Honda Research Institute (HRI), a Honda R&D subsidiary, and Boston University have agreed to begin joint research in the area of data security and privacy for artificial intelligence (AI) research.
Honda intends to develop Cooperative Intelligence: AI that cooperates with people which will 1) empower: expanding the potential of people; 2) share experience: accommodating and growing together with people; and 3) empathize: be capable of understanding and relating to the emotions of people.
In order to enable AI to cooperate with people, personal information about the users must be collected and analyzed. This information must be protected. Honda noted. To accelerate its research in the area of information security, Honda has chosen the Rafik B. Hariri Institute for Computing and Computational Science & Engineering of Boston University as one strategic partner for joint research collaboration.
To coordinate and structure the collaboration, an oversight committee has been established, consisting of the members of Boston University and Honda, including Dr. Azer Bestavros, Distinguished Professor of Computer Science Department at Boston University and Founding Director of Boston University Hariri Institute for Computing, and Dr. Bernhard Sendhoff, Head of Global Operations of HRI and President of HRI Europe.
A first research project will investigate data privacy control using a technology called secure multi-party computation (MPC).
In a paper presented at the 2017 Theory and Practice of Multi-Party Computation Workshop (TPMPC’17) this past April, Dr. Bestavros and his colleagues wrote that:
Secure multi-party computation (MPC) can possess substantial social value: it enables companies, government agencies, and other organizations to benefit from collective data aggregation and analysis in contexts where the raw data are encumbered by legal and corporate policy restrictions on data sharing. Theoretical constructs for MPC have been known for decades, and the past few years have seen several successful deployments of MPC along with the development of a number of software framework that aim to deliver MPC’s benefits to end-users.
However, MPC’s social benefits cannot be realized unless we design MPC systems whose security and functionality can be comprehended by the executives, directors, and legal advisors of participating organizations, and we automate the secure compilation of legacy applications that were developed in well-known programming paradigms.
Currently, personalized services have become common in our daily lives. These systems typically share personal data of users, often without their knowledge and control. Honda’s goal is to create data security technologies that enable users to control which data can be shared with systems and which cannot. This project officially started on 1 May 2017.
Ueli Maurer (2006) “Secure multi-party computation made simple,” Discrete Applied Mathematics, Volume 154, Issue 2, Pages 370-381 doi: 10.1016/j.dam.2005.03.020 (Open access)
Azer Bestavros, Frederick Jansen, Andrei Lapets, Malte Schwarzkopf, Mayank Varia, and Nikolaj Volgushev (2017) “Design and Deployment of Usable, Scalable MPC,” Presented at the 2017 Theory and Practice of Multi-Party Computation Workshop (TPMPC’17), April 2017