Company Filing History:
Years Active: 2019-2022
Title: Rakhi S Arora: Innovator in Secure Multi-Party Computing
Introduction
Rakhi S Arora is a prominent inventor based in Bengaluru, India. She has made significant contributions to the field of secure multi-party computing, particularly in the area of machine learning and data security. With a total of 4 patents to her name, her work is paving the way for advancements in data privacy and computational security.
Latest Patents
Rakhi's latest patents include innovative methods for machine learning with differently masked data in secure multi-party computing. In this patent, a super mask is constructed using a set of masks corresponding to various data contributors. Each contributor uses a unique mask to obfuscate their data, allowing for the formation of a first scaled masked data. This data is then used to train a machine learning model while maintaining the obfuscation of the contributors' data.
Another notable patent focuses on masking text data for secure multiparty computation. This method involves receiving masked input data from multiple contributors, each with a unique contributor mask value. The process includes aggregating the input data and publishing computational results while ensuring that the results remain masked according to the respective contributor's mask value.
Career Highlights
Rakhi S Arora is currently employed at International Business Machines Corporation (IBM), where she continues to innovate in the field of secure computing. Her work is instrumental in developing technologies that enhance data security and privacy in collaborative environments.
Collaborations
Rakhi has collaborated with notable colleagues such as Vaibhav Murlidhar Kulkarni and Padmanabhan Krishnan. These collaborations have further enriched her research and development efforts in the field.
Conclusion
Rakhi S Arora is a trailblazer in the realm of secure multi-party computing, with her patents reflecting her commitment to advancing data security. Her contributions are vital in shaping the future of machine learning and data privacy.