Efficient Top-k Query Algorithms Using K-Skyband Partition. - Neil Zhenqiang Gong; Guangzhong Sun; Jing Yuan 007; Yanjing Zhong (Infoscale, 2009)

Protecting Privacy in Location-Based Services Using K-Anonymity without Cloaked Region. - Neil Zhenqiang Gong; Guangzhong Sun; Xing Xie 001 (Mobile Data Management, 2010)

Efficient Approximate Top-k Query Algorithm Using Cube Index. - Dongqu Chen; Guang-Zhong Sun; Neil Zhenqiang Gong (APWeb, 2011)

Efficient Top-K Query Algorithms Using Density Index. - Dongqu Chen; Guang-Zhong Sun; Neil Zhenqiang Gong; Xiaoqiang Zhong (ICAIC (1), 2011)

Predicting Links and Inferring Attributes using a Social-Attribute Network (SAN) - Neil Zhenqiang Gong; Ameet Talwalkar; Lester W. Mackey; Ling Huang 001; Eui Chul Richard Shin; Emil Stefanov; Elaine Shi; Dawn Song (CoRR, 2011)

Evolution of social-attribute networks: measurements, modeling, and implications using google+. - Neil Zhenqiang Gong; Wenchang Xu; Ling Huang 001; Prateek Mittal; Emil Stefanov; Vyas Sekar; Dawn Song (Internet Measurement Conference, 2012)

On the Feasibility of Internet-Scale Author Identification. - Arvind Narayanan; Hristo S. Paskov; Neil Zhenqiang Gong; John Bethencourt; Emil Stefanov; Eui Chul Richard Shin; Dawn Song (IEEE Symposium on Security and Privacy, 2012)

Reciprocity in Social Networks: Measurements, Predictions, and Implications - Neil Zhenqiang Gong; Wenchang Xu; Dawn Song (CoRR, 2013)

Connect the dots by understanding user status and transitions. - Xuan Bao; Yilin Shen; Neil Zhenqiang Gong; Hongxia Jin; Bing Hu 001 (UbiComp Adjunct, 2014)

Reciprocal versus parasocial relationships in online social networks. - Neil Zhenqiang Gong; Wenchang Xu (Soc. Netw. Anal. Min., 2014)

SybilBelief: A Semi-Supervised Learning Approach for Structure-Based Sybil Detection. - Neil Zhenqiang Gong; Mario Frank 001; Prateek Mittal (IEEE Trans. Inf. Forensics Secur., 2014)

On the Security of Trustee-Based Social Authentications. - Neil Zhenqiang Gong; Di Wang (IEEE Trans. Inf. Forensics Secur., 2014)

Joint Link Prediction and Attribute Inference Using a Social-Attribute Network. - Neil Zhenqiang Gong; Ameet Talwalkar; Lester W. Mackey; Ling Huang 001; Eui Chul Richard Shin; Emil Stefanov; Elaine Shi; Dawn Song (ACM Trans. Intell. Syst. Technol., 2014)

Protecting Your Children from Inappropriate Content in Mobile Apps: An Automatic Maturity Rating Framework. - Bing Hu 001; Bin Liu 045; Neil Zhenqiang Gong; Deguang Kong; Hongxia Jin (CIKM, 2015)

On Your Social Network De-anonymizablity: Quantification and Large Scale Evaluation with Seed Knowledge. - Shouling Ji; Weiqing Li; Neil Zhenqiang Gong; Prateek Mittal; Raheem A. Beyah (NDSS, 2015)

Personalized Mobile App Recommendation: Reconciling App Functionality and User Privacy Preference. - Bin Liu 045; Deguang Kong; Lei Cen; Neil Zhenqiang Gong; Hongxia Jin; Hui Xiong 001 (WSDM, 2015)

SybilFrame: A Defense-in-Depth Framework for Structure-Based Sybil Detection. - Peng Gao 008; Neil Zhenqiang Gong; Sanjeev R. Kulkarni; Kurt Thomas; Prateek Mittal (CoRR, 2015)

Towards Forgery-Resistant Touch-based Biometric Authentication on Mobile Devices. - Neil Zhenqiang Gong; Mathias Payer; Reza Moazzezi; Mario Frank 001 (CoRR, 2015)

What You Submit Is Who You Are: A Multimodal Approach for Deanonymizing Scientific Publications. - Mathias Payer; Ling Huang 001; Neil Zhenqiang Gong; Kevin Borgolte; Mario Frank 001 (IEEE Trans. Inf. Forensics Secur., 2015)

Forgery-Resistant Touch-based Authentication on Mobile Devices. - Neil Zhenqiang Gong; Mathias Payer; Reza Moazzezi; Mario Frank 001 (AsiaCCS, 2016)

