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Function Computation under Privacy, Secrecy, Distortion, and Communication Constraints.

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  • 1Chair of Communications Engineering and Security, University of Siegen, 57076 Siegen, Germany.

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|January 21, 2022
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Summary

This study introduces new privacy, secrecy, and storage constraints for remote function computation. It develops new methods for secure information processing with noisy data from multiple sources.

Keywords:
distributed computationinformation theoretic privacyremote sourcesecure function computation

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Area of Science:

  • Information Theory
  • Distributed Computing
  • Cybersecurity

Background:

  • Classic function computation problems lack privacy and secrecy considerations.
  • Existing models do not account for constraints on remote sources with noisy measurements.
  • Multiple parties observing data introduce complexities in secure computation.

Purpose of the Study:

  • To extend reliable function computation by incorporating privacy, secrecy, and storage constraints.
  • To introduce novel metrics for measuring information leakage to eavesdroppers and fusion centers.
  • To explore the trade-offs between function distortion, storage rate, and security leakages.

Main Methods:

  • Developing new privacy leakage metrics relative to the remote source.
  • Allowing for distorted function computation to optimize storage and security.
  • Deriving inner and outer bounds for rate regions in lossless and lossy computation.
  • Analyzing special cases like invertible functions and degraded channels.

Main Results:

  • Established rate regions for lossless and lossy single-function computation with two transmitting nodes.
  • Recovered and extended previous results in the literature.
  • Characterized simplified rate regions for special cases, demonstrating achievable regions.

Conclusions:

  • The study provides a theoretical framework for secure and private function computation under various constraints.
  • New insights into the trade-offs between computation reliability, storage, and information security are presented.
  • The derived bounds and characterized regions advance the understanding of distributed information processing with security guarantees.