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Parth Nagar

Parth Nagar

PhD researcher in privacy-preserving ML and cryptography

Puttaparthi, Andhra Pradesh, India
researchgate+1
Joined February 2026
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Summary

Focused researcher in privacy-preserving machine learning and cryptography: Parth's stated research concentrates on privacy-enhancing technologies (PETs) — especially Fully Homomorphic Encryption (FHE), machine learning on encrypted data, and federated learning — applied to secure analytics. researchgate+1
Work and projects centered on privacy-preserving anomaly detection: Parth has contributed to research applying federated learning and homomorphic encryption to anomaly detection in IoT and related distributed/private learning frameworks. researchgate+2
Academic progression at Sri Sathya Sai Institute of Higher Learning: Parth completed BSc (Hons) and MSc at SSSIHL and is affiliated there as a doctoral researcher / research scholar, indicating an academic trajectory within the same institution. researchgate+2
Engaged in the academic and conference circuit: Parth maintains researcher identifiers and profiles (ResearchGate, ORCID, LinkedIn) and has work accepted/published in conferences and compiled venues related to security, privacy, and distributed learning. orcid+2

Work

Education

Projects

Writing

A Quorum-Based Privacy-Preserving Distributed Learning Framework for Anomaly Detection

January 1, 2025

Book chapter / conference paper presenting a quorum-based privacy-preserving distributed learning framework aimed at anomaly detection.

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A Fully Privacy-Preserving Solution for Anomaly Detection in IoT using Federated Learning and Homomorphic Encryption

November 1, 2023

Paper describing a privacy-preserving approach to anomaly detection in IoT environments using federated learning combined with homomorphic encryption techniques.

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Anomaly Detection Through Unsupervised Federated Learning

Work on anomaly detection using unsupervised federated learning methods.

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