You Are Who You Know and How You Behave: Attribute Inference Attacks via Users' Social Friends and Behaviors. - Neil Zhenqiang Gong; Bin Liu 045 (USENIX Security Symposium, 2016)

Seed-Based De-Anonymizability Quantification of Social Networks. - Shouling Ji; Weiqing Li; Neil Zhenqiang Gong; Prateek Mittal; Raheem A. Beyah (IEEE Trans. Inf. Forensics Secur., 2016)

Structural Analysis of User Choices for Mobile App Recommendation. - Bin Liu 045; Yao Wu; Neil Zhenqiang Gong; Junjie Wu 002; Hui Xiong 001; Martin Ester (ACM Trans. Knowl. Discov. Data, 2016)

Mitigating Evasion Attacks to Deep Neural Networks via Region-based Classification. - Xiaoyu Cao; Neil Zhenqiang Gong (ACSAC, 2017)

Random Walk Based Fake Account Detection in Online Social Networks. - Jinyuan Jia 001; Binghui Wang; Neil Zhenqiang Gong (DSN, 2017)

PIANO: Proximity-Based User Authentication on Voice-Powered Internet-of-Things Devices. - Neil Zhenqiang Gong; Altay Ozen; Yu Wu; Xiaoyu Cao; Richard Shin; Dawn Song; Hongxia Jin; Xuan Bao (ICDCS, 2017)

GANG: Detecting Fraudulent Users in Online Social Networks via Guilt-by-Association on Directed Graphs. - Binghui Wang; Neil Zhenqiang Gong; Hao Fu (ICDM, 2017)

SybilSCAR: Sybil detection in online social networks via local rule based propagation. - Binghui Wang; Le Zhang 006; Neil Zhenqiang Gong (INFOCOM, 2017)

Fake Co-visitation Injection Attacks to Recommender Systems. - Guolei Yang; Neil Zhenqiang Gong; Ying Cai (NDSS, 2017)

AttriInfer: Inferring User Attributes in Online Social Networks Using Markov Random Fields. - Jinyuan Jia 001; Binghui Wang; Le Zhang 006; Neil Zhenqiang Gong (WWW, 2017)

Robust Spammer Detection in Microblogs: Leveraging User Carefulness. - Hao Fu; Xing Xie 001; Yong Rui; Neil Zhenqiang Gong; Guangzhong Sun; Enhong Chen (ACM Trans. Intell. Syst. Technol., 2017)

Poisoning Attacks to Graph-Based Recommender Systems. - Minghong Fang; Guolei Yang; Neil Zhenqiang Gong; Jia Liu 002 (ACSAC, 2018)

EviHunter: Identifying Digital Evidence in the Permanent Storage of Android Devices via Static Analysis. - Chris Chao-Chun Cheng; Chen Shi; Neil Zhenqiang Gong; Yong Guan (CCS, 2018)

SYBILFUSE: Combining Local Attributes with Global Structure to Perform Robust Sybil Detection. - Peng Gao 008; Binghui Wang; Neil Zhenqiang Gong; Sanjeev R. Kulkarni; Kurt Thomas; Prateek Mittal (CNS, 2018)

SybilBlind: Detecting Fake Users in Online Social Networks Without Manual Labels. - Binghui Wang; Le Zhang 006; Neil Zhenqiang Gong (RAID, 2018)

Stealing Hyperparameters in Machine Learning. - Binghui Wang; Neil Zhenqiang Gong (IEEE Symposium on Security and Privacy, 2018)

A Dynamic Taint Analysis Tool for Android App Forensics. - Zhen Xu; Chen Shi; Chris Chao-Chun Cheng; Neil Zhenqiang Gong; Yong Guan (IEEE Symposium on Security and Privacy Workshops, 2018)

AttriGuard: A Practical Defense Against Attribute Inference Attacks via Adversarial Machine Learning. - Jinyuan Jia 001; Neil Zhenqiang Gong (USENIX Security Symposium, 2018)

Attribute Inference Attacks in Online Social Networks. - Neil Zhenqiang Gong; Bin Liu 045 (ACM Trans. Priv. Secur., 2018)

MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples. - Jinyuan Jia 001; Ahmed Salem 001; Michael Backes 001; Yang Zhang 016; Neil Zhenqiang Gong (CCS, 2019)

Attacking Graph-based Classification via Manipulating the Graph Structure. - Binghui Wang; Neil Zhenqiang Gong (CCS, 2019)

Detecting Fake Accounts in Online Social Networks at the Time of Registrations. - Dong Yuan 006; Yuanli Miao; Neil Zhenqiang Gong; Zheng Yang; Qi Li 002; Dawn Song; Qian Wang 002; Xiao Liang (CCS, 2019)

Calibrate: Frequency Estimation and Heavy Hitter Identification with Local Differential Privacy via Incorporating Prior Knowledge. - Jinyuan Jia 001; Neil Zhenqiang Gong (INFOCOM, 2019)

