A Privacy Preserving Anomaly Detection Framework for Cooperative Smart Farming Ecosystem

Author:

Chukkapalli Sai Sree Laya1,Ranade Priyanka1,Mittal Sudip2,Joshi Anupam1

Affiliation:

1. University of Maryland Baltimore County,Dept. of Computer Science & Electrical Engineering

2. Mississippi State University,Department of Computer Science & Engineering

Publisher

IEEE

Reference42 articles.

1. On fully homomorphic encryption for privacy-preserving deep learning;marcano;2019 IEEE Globecom Workshops (GC Wkshps),0

2. Privacy-Preserving Decentralized Key-Policy Attribute-Based Encryption

3. Ontology driven AI and Access Control Systems for Smart Fisheries

4. Privacy-preserving anonymization of set-valued data

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Synthetic Data for Privacy Preservation in Distributed Data Analysis Systems;Springer Optimization and Its Applications;2024-05-10

2. Differential Privacy for Anomaly Detection: Analyzing the Trade-Off Between Privacy and Explainability;Communications in Computer and Information Science;2024

3. Hierarchical Federated Transfer learning and Digital Twin Enhanced Secure Cooperative Smart Farming;2023 IEEE International Conference on Big Data (BigData);2023-12-15

4. Anomaly Detection for Electric Energy Consumption in Smart Farms;IEEE Transactions on AgriFood Electronics;2023-06

5. IoT-Enabled Smart Agriculture: Security Issues and Applications;Artificial Intelligence and Smart Environment;2023

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