Abstract: A method for adaptive data masking of a database is provided. The method comprises extracting data from a first database and providing one or more predefined rules for masking the extracted data. The method further comprises masking a first portion of extracted data using a trained Artificial Neural Network (ANN), where the ANN is trained for masking at least one database having properties similar to the first database. The masked and unmasked data is aggregated to arrive at an output structurally similar to the extracted data. The method furthermore comprises determining a deviation value between the arrived output and expected output of the extracted data, and adapting the trained ANN automatically according to data masking requirements of the first database, if the deviation value is more than a predefined value.

Abstract: A method for adaptive data masking of a database is provided. The method comprises extracting data from a first database and providing one or more predefined rules for masking the extracted data. The method further comprises masking a first portion of extracted data using a trained Artificial Neural Network (ANN), where the ANN is trained for masking at least one database having properties similar to the first database. The masked and unmasked data is aggregated to arrive at an output structurally similar to the extracted data. The method furthermore comprises determining a deviation value between the arrived output and expected output of the extracted data, and adapting the trained ANN automatically according to data masking requirements of the first database, if the deviation value is more than a predefined value.

Abstract: A method and system to authenticate human interactive proof (HIP) are described here. In response to a request from a web server, a motion random HIP in the form of motion-captcha is generated. The web server can then display the generated the motion random HIP in a requested web page. The web page is accompanied with a request from the user to provide the response for the generated motion captcha. After evaluation and verification of response received from the particular user, the authentication system determine whether the response to the HIP challenge is from human or from other source like computer software scripted agent.