Characterizing and Detecting Malicious Accounts in Privacy-Centric Mobile Social Networks: A Case Study. - Zenghua Xia; Chang Liu 021; Neil Zhenqiang Gong; Qi Li 002; Yong Cui 001; Dawn Song (KDD, 2019)

Graph-based Security and Privacy Analytics via Collective Classification with Joint Weight Learning and Propagation. - Binghui Wang; Jinyuan Jia 001; Neil Zhenqiang Gong (NDSS, 2019)

Defending against Machine Learning based Inference Attacks via Adversarial Examples: Opportunities and Challenges. - Jinyuan Jia 001; Neil Zhenqiang Gong (CoRR, 2019)

Structure-Based Sybil Detection in Social Networks via Local Rule-Based Propagation. - Binghui Wang; Jinyuan Jia 001; Le Zhang 006; Neil Zhenqiang Gong (IEEE Trans. Netw. Sci. Eng., 2019)

Defending Against Machine Learning Based Inference Attacks via Adversarial Examples: Opportunities and Challenges. - Jinyuan Jia 001; Neil Zhenqiang Gong (Adaptive Autonomous Secure Cyber Systems, 2020)

Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized Smoothing. - Jinyuan Jia 001; Xiaoyu Cao; Binghui Wang; Neil Zhenqiang Gong (ICLR, 2020)

State Estimation via Inference on a Probabilistic Graphical Model - A Different Perspective. - Luke Myers; Binghui Wang; Neil Zhenqiang Gong; Daji Qiao (ISGT, 2020)

Local Model Poisoning Attacks to Byzantine-Robust Federated Learning. - Minghong Fang; Xiaoyu Cao; Jinyuan Jia 001; Neil Zhenqiang Gong (USENIX Security Symposium, 2020)

Influence Function based Data Poisoning Attacks to Top-N Recommender Systems. - Minghong Fang; Neil Zhenqiang Gong; Jia Liu 002 (WWW, 2020)

Certified Robustness of Community Detection against Adversarial Structural Perturbation via Randomized Smoothing. - Jinyuan Jia 001; Binghui Wang; Xiaoyu Cao; Neil Zhenqiang Gong (WWW, 2020)

On Certifying Robustness against Backdoor Attacks via Randomized Smoothing. - Binghui Wang; Xiaoyu Cao; Jinyuan Jia 001; Neil Zhenqiang Gong (CoRR, 2020)

Certified Robustness of Nearest Neighbors against Data Poisoning Attacks. - Jinyuan Jia 001; Xiaoyu Cao; Neil Zhenqiang Gong (CoRR, 2020)

Provably Secure Federated Learning against Malicious Clients. - Xiaoyu Cao; Jinyuan Jia 001; Neil Zhenqiang Gong (AAAI, 2021)

Intrinsic Certified Robustness of Bagging against Data Poisoning Attacks. - Jinyuan Jia 001; Xiaoyu Cao; Neil Zhenqiang Gong (AAAI, 2021)

Semi-Supervised Node Classification on Graphs: Markov Random Fields vs. Graph Neural Networks. - Binghui Wang; Jinyuan Jia 001; Neil Zhenqiang Gong (AAAI, 2021)

On Detecting Growing-Up Behaviors of Malicious Accounts in Privacy-Centric Mobile Social Networks. - Zijie Yang; Binghui Wang; Haoran Li; Dong Yuan 006; Zhuotao Liu; Neil Zhenqiang Gong; Chang Liu 021; Qi Li 002; Xiao Liang; Shaofeng Hu (ACSAC, 2021)

IPGuard: Protecting Intellectual Property of Deep Neural Networks via Fingerprinting the Classification Boundary. - Xiaoyu Cao; Jinyuan Jia 001; Neil Zhenqiang Gong (AsiaCCS, 2021)

Robust and Verifiable Information Embedding Attacks to Deep Neural Networks via Error-Correcting Codes. - Jinyuan Jia 001; Binghui Wang; Neil Zhenqiang Gong (AsiaCCS, 2021)

EncoderMI: Membership Inference against Pre-trained Encoders in Contrastive Learning. - Hongbin Liu 005; Jinyuan Jia 001; Wenjie Qu 001; Neil Zhenqiang Gong (CCS, 2021)

PointGuard: Provably Robust 3D Point Cloud Classification. - Hongbin Liu 005; Jinyuan Jia 001; Neil Zhenqiang Gong (CVPR, 2021)

Understanding the Security of Deepfake Detection. - Xiaoyu Cao; Neil Zhenqiang Gong (ICDF2C, 2021)

On the Intrinsic Differential Privacy of Bagging. - Hongbin Liu 005; Jinyuan Jia 001; Neil Zhenqiang Gong (IJCAI, 2021)

