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    王垚飞

    • 副教授 硕士生导师
    • 教师拼音名称:Wang Yaofei
    • 所在单位:计算机与信息学院
    • 办公地点:安徽省合肥市蜀山区丹霞路485号合肥工业大学翡翠湖校区翡翠科教楼A座604-4
    • 联系方式:wyf@hfut.edu.cn
    • 学位:工学博士学位
    • 在职信息:在职
    • 毕业院校:中国科学技术大学 网络空间安全学院

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    个人简介

    王垚飞,副教授(黄山学者学术骨干),硕士生导师,在USENIX Sec、S&P、IEEE TIFS、TDSC等信息安全和人工智能安全领域的顶级期刊和会议发表多篇论文。


    研究领域:在人工智能环境下,针对信息隐藏与多媒体内容安全进行深入探讨。研究内容具体涵盖利用预训练的大型模型构建生成式隐写技术,以实现隐蔽通信;同时,针对人工智能生成内容(Artificial Intelligence Generated Content, AIGC)嵌入数字水印技术,旨在进行版权保护以及AIGC的检测与识别。


    招生

    本人每年有全日制培养研究生名额5名。课题组长期与中国科学技术大学张卫明教授课题组、安全技术公司以及其它合作伙伴保持紧密的交流与合作关系。


    本研究小组现诚招2025年入学的硕士研究生,同时亦欢迎本科访问学生申请,名额有限,敬请提前联系。


    培养

    在生成式人工智能技术日新月异的当下,人与人的差距已不在于能解答多少已知问题,而在于能否提出具有洞见的真问题,并借助AI实现创新突破。本课题组秉持"AI为器,育人为本"的理念培养学生。让论文成为能力提升的自然产物,而非功利性追求的单一目标。


    本课题组对学生的要求如下: 1)诚实守信、热爱祖国;2)熟练运用AI工具构建"人机协同"的学习和工作范式;3)具备扎实的数学或编程基础;4)本科访问学生或需要外部推荐信的学生,应在本研究小组内至少学习一段时间。


    联系方式:wyf@hfut.edu.cn


    项目

    1、科技创新特区项目,面向大语言模型XX研究,主持,2023年12月-2025年11月,在研

    2、国家自然科学基金青年基金,彩色图像隐写非对称失真设计与鲁棒性增强方法研究,主持,2024年1月-2026年12月,在研

    3、基础加强重点项目子课题,XX理论构造研究,主持,2023年6月-2026年5月,在研

    4、XX技术预研项目,XX隐写分析技术研究,联合承研,2022年12月-2024年11月,结题


    课题组学生成员

    2024级:王心茹、郑裕丰、柯晨读,联合指导:曹文钊

    2023级:庞威龙、石子悦、联合指导:荣先进【博士】、蔡宇航

    2022级:联合指导:潘超【博士】

    2021级:联合指导:彭银银【博士】、裴刚、汤允金

    2020级:联合指导:张雨


    本科生竞赛及大创工作

    2024年,省级大创:《“追Gen溯源”——基于水印技术的大语言模型生成文本溯源系统》(2022级本科生:余奕俊、黄煜文、韩佳良、王磊、兰奕程)

    2023年,省级大创:《基于水印嵌入的大型语言模型检测系统》(结题优秀)(2021级本科生:汪超、张飞龙、杜述超、廖国仲、彭德帅)

    2023年,第五届全国高校计算机能力挑战赛:人工智能挑战赛全国决赛(国家级一等奖),嵌入式系统挑战赛全国决赛(国家级一等奖),“优秀指导老师”,嵌入式系统挑战赛区域赛(省级二等奖),程序设计挑战赛区域赛(省级二等奖),人工智能挑战赛区域赛(省级三等奖)(2021级本科生:汪超、王超凡、赵彦博)

    2023年,全国大学生信息安全竞赛省赛:信息安全作品竞赛(省级一等奖),网络攻防赛(省级二等奖)(2021级本科生:汪超、张飞龙、杜述超、牛政翰、王杜涛)

    恭喜2021级本科生汪超同学获得中国科学技术大学网络空间安全学院研究生offer!


