify sets of transformations to mitigate a privacy risk below a user specified threshold specified in-terms of privacy-risk score for a given input dataset while keeping the utility of the dataset above the user-specified utility threshold specified in-terms of utility score. A simulation engine configured to simulate the identified set of transformations from the recommendation engine on the dataset to determine the optimal application of the plurality of transformations for maximizing the utility of the dataset, and output device to provide the optimized dataset with the privacy risk score and utility score.

System and method for guiding privacy-enhancing transformations

A system and method for objective quantification and mitigation of privacy-risk of a dataset is disclosed. The system and method include an input-output (IO) interface for receiving at least one input dataset, on at least one of which a measurement of the risk is to be performed, and a configuration file governing the anonymization; a scoring engine including: a uniqueness sub-engine for determining uniqueness scores at data and data-subject level across both individual columns and combinations of columns; a similarity sub-engine that calculates the overlap, reproducibility and similarity by comparing all columns and subsets of columns between at least two datasets, where one dataset is the original version and the other one is transformed, modified, anonymized or synthetic version of original dataset; a statistical sub-engine that calculates statistics that are an indication of privacy-risks and re-identification risks; a contextual sub-engine for quantifying contextual factors by considering weighted approaches and producing a single context-centric score; and a recommendation engine identifying mitigating measures to reduce the privacy-risks by taking in to account the factors that are contributing to higher risk.

System and method for objective quantification and mitigation of privacy risk

A system and method for objective quantification and mitigation of privacy-risk of a dataset is disclosed. These include an input-output (IO) interface for receiving at least one input dataset, and a configuration file governing the anonymization; a scoring engine including: a uniqueness sub-engine for determining uniqueness scores at data and data-subject level across both individual columns and combinations of columns; a similarity sub-engine that calculates the overlap, reproducibility and similarity by comparing all columns and subsets of columns between at least two datasets, modified, anonymized or synthetic version of original dataset; a statistical sub-engine that calculates statistics that are an indication of privacy-risks and re-identification risks; a contextual sub-engine for quantifying contextual factors by considering weighted approaches and producing a single context-centric score; and a recommendation engine identifying mitigating measures to reduce the privacy-risks by taking in to account the factors that are contributing to higher risk.

A system has a primary server storing search data sets ('staks') and a linked social network server.

Searching system having a server which automatically generates search data sets for shared searching

A searching system may include a primary server with interfaces for communication with databases or with underlying search engines. The primary server may be adapted to receive a search query from a client under instructions from a user; and retrieve search results and transmit the results as a response to the client. The primary server may be adapted to store search data sets of relevant results for queries by users who are member of the set. The primary server may be adapted to select a search data set of which the user for the query is a member, and to use said search data set in providing the response to the query. The primary server may be adapted to download data concerning the selected search data set to the user. The primary server may be adapted to automatically update the search data set according to the results selected by the user.

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Dublin, Ireland

Maurice Coyle