Unveiling Fake Accounts at the Time of Registration: An Unsupervised Approach. - Xiao Liang; Zheng Yang; Binghui Wang; Shaofeng Hu; Zijie Yang; Dong Yuan 006; Neil Zhenqiang Gong; Qi Li 002; Fang He (KDD, 2021)

Certified Robustness of Graph Neural Networks against Adversarial Structural Perturbation. - Binghui Wang; Jinyuan Jia 001; Xiaoyu Cao; Neil Zhenqiang Gong (KDD, 2021)

FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping. - Xiaoyu Cao; Minghong Fang; Jia Liu 002; Neil Zhenqiang Gong (NDSS, 2021)

Data Poisoning Attacks to Deep Learning Based Recommender Systems. - Hai Huang 014; Jiaming Mu; Neil Zhenqiang Gong; Qi Li 002; Bin Liu 045; Mingwei Xu (NDSS, 2021)

Practical Blind Membership Inference Attack via Differential Comparisons. - Bo Hui 002; Yuchen Yang 001; Haolin Yuan; Philippe Burlina; Neil Zhenqiang Gong; Yinzhi Cao (NDSS, 2021)

Backdoor Attacks to Graph Neural Networks. - Zaixi Zhang; Jinyuan Jia 001; Binghui Wang; Neil Zhenqiang Gong (SACMAT, 2021)

Data Poisoning Attacks to Local Differential Privacy Protocols. - Xiaoyu Cao; Jinyuan Jia 001; Neil Zhenqiang Gong (USENIX Security Symposium, 2021)

Stealing Links from Graph Neural Networks. - Xinlei He 001; Jinyuan Jia 001; Michael Backes 001; Neil Zhenqiang Gong; Yang Zhang 016 (USENIX Security Symposium, 2021)

Data Poisoning Attacks and Defenses to Crowdsourcing Systems. - Minghong Fang; Minghao Sun; Qi Li 012; Neil Zhenqiang Gong; Jin Tian 001; Jia Liu 002 (WWW, 2021)

Linear-Time Self Attention with Codeword Histogram for Efficient Recommendation. - Yongji Wu; Defu Lian; Neil Zhenqiang Gong; Lu Yin; Mingyang Yin; Jingren Zhou 001; Hongxia Yang (WWW, 2021)

Rethinking Lifelong Sequential Recommendation with Incremental Multi-Interest Attention. - Yongji Wu; Lu Yin; Defu Lian; Mingyang Yin; Neil Zhenqiang Gong; Jingren Zhou 001; Hongxia Yang (CoRR, 2021)

FaceGuard: Proactive Deepfake Detection. - Yuankun Yang; Chenyue Liang; Hongyu He; Xiaoyu Cao; Neil Zhenqiang Gong (CoRR, 2021)

10 Security and Privacy Problems in Self-Supervised Learning. - Jinyuan Jia 001; Hongbin Liu 005; Neil Zhenqiang Gong (CoRR, 2021)

LogExtractor: Extracting digital evidence from android log messages via string and taint analysis. - Chris Chao-Chun Cheng; Chen Shi; Neil Zhenqiang Gong; Yong Guan (Digit. Investig., 2021)

Certified Robustness of Nearest Neighbors against Data Poisoning and Backdoor Attacks. - Jinyuan Jia 001; Yupei Liu; Xiaoyu Cao; Neil Zhenqiang Gong (AAAI, 2022)

AFLGuard: Byzantine-robust Asynchronous Federated Learning. - Minghong Fang; Jia Liu 002; Neil Zhenqiang Gong; Elizabeth S. Bentley (ACSAC, 2022)

GraphTrack: A Graph-based Cross-Device Tracking Framework. - Binghui Wang; Tianchen Zhou; Song Li 006; Yinzhi Cao; Neil Zhenqiang Gong (AsiaCCS, 2022)

Understanding Disparate Effects of Membership Inference Attacks and their Countermeasures. - Da Zhong 001; Haipei Sun; Jun Xu 024; Neil Zhenqiang Gong; Wendy Hui Wang (AsiaCCS, 2022)

StolenEncoder: Stealing Pre-trained Encoders in Self-supervised Learning. - Yupei Liu; Jinyuan Jia 001; Hongbin Liu 005; Neil Zhenqiang Gong (CCS, 2022)

Membership Inference Attack in Face of Data Transformations. - Jiyu Chen; Yiwen Guo; Hao Chen 003; Neil Gong 001 (CNS, 2022)

MPAF: Model Poisoning Attacks to Federated Learning based on Fake Clients. - Xiaoyu Cao; Neil Zhenqiang Gong (CVPR Workshops, 2022)

HERO: hessian-enhanced robust optimization for unifying and improving generalization and quantization performance. - Huanrui Yang; Xiaoxuan Yang 001; Neil Zhenqiang Gong; Yiran Chen 001 (DAC, 2022)