    代表性论文

    1. Wang Y, Pei G, Chen K, et al. SparSamp: Efficient Provably Secure Steganography Based on Sparse Sampling[C]//34th USENIX Security Symposium, USENIX Security 2025, Seattle, WA, USA, 2025.(CCF A,信息安全领域四大顶级学术会议之一,相关报道:https://mp.weixin.qq.com/s/AlcisLxvln9V0A8bdlBVeQ

    2. Chao Pan, Donghui Hu*, Yaofei Wang*, Kejiang Chen, Yinyin Peng, Xianjin Rong, Chen Gu, Meng Li, "Rethinking Prefix-based Steganography for Enhanced Security and Efficiency," IEEE Transactions on Information Forensics and Security, Accept.( CCF A,中科院SCI一区,信息安全领域顶级期刊

    3. Y. Peng, Y. Wang*, D. Hu*, K. Chen, X. Rong, and W. Zhang, “LDStega: Practical and Robust Generative Image Steganography based on Latent Diffusion Models,” presented at the ACM Multimedia 2024, Jul. 2024. Accessed: Sep. 08, 2024. [Online]. Available: https://openreview.net/forum?id=kEqGgMgIluCCF A,相关报道:https://mp.weixin.qq.com/s/9YWILSAhKt4IBgbVtyj50w

    4. Q. Huang, C. Gu*, Y. Wang*, and D. Hu, “SpotAttack: Covering Spots on Surface to Attack LiDAR Based Autonomous Driving Systems,” IEEE Internet of Things Journal, pp. 1–1, 2024, doi: 10.1109/JIOT.2024.3452694.(中科院SCI一区,相关报道:https://mp.weixin.qq.com/s/Q7RAykFgjTLJvgHbq3_A8A

    5. Y. Peng, D. Hu*, Y. Wang*, K. Chen, G. Pei, and W. Zhang, “StegaDDPM: Generative Image Steganography based on Denoising Diffusion Probabilistic Model,” in Proceedings of the 31st ACM International Conference on Multimedia, in MM ’23. New York, NY, USA: Association for Computing Machinery, Oct. 2023, pp. 7143–7151. doi: 10.1145/3581783.3612514.(CCF A,相关报道:https://mp.weixin.qq.com/s/cb3mYwApwng1qjl5CksxXA

    6. Y. Wang, W. Zhang, W. Li, and N. Yu, “Non-Additive Cost Functions for JPEG Steganography Based on Block Boundary Maintenance,” IEEE Transactions on Information Forensics and Security, vol. 16, pp. 1117–1130, 2021, doi: 10.1109/TIFS.2020.3029908.( CCF A,中科院SCI一区,信息安全领域顶级期刊

    7. Y. Wang, W. Zhang, W. Li, X. Yu, and N. Yu, “Non-Additive Cost Functions for Color Image Steganography Based on Inter-Channel Correlations and Differences,” IEEE Transactions on Information Forensics and Security, vol. 15, pp. 2081–2095, 2020, doi: 10.1109/TIFS.2019.2956590.( CCF A,中科院SCI一区,信息安全领域顶级期刊

    8. Y. Wang, W. Li, W. Zhang, X. Yu, K. Liu, and N. Yu, “BBC++: Enhanced Block Boundary Continuity on Defining Non-Additive Distortion for JPEG Steganography,” IEEE Transactions on Circuits and Systems for Video Technology, pp. 1–1, 2020, doi: 10.1109/TCSVT.2020.3010554.(中科院SCI一区)

    9. Y. Peng, D. Hu*, G. Pei, and Y. Wang*, “Image Steganography with Deep Orthogonal Fusion of Multi-Scale Channel Attention,” in ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr. 2024, pp. 4850–4854. doi: 10.1109/ICASSP48485.2024.10446373.(CCF B

    10. X. Cheng, Y. Wang*, C. Liu, D. Hu*, and Z. Su, “HiFi-GANw: Watermarked Speech Synthesis Via Fine-Tuning of HiFi-GAN,” IEEE Signal Processing Letters, pp. 1–5, 2024, doi: 10.1109/LSP.2024.3456673.(中科院SCI二区)

    11. 王垚飞,张卫明,陈可江*,周文柏,俞能海, “图像非加性隐写综述,” 网络与信息安全学报, vol. 7, no. 6, pp. 1–10, Dec. 2021, doi: 10.11959/j.issn.2096-109x.2021102.

