Sathish Kumar G.,Premalatha K.,Uma Maheshwari G.,Rajesh Kanna P.,Vijaya G.,Nivaashini M..Differential privacy scheme using Laplace mechanism and statistical method computation in deep neural network for privacy preservation[J].Engineering Applications of Artificial Intelligence,2024.

Niu Dongxiao,Sun Lijie,Yu Min,Wang Keke.Point and interval forecasting of ultra-short-term wind power based on a data-driven method and hybrid deep learning model[J].Energy,2022.

Wang Teng,Hu Zhi.Local differential privacy-based frequent sequence mining[J].Journal of King Saud University - Computer and Information Sciences,2022.

Wang Weikang,Yin He,Chen Chang,Till Abigail,Yao Wenxuan,Deng Xianda,Liu Yilu.Frequency Disturbance Event Detection Based on Synchrophasors and Deep Learning[J].IEEE Transactions on Smart Grid,2020.

Mayo Maldonado J.C.,Valdez Resendiz J.E.,Guillen D.,Bariya M.,Von Meier A.,Salas Esquivel E.A.,Ostfeld A..Data-driven framework to model identification, event detection and topology change location using D-PMUs[J].IEEE Transactions on Instrumentation and Measurement,2020.

Li He,Ota Kaoru,Dong Mianxiong.Learning IoT in Edge: Deep Learning for the Internet of Things with Edge Computing[J].IEEE Network,2018.

Lin Jie,Yu Wei,Zhang Nan,Yang Xinyu,Zhang Hanlin,Zhao Wei.A Survey on Internet of Things: Architecture, Enabling Technologies, Security and Privacy, and Applications[J].IEEE Internet of Things Journal,2017.

Martín Abadi,Andy Chu,Ian J. Goodfellow,H. Brendan McMahan,Ilya Mironov,Kunal Talwar,Li Zhang 0001.Deep Learning with Differential Privacy.[J].CoRR,2016.

刘礼,杨佳轩,强仁,龚钢军,陆俊,武昕.基于DAE和改进RFKM的负荷数据精准特征提取与标签定义[J].电力信息与通信技术,2024(07).

王继东,于俊源,孔祥玉.基于双重分解和双向长短时记忆网络的中长期负荷预测模型[J].电网技术,2024(08).

陆俊,刘博涵,丁慧霞,龚钢军,高凯强,汪莞乔.适应新型电力负荷管理系统的通信安全防护技术架构研究[J].电力信息与通信技术,2024(06).

刘博涵,陆俊,丁慧霞,龚钢军,高凯强,汪莞乔.基于分布式协同免疫的电力负荷管理终端安全防护策略[J].电力信息与通信技术,2024(05).

吴俊仪,李晓会.基于差分隐私的分段裁剪联邦学习算法[J].计算机应用研究,2024(05).

张少波,张激勇,朱更明,龙赛琴,李哲涛.基于Bregman散度和差分隐私的个性化联邦学习方法[J].软件学报,2024(11).

黄建德,何秋,宗悦,王斌,罗远林,吴鹏浩,于尧,郭磊.面向抽水蓄能电站智能巡检系统的联邦学习隐私保护方法[J].重庆邮电大学学报(自然科学版),2023(06).

袁郁,杨超,郑伟铭,林俊鹏,陈新.基于Bi-SRNN的联邦学习区域电力短期负荷预测模型[J].电网与清洁能源,2023(10).

王蓓蓓,朱竞,王嘉乐,马琎劼.电表数据隐私保护下的联邦学习行业电力负荷预测框架[J].电力系统自动化,2023(13).

杨会峰,陈连栋,程凯,王乃玉,李轩,关志涛.支持个性化隐私保护的异步联邦窃电检测方法[J].电力信息与通信技术,2023(06).

李洪裕,董骁翀,王新迎,蒲天骄,孙英云.考虑数据隐私保护的可再生能源场景生成框架[J].电网技术,2023(09).

郭方洪,刘师硕,吴祥,陈博,张文安,葛其运.基于联邦学习的含不平衡样本数据电力变压器故障诊断[J].电力系统自动化,2023(10).

尹春勇,屈锐.基于个性化差分隐私的联邦学习算法[J].计算机应用,2023(04).

王腾,霍峥,黄亚鑫,范艺琳.联邦学习中的隐私保护技术研究综述[J].计算机应用,2023(02).

梁天恺,曾碧,陈光.联邦学习综述：概念、技术、应用与挑战[J].计算机应用,2022(12).