Semi-Leak: Membership Inference Attacks Against Semi-supervised Learning. - Xinlei He 001; Hongbin Liu 005; Neil Zhenqiang Gong; Yang Zhang 016 (ECCV (31), 2022)

Addressing Heterogeneity in Federated Learning via Distributional Transformation. - Haolin Yuan; Bo Hui 002; Yuchen Yang 001; Philippe Burlina; Neil Zhenqiang Gong; Yinzhi Cao (ECCV (38), 2022)

Almost Tight L0-norm Certified Robustness of Top-k Predictions against Adversarial Perturbations. - Jinyuan Jia 001; Binghui Wang; Xiaoyu Cao; Hongbin Liu 005; Neil Zhenqiang Gong (ICLR, 2022)

Deep Neural Network Piration without Accuracy Loss. - Aritra Ray; Jinyuan Jia 001; Sohini Saha; Jayeeta Chaudhuri; Neil Zhenqiang Gong; Krishnendu Chakrabarty (ICMLA, 2022)

FLDetector: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clients. - Zaixi Zhang; Xiaoyu Cao; Jinyuan Jia 001; Neil Zhenqiang Gong (KDD, 2022)

MultiGuard: Provably Robust Multi-label Classification against Adversarial Examples. - Jinyuan Jia 001; Wenjie Qu 001; Neil Zhenqiang Gong (NeurIPS, 2022)

BadEncoder: Backdoor Attacks to Pre-trained Encoders in Self-Supervised Learning. - Jinyuan Jia 001; Yupei Liu; Neil Zhenqiang Gong (SP, 2022)

PoisonedEncoder: Poisoning the Unlabeled Pre-training Data in Contrastive Learning. - Hongbin Liu 005; Jinyuan Jia 001; Neil Zhenqiang Gong (USENIX Security Symposium, 2022)

Poisoning Attacks to Local Differential Privacy Protocols for Key-Value Data. - Yongji Wu; Xiaoyu Cao; Jinyuan Jia 001; Neil Zhenqiang Gong (USENIX Security Symposium, 2022)

StolenEncoder: Stealing Pre-trained Encoders. - Yupei Liu; Jinyuan Jia 001; Hongbin Liu 005; Neil Zhenqiang Gong (CoRR, 2022)

Fine-grained Poisoning Attacks to Local Differential Privacy Protocols for Mean and Variance Estimation. - Xiaoguang Li; Neil Zhenqiang Gong; Ninghui Li; Wenhai Sun; Hui Li 006 (CoRR, 2022)

CorruptEncoder: Data Poisoning based Backdoor Attacks to Contrastive Learning. - Jinghuai Zhang; Hongbin Liu 005; Jinyuan Jia 001; Neil Zhenqiang Gong (CoRR, 2022)

SoK: Inference Attacks and Defenses in Human-Centered Wireless Sensing. - Wei Sun 013; Tingjun Chen; Neil Gong 001 (CoRR, 2022)

Distributed information encoding and decoding using self-organized spatial patterns. - Jia Lu; Ryan Tsoi; Nan Luo; Yuanchi Ha; Shangying Wang; Minjun Kwak; Yasa Baig; Nicole Moiseyev; Shari Tian; Alison Zhang; Neil Zhenqiang Gong; Lingchong You (Patterns, 2022)

FLCert: Provably Secure Federated Learning Against Poisoning Attacks. - Xiaoyu Cao; Zaixi Zhang; Jinyuan Jia 001; Neil Zhenqiang Gong (IEEE Trans. Inf. Forensics Secur., 2022)

Evading Watermark based Detection of AI-Generated Content. - Zhengyuan Jiang; Jinghuai Zhang; Neil Zhenqiang Gong (CCS, 2023)

PointCert: Point Cloud Classification with Deterministic Certified Robustness Guarantees. - Jinghuai Zhang; Jinyuan Jia 001; Hongbin Liu 005; Neil Zhenqiang Gong (CVPR, 2023)

Fortifying Federated Learning against Membership Inference Attacks via Client-level Input Perturbation. - Yuchen Yang 001; Haolin Yuan; Bo Hui 002; Neil Zhenqiang Gong; Neil Fendley; Philippe Burlina; Yinzhi Cao (DSN, 2023)

IPCert: Provably Robust Intellectual Property Protection for Machine Learning. - Zhengyuan Jiang; Minghong Fang; Neil Zhenqiang Gong (ICCV (Workshops), 2023)

REaaS: Enabling Adversarially Robust Downstream Classifiers via Robust Encoder as a Service. - Wenjie Qu 001; Jinyuan Jia 001; Neil Zhenqiang Gong (NDSS, 2023)

