Patents by Inventor Wael Shama

Wael Shama has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Computing trade-offs between privacy and accuracy of data analysis
    Patent number: 11783083
    Abstract: In an approach for computing trade-offs between privacy and accuracy of data analysis on building a learning model, a processor receives a dataset for training a model. The dataset includes one or more pre-identified sensitive data fields. The processor determines a weight of each sensitive data field for the model. The processor evaluates resource cost of applying a privacy preservation technique to the one or more pre-identified sensitive data fields. The processor identifies correlation among the sensitive data fields. The processor presents a comparison of options for training the model, in terms of tradeoffs of accuracy for training the model and the resource cost of the privacy preservation technique.
    Type: Grant
    Filed: March 19, 2021
    Date of Patent: October 10, 2023
    Assignee: International Business Machines Corporation
    Inventors: Wael Shama, Jonathan Bnayahu, Artem Barger, Eliezer Segev Wasserkrug
  • COMPUTING TRADE-OFFS BETWEEN PRIVACY AND ACCURACY OF DATA ANALYSIS
    Publication number: 20220300640
    Abstract: In an approach for computing trade-offs between privacy and accuracy of data analysis on building a learning model, a processor receives a dataset for training a model. The dataset includes one or more pre-identified sensitive data fields. The processor determines a weight of each sensitive data field for the model. The processor evaluates resource cost of applying a privacy preservation technique to the one or more pre-identified sensitive data fields. The processor identifies correlation among the sensitive data fields. The processor presents a comparison of options for training the model, in terms of tradeoffs of accuracy for training the model and the resource cost of the privacy preservation technique.
    Type: Application
    Filed: March 19, 2021
    Publication date: September 22, 2022
    Inventors: Wael Shama, Jonathan Bnayahu, Artem Barger, Eliezer Segev Wasserkrug