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Multi-Party Computation in IoT for Privacy-Preservation

Himanshu Rai Goyal, Sudipta Saha

20222022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS)22 citationsDOI

Abstract

Preservation of privacy has been a serious concern with the increasing use of IoT-assisted smart systems and their ubiquitous smart sensors. To solve the issue, the smart systems are being trained to depend more on aggregated data instead of directly using raw data. However, most of the existing strategies for privacy-preserving data aggregation, either depend on computation-intensive Homomorphic Encryption based operations or communication-intensive collaborative mechanisms. Unfortunately, none of the approaches are directly suitable for a resource-constrained IoT system. In this work, we leverage the concurrent-transmission-based communication technology to efficiently realize a Multi-Party Computation (MPC) based strategy, the well-known Shamir’s Secret Sharing (SSS), and optimize the same to make it suitable for real-world IoT systems.

Topics & Concepts

Computer scienceHomomorphic encryptionEncryptionComputer securitySecure multi-party computationInternet of ThingsLeverage (statistics)ComputationData sharingSecret sharingInformation privacyDistributed computingCryptographyAlgorithmMachine learningAlternative medicineMedicinePathologyCryptography and Data SecurityPrivacy-Preserving Technologies in DataStochastic Gradient Optimization Techniques
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