FedRecover: Recovering from Poisoning Attacks in Federated Learning using Historical Information. - Xiaoyu Cao; Jinyuan Jia 001; Zaixi Zhang; Neil Zhenqiang Gong (SP, 2023)

PORE: Provably Robust Recommender Systems against Data Poisoning Attacks. - Jinyuan Jia 001; Yupei Liu; Yuepeng Hu; Neil Zhenqiang Gong (USENIX Security Symposium, 2023)

Fine-grained Poisoning Attack to Local Differential Privacy Protocols for Mean and Variance Estimation. - Xiaoguang Li; Ninghui Li; Wenhai Sun; Neil Zhenqiang Gong; Hui Li 006 (USENIX Security Symposium, 2023)

PrivateFL: Accurate, Differentially Private Federated Learning via Personalized Data Transformation. - Yuchen Yang 001; Bo Hui 002; Haolin Yuan; Neil Zhenqiang Gong; Yinzhi Cao (USENIX Security Symposium, 2023)

SneakyPrompt: Evaluating Robustness of Text-to-image Generative Models' Safety Filters. - Yuchen Yang 001; Bo Hui 002; Haolin Yuan; Neil Zhenqiang Gong; Yinzhi Cao (CoRR, 2023)

PromptBench: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts. - Kaijie Zhu; Jindong Wang 001; Jiaheng Zhou; Zichen Wang; Hao Chen 102; Yidong Wang; Linyi Yang; Wei Ye 004; Neil Zhenqiang Gong; Yue Zhang 004; Xing Xie 001 (CoRR, 2023)

Securing Visually-Aware Recommender Systems: An Adversarial Image Reconstruction and Detection Framework. - Minglei Yin; Bin Liu 045; Neil Zhenqiang Gong; Xin Li 005 (CoRR, 2023)

DyVal: Graph-informed Dynamic Evaluation of Large Language Models. - Kaijie Zhu; Jiaao Chen; Jindong Wang 001; Neil Zhenqiang Gong; Diyi Yang; Xing Xie 001 (CoRR, 2023)

Prompt Injection Attacks and Defenses in LLM-Integrated Applications. - Yupei Liu; Yuqi Jia; Runpeng Geng; Jinyuan Jia 001; Neil Zhenqiang Gong (CoRR, 2023)

Competitive Advantage Attacks to Decentralized Federated Learning. - Yuqi Jia; Minghong Fang; Neil Zhenqiang Gong (CoRR, 2023)

Mendata: A Framework to Purify Manipulated Training Data. - Zonghao Huang; Neil Gong 001; Michael K. Reiter (CoRR, 2023)

Generation-based fuzzing? Don't build a new generator, reuse! - Chengbin Pang; Hongbin Liu 005; Yifan Wang; Neil Zhenqiang Gong; Bing Mao 001; Jun Xu 024 (Comput. Secur., 2023)

Visual Hallucinations of Multi-modal Large Language Models. - Wen Huang; Hongbin Liu 005; Minxin Guo; Neil Gong 001 (ACL (Findings), 2024)

GradSafe: Detecting Jailbreak Prompts for LLMs via Safety-Critical Gradient Analysis. - Yueqi Xie; Minghong Fang; Renjie Pi; Neil Gong 001 (ACL (1), 2024)

AACD '24: 11th ACM Workshop on Adaptive and Autonomous Cyber Defense. - Neil Gong 001; Qi Li 002; Xiaoli Zhang 003 (CCS, 2024)

PLeak: Prompt Leaking Attacks against Large Language Model Applications. - Bo Hui 002; Haolin Yuan; Neil Gong 001; Philippe Burlina; Yinzhi Cao (CCS, 2024)

Byzantine-Robust Decentralized Federated Learning. - Minghong Fang; Zifan Zhang; Hairi; Prashant Khanduri; Jia Liu 002; Songtao Lu; Yuchen Liu 001; Neil Gong 001 (CCS, 2024)

A General Framework for Data-Use Auditing of ML Models. - Zonghao Huang; Neil Zhenqiang Gong; Michael K. Reiter (CCS, 2024)

Optimization-based Prompt Injection Attack to LLM-as-a-Judge. - Jiawen Shi; Zenghui Yuan; Yinuo Liu; Yue Huang 001; Pan Zhou 001; Lichao Sun 001; Neil Zhenqiang Gong (CCS, 2024)

Data Poisoning Based Backdoor Attacks to Contrastive Learning. - Jinghuai Zhang; Hongbin Liu 005; Jinyuan Jia 001; Neil Zhenqiang Gong (CVPR, 2024)

Unlocking the Potential of Federated Learning: The Symphony of Dataset Distillation via Deep Generative Latents. - Yuqi Jia; Saeed Vahidian; Jingwei Sun 002; Jianyi Zhang; Vyacheslav Kungurtsev; Neil Zhenqiang Gong; Yiran Chen 001 (ECCV (78), 2024)

