@inproceedings{9c25a172784d49919549d4497fb2e15c,
title = "High-Secure Data Collection in IoT Sensor Networks using Homomorphic Encryption",
abstract = "In wireless sensor networks, sensor nodes are deployed in open environments to gather and send collected data to a remote server. During the data transmission process, the collected data is vulnerable to security risks, making it crucial to encrypt the data to prevent it from falling into the wrong hands. This paper proposes a new approach that integrates homomorphic encryption (HE) algorithms into the sensor devices, allowing the data collected by the sensors to be encrypted before transmission. By utilizing HE in the sensor networks, the server can execute calculations on the encrypted data without requiring decryption. To implement the HE function, we use the Simple Encrypted Arithmetic Library (SEAL), which the Microsoft Cryptography Research Group developed. We evaluated the HE-based data collection scheme in IoT sensor networks with various network topologies to assess network lifetime, communication distance, and data collection latency.",
keywords = "Cloud service, data collection, encrypted data, homomorphic encryption, sensor networks",
author = "Nguyen, {Tuy Tan} and Phan, {Quoc Bao} and Bui, {Ngoc Thang} and Carlo daCunha",
note = "Publisher Copyright: {\textcopyright} 2023 SPIE.; Sensors and Systems for Space Applications XVI 2023 ; Conference date: 30-04-2023 Through 05-05-2023",
year = "2023",
doi = "10.1117/12.2663875",
language = "English (US)",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Genshe Chen and Pham, {Khanh D.}",
booktitle = "Sensors and Systems for Space Applications XVI",
}