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  1. [TIFS’24] Unstoppable Attack: Label-Only Model Inversion via Conditional Diffusion Model
    Rongke Liu, Dong Wang, Yizhi Ren, Kaitian Guo, Qianqian Qin, and Xiaolei Liu
    IEEE Transactions on Information Forensics and Security, 19 :3958–3973, 2024.
  2. [IEEE Network’24] An Adversarial Example Defense Algorithm for Intelligent Driving
    Jiazhong Lu, Chenli Wang, Yuanyuan Huang, Kangyi Ding, and Xiaolei Liu
    IEEE Network, 2024.


  1. [Appl.Sci.’23] A Robust Adversarial Example Attack Based on Video Augmentation
    Mingyong Yin, Yixiao Xu, Teng Hu, and Xiaolei Liu
    Applied Sciences, 13(3) :1914, 2023.
  2. [ICASSP’23] Sparse Black-Box Inversion Attack with Limited Information
    Yixiao Xu, Xiaolei Liu, Teng Hu, Bangzhou Xin, and Run Yang
    ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1–5, IEEE, 2023.
  3. [J.Grid Comput.’23] Anti-attack Intrusion Detection Model based on MPNN and Traffic Spatiotemporal Characteristics
    Jiazhong Lu, Jin Lan, Yuanyuan Huang, Maojia Song, and Xiaolei Liu
    Journal of Grid Computing, 21(60) 2023.


  1. [ICASSP’22] Sparse Adversarial Attack For Video Via Gradient-Based Keyframe Selection
    Yixiao Xu, Xiaolei Liu, Mingyong Yin, Teng Hu, and Kangyi Ding
    ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2874–2878, IEEE, 2022.
  2. [ICME’22] Targeted Anonymization: A Face Image Anonymization Method for Unauthorized Models
    Kangyi Ding, Teng Hu, Xiaolei Liu, Weina Niu, Yanping Wang, and Xiaosong Zhang
    2022 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6, IEEE, 2022.
  3. [Sensors’22] IBD: An Interpretable Backdoor-Detection Method via Multivariate Interactions
    Yixiao Xu, Xiaolei Liu, Kangyi Ding, and Bangzhou Xin
    Sensors, 22(22) :8697, 2022.
  4. [Sensors’22] A Novel Steganography Method for Character-Level Text Image Based on Adversarial Attacks
    Kangyi Ding, Teng Hu, Weina Niu, Xiaolei Liu, Junpeng He, Mingyong Yin, and Xiaosong Zhang
    Sensors, 22(17) :6497, 2022.


  1. [NCA’21] Research on information steganography based on network data stream
    Jiazhong Lu, Weisha Zhang, Ziye Deng, Shibin Zhang, Yan Chang, and Xiaolei Liu
    Neural Computing and Applications, 33 :851–866, 2021.
  2. [IPM’21] Transaction-based classification and detection approach for Ethereum smart contract
    Teng Hu, Xiaolei Liu, Ting Chen, Xiaosong Zhang, Xiaoming Huang, Weina Niu, Jiazhong Lu, Kun Zhou, and Yuan Liu
    Information Processing & Management, 58(2) :102462, 2021.
  3. [ITS’21] Compiler-Based Efficient CNN Model Construction for 5G Edge Devices
    Kun Wan, Xiaolei Liu, Jianyu Yu, Xiaosong Zhang, Xiaojiang Du, and Nadra Guizani
    IEEE Transactions on Intelligent Transportation Systems, 2021.
  4. [SCN’21] HTTP-based APT malware infection detection using URL correlation analysis
    Weina Niu, Jiao Xie, Xiaosong Zhang, Chong Wang, Xinqiang Li, Ruidong Chen, and Xiaolei Liu
    Security and Communication Networks, 2021 :1–12, 2021.
  5. [KBS’21] A low-query black-box adversarial attack based on transferability
    Kangyi Ding, Xiaolei Liu, Weina Niu, Teng Hu, Yanping Wang, and Xiaosong Zhang
    Knowledge-Based Systems, 226 :107102, 2021.
  6. [ICMLWS’21] Audio injection adversarial example attack
    Xiaolei Liu, Xingshu Chen, Mingyong Yin, Yulong Wang, Teng Hu, and Kangyi Ding
    ICML 2021 Workshop on Adversarial Machine Learning 2021.
  7. [SCN’21] A Hybrid Association Rule-Based Method to Detect and Classify Botnets
    Yuanyuan Huang, Lu Jiazhong, Haozhe Tang, and Xiaolei Liu
    Security and Communication Networks, 2021 :1–9, 2021.


