许润华 - 北京航空航天大学

个人简介

许润华，博士，北京航空航天大学计算机学院助理教授。主要研究方向为隐私安全计算、隐私保护机器学习、智能合约和区块链和可信隐私计算基础设施，已在TDSC、TOIT、SRDS、ICDCS等类国际权威学术期刊和会议上发表论文23篇、撰写英文专著2章节，申请隐私计算领域美国专利2项，获得IEEE CLOUD 2022最佳论文奖；担任IEEE TDSC、IEEE TIFS、Computer&Security、IEEE TII、IEEE JSAC、IEEE TSC、IEEE S&P、IEEE TNNLS、JISA等多个安全领域国际权威期刊和IEEE BigData、IEEE TPS等国际会议的程序委员会成员或审稿人，协助组织近五年IEEE CIC国际会议，参与创办并协助组织近五年IEEE TPS和IEEE CogMI国际会议；曾作为核心骨干参与美国NSF项目2项，美国NSA/DHS项目1项；曾作为IBM研究院研究科学家，负责IBM研究院联邦学习项目隐私安全方向。 Education 2015-2020, Ph.D. in Information Security, University of Pittsburgh, Pittsburgh, U.S. 2011-2014, M.S. in Computer Science, Beihang University, Beijing, China 2007-2011, B.E. in Software Engineering, Northwestern Polytechnical University, Xi'an, China