    12. J. Ding, K. Chen, Y. Wang, N. Zhao, W. Zhang, and N. Yu, “Discop: Provably Secure Steganography in Practice Based on ‘Distribution Copies,’” presented at the 2023 IEEE Symposium on Security and Privacy (SP), IEEE Computer Society, May 2023, pp. 2238–2255. doi: 10.1109/SP46215.2023.00155.(CCF A,信息安全领域四大顶级学术会议之一

    13. X. Wang, Y. Wang*, K. Chen, J. Ding, W. Zhang*, and N. Yu, “ICStega: Image Captioning-based Semantically Controllable Linguistic Steganography,” in ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Jun. 2023, pp. 1–5. doi: 10.1109/ICASSP49357.2023.10095722.(CCF B

    14. J. Feng, Y. Wang, K. Chen, W. Zhang, and N. Yu, “An Effective Steganalysis for Robust Steganography with Repetitive JPEG Compression,” in ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022, pp. 3084–3088. doi: 10.1109/ICASSP43922.2022.9747061.(CCF B

    15. K. Chen, H. Zhou, Y. Wang, M. Li, W. Zhang, and N. Yu, “Cover Reproducible Steganography via Deep Generative Models,” IEEE Transactions on Dependable and Secure Computing, pp. 1–13, 2022, doi: 10.1109/TDSC.2022.3217569.(中科院SCI一区)

    16. K. Zeng, K. Chen, W. Zhang, and Y. Wang, “Upward Robust Steganography Based on Overflow Alleviation,” IEEE Transactions on Multimedia, vol. 26, pp. 299–312, 2024, doi: 10.1109/TMM.2023.3264628.( 中科院SCI一区

    17. K. Zeng, K. Chen, W. Zhang, Y. Wang, and N. Yu, “Robust Steganography for High Quality Images,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 33, no. 9, pp. 4893–4906, Sep. 2023, doi: 10.1109/TCSVT.2023.3250750.(中科院SCI一区)

    18. Z. Su, M. Li, G. Zhang, Q. Wu, and Y. Wang, “Robust audio copy-move forgery detection on short forged slices using sliding window,” Journal of Information Security and Applications, vol. 75, p. 103507, Jun. 2023, doi: 10.1016/j.jisa.2023.103507.(中科院二区)

    19. X. Yu, K. Chen, Y. Wang, W. Li, W. Zhang, and N. Yu, “Robust adaptive steganography based on generalized dither modulation and expanded embedding domain,” Signal Processing, vol. 168, p. 107343, Mar. 2020, doi: 10.1016/j.sigpro.2019.107343.(中科院二区)

    20. K. Zeng, K. Chen, W. Zhang, Y. Wang, and N. Yu, “Improving Robust Adaptive Steganography via Minimizing Channel Errors,” Signal Processing, p. 108498, Feb. 2022, doi: 10.1016/j.sigpro.2022.108498.(中科院二区)

    21. W. Li, K. Chen, W. Zhang, H. Zhou, Y. Wang, and N. Yu, “JPEG Steganography with Estimated Side-information,” IEEE Transactions on Circuits and Systems for Video Technology, pp. 1–1, 2019, doi: 10.1109/TCSVT.2019.2925118.(中科院SCI一区)

    22. X. Yu, K. Chen, W. Zhang, Y. Wang, and N. Yu, “Improving the Embedding Strategy for Batch Adaptive Steganography,” in Digital Forensics and Watermarking, C. D. Yoo, Y.-Q. Shi, H. J. Kim, A. Piva, and G. Kim, Eds., in Lecture Notes in Computer Science. Cham: Springer International Publishing, 2019, pp. 248–260. doi: 10.1007/978-3-030-11389-6_19.



    教育经历

    [1] 2017.9 -- 2022.6
    中国科学技术大学

    [2] 2013.9 -- 2017.6
    西南交通大学