Table of Links

Abstract and Introduction

Problem Formulation

Affine Solution to Problem 1

Privacy Guarantee

General Guidelines for Implementation

Case Studies

Conclusion and References

VII. CONCLUSION

In this paper, we have developed a privacy-preserving framework for the implementation of remote dynamical algorithms in the cloud. It is built on the synergy of random coding and system immersion tools from control theory to protect private information. We have devised a synthesis procedure to design the dynamics of a coding scheme for privacy and a higher-dimensional system called target algorithm such that trajectories of the standard dynamical algorithm are immersed/embedded in its trajectories, and it operates on randomly encoded higher-dimensional data. Random coding was formulated at the user side as a random change of coordinates that maps original private data to a higher-dimensional space. Such coding enforces that the target algorithm produces an encoded higher-dimensional version of the utility of the original algorithm that can be decoded on the user side.

The proposed immersion-based coding scheme provides the same utility as the original algorithm (i.e., when no coding is employed to protect against data inference), (practically) reveals no information about private data, can be applied to large-scale algorithms, is computationally efficient, and offers any desired level of differential privacy without degrading the algorithm utility.

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