研究领域

隐私安全计算、隐私保护机器学习、智能合约和区块链和可信隐私计算基础设施

近期论文

查看导师最新文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

Runhua Xu, Bo Li, Chao Li, James Joshi, Shuai Ma, and Jianxin Li. "TAPFed: Threshold Secure Aggregation for Privacy-Preserving Federated Learning." (under peer-review) Chao Li, Balaji Palanisamy, Runhua Xu, Li Duan, Jiqiang Liu and Wei Wang. “How Hard is Takeover in DPoS Blockchains? Understanding the Security of Coin-based Voting Governance”. In Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security (CCS'23), November 26-30, 2023, Copenhagen, Denmark. ACM. (accepted) Chao Li, Runhua Xu, and Li Duan. “Characterizing Coin-Based Voting Governance in DPoS Blockchains”. Proceedings of the International AAAI Conference on Web and Social Media 17 (1):1148-52. [ PDF ] [ DOI ] Chao Li, Balaji Palanisamy, Runhua Xu, and Li Duan. “Cross-Consensus Measurement of Individual-level Decentralization in Blockchains”. IEEE 9th Intl Conference on Big Data Security on Cloud (BigDataSecurity 2023), New York, NY, USA, 2023, pp. 45-50. [ IEEE ] [ DOI ] Runhua Xu, Chao Li and James Joshi. "Blockchain-based Transparency Framework for Privacy Preserving Third-party Services." IEEE Transactions on Dependable and Secure Computing (IEEE TDSC). IEEE 2022. [ pdf ] [ arXiv ] [ IEEE Early Access ] Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, Heiko Ludwig. "DeTrust-FL: Efficient Privacy-Preserving Federated Learning in Decentralized Trust Setting." In 2022 IEEE International Conference on Cloud Computing (IEEE CLOUD 2022), Hybrid event in Barcelona, Spain, IEEE 2022. (Best Paper Award) [ pdf ] [ arXiv ] [ slides ] Nathalie Baracaldo and Runhua Xu. "Protecting Against Data Leakage in Federated Learning: What Approach Should You Choose?" Federated Learning: A Comprehensive Overview of Methods and Applications. Ludwig, H., Baracaldo, N. (eds). Springer, Cham. pp.281–312. 2022. [ Springer Link ] Runhua Xu, Nathalie Baracaldo, Yi Zhou, Annie Abay, and Ali Anwar. "Privacy-Preserving Vertical Federated Learning." Federated Learning: A Comprehensive Overview of Methods and Applications. Ludwig, H., Baracaldo, N. (eds). Springer, Cham. pp.417-438. 2022. [ Springer Link ] Runhua Xu, Nathalie Baracaldo and James B.D. Joshi. "Privacy-Preserving Machine Learning: Methods, Challenges and Directions ." (preprint) [ arXiv ] Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, James Joshi, Heiko Ludwig. "FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data." In Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security (AISec'21), pp. 181-192. 2021. [ arXiv ] [ S&P2021 Poster] Nathalie Baracaldo, Runhua Xu, Yi Zhou, Ali Anwar, and Heiko Ludwig. "Efficient private vertical federated learning." Patent Application 16/706,328, filed June 10, 2021. [ Link ] Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, and Heiko Ludwig. "Privacy-preserving federated learning." U.S. Patent Application 16/682,927, filed May 13, 2021. [ Link ] Runhua Xu, James B.D. Joshi and Chao Li. "NN-EMD: Efficiently Training Neural Networks using Encrypted Multi-sourced Datasets." IEEE Transactions on Dependable and Secure Computing (IEEE TDSC). IEEE 2021. [ arXiv ] [ appendix ] Chao Li, Balaji Palanisamy, Runhua Xu, Jinlai Xu and Jingzhe Wang. “SteemOps: Extracting and Analyzing Key Operations in Steemit Blockchain-based Social Media Platform.” In 11th ACM Conference on Data and Application Security and Privacy (ACM CODASPY 21), Virtual Event, USA. [ pdf ] [ dataset ] Runhua Xu and James B.D. Joshi “Revisiting Secure Computation Using Functional Encryption: Opportunities and Research Directions.” In The 2ed IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (TPS), IEEE 2020. [ pdf ] [ slides ] Chao Li, Balaji Palanisamy, Runhua Xu , Jian Wang, Jiqiang Liu “NF-Crowd: Nearly-free Blockchain-based Crowdsourcing.” 2020 International Symposium on Reliable Distributed Systems (SRDS20), Shanghai, China. IEEE 2020. [ pdf ] Runhua Xu and James B.D. Joshi “Trustworthy and Transparent Third Party Authority.” ACM Transactions on Internet Technology (ACM TOIT). ACM 2020. [ pdf ] Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar and Heiko Ludwig. "HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning." In 12th ACM Workshop on Artificial Intelligence and Security(AISec’19), November 15, 2019, London, United Kingdom. ACM 2019. [ pdf ] Runhua Xu, James B.D. Joshi and Prashant Krishnamurthy. “An Integrated Privacy Preserving Attribute Based Access Control Framework Supporting Secure Deduplication.” IEEE Transactions on Dependable and Secure Computing (IEEE TDSC). IEEE 2019. [ pdf ] Runhua Xu, James B.D. Joshi and Chao Li. "CryptoNN : Training Neural Networks over Encrypted Data." In The 39th IEEE International Conference on Distributed Computing Systems (ICDCS 2019), Dallas, USA. IEEE 2019. [ arXiv ] [ slides ] Chao Li, Balaji Palanisamy, and Runhua Xu. “Scalable and Privacy-preserving Design of On/Off-chain Smart Contracts.” In The First International Workshop on Blockchain and Data Management (BlockDM 2019), Macau SAR, China, IEEE 2019. [ arXiv ] [ slides ] Runhua Xu, Balaji Palanisamy and James B.D. Joshi. “QueryGuard: Privacy-preserving Latency-aware Query Optimization for Edge Computing.” In 2018 17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications(TrustCom-18), New York, USA. 2018. [ pdf ] [ slides ] Runhua Xu, James B.D. Joshi, Prashant Krishnamurthy and David Tipper. “Insider Threat Mitigation in Attribute based Encryption.” In 9th Annual National Cyber Summit (Research Track), Von Braun Center, Huntsville, AL, USA. 2017. [ pdf ] [ slides ] Runhua Xu and James B.D. Joshi. “Enabling Attribute Based Encryption as an Internet Service.” In 2016 IEEE 2nd International Conference on Collaboration and Internet Computing, Pittsburgh, USA. pp. 417-426.IEEE, 2016. [ pdf ] [ slides ] Runhua Xu and James B.D. Joshi. “An Integrated Privacy Preserving Attribute Based Access Control Framework.” In 2016 IEEE 9th International Conference on Cloud Computing (IEEE CLOUD 2016) (Research Track), San Francisco, USA. pp. 68-76. IEEE, 2016 [ pdf ] [ slides ] Runhua Xu, and Bo Lang. “A CP-ABE scheme with hidden policy and its application in cloud computing.” International Journal of Cloud Computing, Advanced Cloud and Big Data. vol. 4, no. 4, pp. 279-298. 2015. [ pdf ] Bo Lang, Runhua Xu, and Yawei Duan. “Self-contained Data Protection Scheme Based on CP-ABE.” EBusiness and Telecommunications, Communications in Computer and Information Science. pp. 306-321. 2014. [ pdf ] Runhua Xu, Yang Wang, and Bo Lang. “A Tree-Based CP-ABE Scheme with Hidden Policy Supporting Secure Data Sharing in Cloud Computing.” In Advanced Cloud and Big Data (CBD), 2013 International Conference on, Nanjing, China. pp. 51-57. IEEE, 2013. [ pdf ] [ slides ] Bo Lang, Runhua Xu, and Yawei Duan. “Extending the ciphertext-policy attribute based encryption scheme for supporting flexible access control.” In Security and Cryptography (SECRYPT), 2013 International Conference on, Reykjavik, Iceland. pp. 1-11. IEEE, 2013. [ pdf ] [ slides ]