卢倩，女，1992年2月生，山东省日照市人，博士，讲师，硕士研究生导师。在IEEE TIFS, TNSM, IoTJ, ESWA, Computers & Security, Computer Networks, TrustCom, SecureComm, IPCCC, WASA等国际期刊、会议上发表论文20余篇，获授权国家发明专利3项。

• 教育背景：

2010.9 - 2014.6 河南大学，计算机科学与技术，学士学位。

2014.9 – 2016.6 中国海洋大学，保密科学与技术，提前攻博（硕博连读）。

2014.9 - 2020.6 中国海洋大学，智能信息与通信系统，博士学位。

• 研究兴趣包括：AI 安全、物联网安全、加密流量分析、射频指纹识别、渗透测试。

• 主讲课程：信息系统安全（本科生课程）、高级网络安全技术（研究生课程）

• 联系方式：luqian@qdu.edu.cn

• 学术论文：

[1] Tong Sun╘, Qian Lu╘*,  Hanlin Zhang, Fei Chen, Hequn Xian. MsaaDI: A Heterogeneity-Resilient Federated Learning Framework for IoT Device Identification With Multi-Scale Adaptive Aggregation. IEEE Transactions on Information Forensics and Security, 2026.(CCF A 类期刊)

[2] Qian Lu*, Zaiting Xu, Hanlin Zhang, Hequn Xian. SLIoTDI: Scalable and Lightweight IoT Device Identification With Session-Level Grayscale Fingerprinting and Adversarial Training. IEEE Transactions on Network and Service Management,2025.(二区，CCF高水平期刊)

[3] Zaiting Xu, Qian Lu*, Fei Chen, Hequn Xian. LFIoTDI: A lightweight and fine-grained device identification approach for IoT security enhancement. Computer Commnications. Computer Communications, 2025. (二区，CCF推荐高水平期刊)

[4] Qian Lu*，Zaikai Yang, Hanlin Zhang, Fei Chen, Hequn Xian. MRFE: A Deep Learning Based Multidimensional Radio Frequency Fingerprinting Enhancement Approach for IoT Device Identification. IEEE Internet of Things Journal, 2024. (一区Top期刊)

[5] Zaikai Yang, Qian Lu*, Hanlin Zhang, Fei Chen, Hequn Xian. Eliminating Rogue Access Point Attacks in IoT: A Deep Learning Approach with Physical-Layer Feature Purification and Device Identification. IEEE Internet of Things Journal, 2024. (一区Top期刊)

[6] Guangli Wu*, Xingyue Wang, Qian Lu*, Hanlin Zhang. Bot-DM: A dual-modal botnet detection method based on the combination of implicit semantic expression and graphical expression. Expert Systems With Applications, 2024. (一区Top期刊)

[7] Qian Lu*, Shihao Li, Jiahui Zhang, Ruobing Jiang. PEDR: Exploiting phase error drift range to detect full-model rogue access point attacks. Computers & Security, 2022. (CCF推荐高水平期刊)

[8] Qian Lu, Ruobing Jiang, Yuzhan Ouyang, Haipeng Qu, Jiahui Zhang. BiRe: A client-side Bi-directional SYN Reflection mechanism against multi-model evil twin attacks. Computers & Security, 2020. (CCF推荐高水平期刊)

[9] Qian Lu, Haipeng Qu, Yuzhan Ouyang, Jiahui Zhang, SLFAT: Client-Side Evil Twin Detection Approach Based on Arrival Time of Special Length Frames, Security and Communication Networks, 2019. (CCF推荐高水平期刊)

[10] Qian Lu, Haipeng Qu, Yuan Zhuang, Xi-Jun Lin, Yanyong Zhu, Yunzheng Liu, A passive client-based approach to detect evil twin attacks, Proc. IEEE TrustCom, Sydney, Australia, 2017. EI (CCF推荐高水平会议)

[11] Xiaowei Peng, Hequn Xian, Qian Lu, Xiuqing Lu, Semantics aware adversarial malware examples generation for black-box attacks, Applied Software Computing, 2021. (一区期刊)

[12] Yan Wang, Qian Lu, Yiheng Jin, Hao Zhang, Communication Modulation Signal Recognition Based on the Deep Multi-hop Neural Network, Journal of the Franklin Institute, 2021. (二区期刊)

[13] Jiahui Zhang, Qian Lu, Ruobing Jiang, Haipeng Qu, PEDR: A Novel Evil Twin Attack Detection Scheme Based on Phase Error Drift Range, Proc. EAI SecureComm, Washington DC, USA, 2020. (CCF推荐高水平会议)

• 国家发明专利：

[1] 卢倩，张家辉，蒋若冰，曲海鹏，欧阳宇展，基于相位误差漂移范围的全模型伪AP检测，专利号：ZL202010838473.4

[2] 曲海鹏，卢倩，蒋若冰，欧阳宇展，王晓东，基于双向SYN 反射的多模型伪AP 检测方法及检测装置，专利号：ZL201910446169.2

[3] 曲海鹏，卢倩，庄园，林喜军，王涛，一种基于客户端的识别伪 AP 的检测方法及检测装置，专利号：ZL201710457735.0