Certifiably Robust Image Watermark. - Zhengyuan Jiang; Moyang Guo; Yuepeng Hu; Jinyuan Jia 001; Neil Zhenqiang Gong (ECCV (77), 2024)

ReCaLL: Membership Inference via Relative Conditional Log-Likelihoods. - Roy Xie; Junlin Wang; Ruomin Huang; Minxing Zhang; Rong Ge; Jian Pei 001; Neil Gong 001; Bhuwan Dhingra (EMNLP, 2024)

MetaTool Benchmark for Large Language Models: Deciding Whether to Use Tools and Which to Use. - Yue Huang 001; Jiawen Shi; Yuan Li 032; Chenrui Fan; Siyuan Wu 001; Qihui Zhang; Yixin Liu 002; Pan Zhou 001; Yao Wan 001; Neil Zhenqiang Gong; Lichao Sun 001 (ICLR, 2024)

DyVal: Dynamic Evaluation of Large Language Models for Reasoning Tasks. - Kaijie Zhu; Jiaao Chen; Jindong Wang 001; Neil Zhenqiang Gong; Diyi Yang; Xing Xie 001 (ICLR, 2024)

Position: TrustLLM: Trustworthiness in Large Language Models. - Yue Huang; Lichao Sun 001; Haoran Wang 005; Siyuan Wu 001; Qihui Zhang; Yuan Li; Chujie Gao; Yixin Huang; Wenhan Lyu; Yixuan Zhang; Xiner Li; Hanchi Sun; et al. (ICML, 2024)

FedREDefense: Defending against Model Poisoning Attacks for Federated Learning using Model Update Reconstruction Error. - Yueqi Xie; Minghong Fang; Neil Zhenqiang Gong (ICML, 2024)

PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts. - Kaijie Zhu; Jindong Wang 001; Jiaheng Zhou; Zichen Wang; Hao Chen 102; Yidong Wang; Linyi Yang; Wei Ye 004; Yue Zhang 004; Neil Gong 001; Xing Xie 001 (LAMPS@CCS, 2024)

AudioMarkBench: Benchmarking Robustness of Audio Watermarking. - Hongbin Liu 005; Moyang Guo; Zhengyuan Jiang; Lun Wang; Neil Gong 001 (NeurIPS, 2024)

Pre-trained Encoders in Self-Supervised Learning Improve Secure and Privacy-preserving Supervised Learning. - Hongbin Liu 005; Wenjie Qu 001; Jinyuan Jia 001; Neil Zhenqiang Gong (SP (Workshops), 2024)

SneakyPrompt: Jailbreaking Text-to-image Generative Models. - Yuchen Yang 001; Bo Hui 002; Haolin Yuan; Neil Gong 001; Yinzhi Cao (SP, 2024)

Mudjacking: Patching Backdoor Vulnerabilities in Foundation Models. - Hongbin Liu 005; Michael K. Reiter; Neil Zhenqiang Gong (USENIX Security Symposium, 2024)

Formalizing and Benchmarking Prompt Injection Attacks and Defenses. - Yupei Liu; Yuqi Jia; Runpeng Geng; Jinyuan Jia 001; Neil Zhenqiang Gong (USENIX Security Symposium, 2024)

ModelGuard: Information-Theoretic Defense Against Model Extraction Attacks. - Minxue Tang; Anna Dai; Louis DiValentin; Aolin Ding; Amin Hass; Neil Zhenqiang Gong; Yiran Chen 001; Hai (Helen) Li (USENIX Security Symposium, 2024)

Robust Federated Learning Mitigates Client-side Training Data Distribution Inference Attacks. - Yichang Xu; Ming Yin; Minghong Fang; Neil Zhenqiang Gong (WWW (Companion Volume), 2024)

Poisoning Federated Recommender Systems with Fake Users. - Ming Yin; Yichang Xu; Minghong Fang; Neil Zhenqiang Gong (WWW, 2024)

TrustLLM: Trustworthiness in Large Language Models. - Lichao Sun 001; Yue Huang 001; Haoran Wang 005; Siyuan Wu 001; Qihui Zhang; Chujie Gao; Yixin Huang; Wenhan Lyu; Yixuan Zhang 001; Xiner Li; Zhengliang Liu; Yixin Liu 002; et al. (CoRR, 2024)

GradSafe: Detecting Unsafe Prompts for LLMs via Safety-Critical Gradient Analysis. - Yueqi Xie; Minghong Fang; Renjie Pi; Neil Zhenqiang Gong (CoRR, 2024)

Watermark-based Detection and Attribution of AI-Generated Content. - Zhengyuan Jiang; Moyang Guo; Yuepeng Hu; Neil Zhenqiang Gong (CoRR, 2024)