  1. [ACISP’20] A black-box attack on neural networks based on swarm evolutionary algorithm
    Xiaolei Liu, Teng Hu, Kangyi Ding, Yang Bai, Weina Niu, and Jiazhong Lu
    Information Security and Privacy: 25th Australasian Conference, ACISP 2020, Perth, WA, Australia, November 30–December 2, 2020, Proceedings 25, pp. 268–284, Springer International Publishing, 2020.
  2. [Sensors’20] Tracking the insider attacker: A blockchain traceability system for insider threats
    Teng Hu, Bangzhou Xin, Xiaolei Liu, Ting Chen, Kangyi Ding, and Xiaosong Zhang
    Sensors, 20(18) :5297, 2020.
  3. [SCN’20] Research and analysis of electromagnetic Trojan detection based on deep learning
    Jiazhong Lu, Xiaolei Liu, Shibin Zhang, and Yan Chang
    Security and Communication Networks, 2020 :1–13, 2020.
  4. [AAAI’20] Weighted-sampling audio adversarial example attack
    Xiaolei Liu, Kun Wan, Yufei Ding, Xiaosong Zhang, and Qingxin Zhu
    Proceedings of the AAAI Conference on Artificial Intelligence, pp. 4908–4915 2020.
    [PDF] | [Link]


  1. [Sensors’19] Adversarial Samples on Android Malware Detection Systems for IoT Systems
    Xiaolei Liu, Xiaojiang Du, Xiaosong Zhang, Qingxin Zhu, Hao Wang, and Mohsen Guizani
    Sensors, 19(4) :974, 2019.
  2. [SCN’19] An Insider Threat Detection Approach Based on Mouse Dynamics and Deep Learning
    Teng Hu, Weina Niu, Xiaosong Zhang, Xiaolei Liu, Jiazhong Lu, and Yuan Liu
    Security and Communication Networks, 2019 2019.
  3. [SCN’19] Integrating Traffics with Network Device Logs for Anomaly Detection
    Jiazhong Lu, Fengmao Lv, Zhongliu Zhuo, Xiaosong Zhang, Xiaolei Liu, Teng Hu, and Wei Deng
    Security and Communication Networks, 2019.
  4. [CEE’19] Evolution-algorithm-based unmanned aerial vehicles path planning in complex environment
    Xiaolei Liu, Xiaojiang Du, Xiaosong Zhang, Qingxin Zhu, and Mohsen Guizani
    Computers & Electrical Engineering, 80 :106493, 2019.


  1. [Sensors’18] TLTD: a testing framework for learning-based IoT traffic detection systems
    Xiaolei Liu, Xiaosong Zhang, Nadra Guizani, Jiazhong Lu, Qingxin Zhu, and Xiaojiang Du
    Sensors, 18(8) :2630, 2018.
  2. [CSR’18] Adversarial Attacks Against Profile HMM Website Fingerprinting Detection Model
    Xiaolei Liu, Zhongliu Zhuo, Xiaojiang Du, Xiaosong Zhang, Qingxin Zhu, and Mohsen Guizani
    Cognitive Systems Research, 2018.

* Ranking of security conferences can be found here and here, but note they do not completely reflect my perception of these conferences.