{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T21:06:27Z","timestamp":1772658387597,"version":"3.50.1"},"reference-count":33,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T00:00:00Z","timestamp":1762905600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T00:00:00Z","timestamp":1762905600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,11,12]]},"DOI":"10.1109\/tps-isa67132.2025.00014","type":"proceedings-article","created":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T20:50:15Z","timestamp":1772571015000},"page":"32-42","source":"Crossref","is-referenced-by-count":0,"title":["One-Shot Secure Aggregation: A Hybrid Cryptographic Protocol for Private Federated Learning in IoT"],"prefix":"10.1109","author":[{"given":"Imraul","family":"Emmaka","sequence":"first","affiliation":[{"name":"University of Arkansas at Little Rock,Department of Computer Science,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tran Viet Xuan","family":"Phuong","sequence":"additional","affiliation":[{"name":"University of Arkansas at Little Rock,Department of Computer Science,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2025.3530529"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.csi.2025.104017"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2025.3593564"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3133982"},{"key":"ref5","article-title":"Lightsecagg: A lightweight and versatile design for secure aggregation in federated learning","volume":"4","author":"So","year":"2022","journal-title":"Proceedings of Machine Learning and Systems (MLSys)"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/SPW53761.2021.00017"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.56553\/popets-2023-0009"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1002\/int.22818"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/s40747-023-00978-9"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1186\/s42400-024-00232-w"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-70694-8_15"},{"key":"ref12","volume-title":"The elliptic curve diffie-hellman (ecdh)","author":"Haakegaard","year":"2015"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-48910-X_16"},{"key":"ref14","first-page":"14774","article-title":"Deep leakage from gradients","volume":"32","author":"Zhu","year":"2019","journal-title":"Advances in Neural Information Processing Systems (NeurIPS)"},{"key":"ref15","first-page":"16937","article-title":"Inverting gradients: How easy is it to break privacy in federated learning?","volume":"33","author":"Geiping","year":"2020","journal-title":"Advances in Neural Information Processing Systems (NeurIPS)"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.41"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2019.00065"},{"key":"ref18","volume-title":"Fastsecagg: Scalable secure aggregation for privacy-preserving federated learning","author":"Kadhe","year":"2020"},{"key":"ref19","first-page":"1243","article-title":"Sash: Efficient secure aggregation based on shprg for federated learning","volume-title":"Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence (UAI), ser. Proceedings of Machine Learning Research","volume":"180","author":"Liu","year":"2022"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/JSAIT.2021.3054610"},{"issue":"3","key":"ref21","first-page":"246","article-title":"Microsecagg: Streamlined single-server secure aggregation","volume-title":"Proceedings on Privacy Enhancing Technologies","volume":"2024","author":"Guo","year":"2024"},{"key":"ref22","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. 20th Int. Conf. on Artificial Intelligence and Statistics (AISTATS), ser. Proceedings of Machine Learning Research","volume":"54","author":"McMahan","year":"2017"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3319535.3363207"},{"key":"ref24","article-title":"Chacha, a variant of salsa20","volume-title":"SASC 2008: The State of the Art of Stream Ciphers, 2008, workshop Record, ECRYPT","author":"Bernstein"},{"key":"ref25","volume-title":"The openfhe library","year":"2024"},{"key":"ref26","article-title":"Homomorphic encryption standard","author":"Albrecht","year":"2019","journal-title":"Cryptology ePrint Archive, Paper 2019\/939"},{"key":"ref27","volume-title":"Fully homomorphic encryption for privacypreserving machine learning (aaai 2024 tutorial)","year":"2024"},{"key":"ref28","volume-title":"Class Params - openfhe documentation (apis for SetMultiplicativeDepth and SetScalingModSize)","year":"2025"},{"key":"ref29","first-page":"502","article-title":"Towards efficient cloud data processing: A comprehensive guide to ckks parameter selection","volume-title":"Proc. 11th Int. Conf. on Information Systems Security and Privacy (ICISSP 2025)","author":"Gharibyar","year":"2025"},{"key":"ref30","volume-title":"Synthetic data: A privacy-preserving way to accelerate research","year":"2023"},{"key":"ref31","article-title":"Synthetic tabular data: Methods, attacks and defenses","author":"Cormode","year":"2025","journal-title":"arXiv preprint"},{"key":"ref32","first-page":"4697","article-title":"Elasm: Error-latencyaware scale management for fully homomorphic encryption","volume-title":"Proc. 32nd USENIX Security Symposium (USENIX Security \u201923)","author":"Lee","year":"2023"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/359168.359176"}],"event":{"name":"2025 IEEE 7th International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (TPS-ISA)","location":"Pittsburgh, PA, USA","start":{"date-parts":[[2025,11,12]]},"end":{"date-parts":[[2025,11,14]]}},"container-title":["2025 IEEE 7th International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (TPS-ISA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11410113\/11410157\/11410332.pdf?arnumber=11410332","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T20:47:27Z","timestamp":1772657247000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11410332\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,12]]},"references-count":33,"URL":"https:\/\/doi.org\/10.1109\/tps-isa67132.2025.00014","relation":{},"subject":[],"published":{"date-parts":[[2025,11,12]]}}}