SoK: Gradient Leakage in Federated Learning. - Jiacheng Du; Jiahui Hu; Zhibo Wang 001; Peng Sun 003; Neil Zhenqiang Gong; Kui Ren 001 (CoRR, 2024)

PoisonedFL: Model Poisoning Attacks to Federated Learning via Multi-Round Consistency. - Yueqi Xie; Minghong Fang; Neil Zhenqiang Gong (CoRR, 2024)

Concealing Backdoor Model Updates in Federated Learning by Trigger-Optimized Data Poisoning. - Yujie Zhang; Neil Gong 001; Michael K. Reiter (CoRR, 2024)

Stable Signature is Unstable: Removing Image Watermark from Diffusion Models. - Yuepeng Hu; Zhengyuan Jiang; Moyang Guo; Neil Zhenqiang Gong (CoRR, 2024)

Self-Cognition in Large Language Models: An Exploratory Study. - Dongping Chen; Jiawen Shi; Yao Wan 001; Pan Zhou 001; Neil Zhenqiang Gong; Lichao Sun 001 (CoRR, 2024)

Tracing Back the Malicious Clients in Poisoning Attacks to Federated Learning. - Yuqi Jia; Minghong Fang; Hongbin Liu 005; Jinghuai Zhang; Neil Zhenqiang Gong (CoRR, 2024)

Refusing Safe Prompts for Multi-modal Large Language Models. - Zedian Shao; Hongbin Liu 005; Yuepeng Hu; Neil Zhenqiang Gong (CoRR, 2024)

Evaluating Large Language Model based Personal Information Extraction and Countermeasures. - Yupei Liu; Yuqi Jia; Jinyuan Jia 001; Neil Zhenqiang Gong (CoRR, 2024)

Automatically Generating Visual Hallucination Test Cases for Multimodal Large Language Models. - Zhongye Liu; Hongbin Liu 005; Yuepeng Hu; Zedian Shao; Neil Zhenqiang Gong (CoRR, 2024)

Making LLMs Vulnerable to Prompt Injection via Poisoning Alignment. - Zedian Shao; Hongbin Liu 005; Jaden Mu; Neil Zhenqiang Gong (CoRR, 2024)

AI-generated Image Detection: Passive or Watermark? - Moyang Guo; Yuepeng Hu; Zhengyuan Jiang; Zeyu Li; Amir Sadovnik; Arka Daw; Neil Gong 001 (CoRR, 2024)

Securing the Future of GenAI: Policy and Technology. - Mihai Christodorescu; Ryan Craven; Soheil Feizi; Neil Zhenqiang Gong; Mia Hoffmann; Somesh Jha; Zhengyuan Jiang; Mehrdad Saberi Kamarposhti; John C. Mitchell; Jessica Newman; Emelia Probasco; Yanjun Qi; et al. (IACR Cryptol. ePrint Arch., 2024)

SoK: Secure Human-centered Wireless Sensing. - Wei Sun 013; Tingjun Chen; Neil Gong 001 (Proc. Priv. Enhancing Technol., 2024)

Link Stealing Attacks Against Inductive Graph Neural Networks. - Yixin Wu 001; Xinlei He 001; Pascal Berrang; Mathias Humbert; Michael Backes 001; Neil Zhenqiang Gong; Yang Zhang 016 (Proc. Priv. Enhancing Technol., 2024)

Model Poisoning Attacks to Federated Learning via Multi-Round Consistency. - Yueqi Xie; Minghong Fang; Neil Zhenqiang Gong (CVPR, 2025)

BadToken: Token-level Backdoor Attacks to Multi-modal Large Language Models. - Zenghui Yuan; Jiawen Shi; Pan Zhou 001; Neil Zhenqiang Gong; Lichao Sun 001 (CVPR, 2025)

A Transfer Attack to Image Watermarks. - Yuepeng Hu; Zhengyuan Jiang; Moyang Guo; Neil Zhenqiang Gong (ICLR, 2025)

StringLLM: Understanding the String Processing Capability of Large Language Models. - Xilong Wang; Hao Fu; Jindong Wang 001; Neil Zhenqiang Gong (ICLR, 2025)

DataSentinel: A Game-Theoretic Detection of Prompt Injection Attacks. - Yupei Liu; Yuqi Jia; Jinyuan Jia 001; Dawn Song; Neil Zhenqiang Gong (SP, 2025)

GRID: Protecting Training Graph from Link Stealing Attacks on GNN Models. - Jiadong Lou; Xu Yuan 001; Rui Zhang; Xingliang Yuan; Neil Zhenqiang Gong; Nian-Feng Tzeng (SP, 2025)

Provably Robust Federated Reinforcement Learning. - Minghong Fang; Xilong Wang; Neil Zhenqiang Gong (WWW, 2025)

GraphRAG under Fire. - Jiacheng Liang; Yuhui Wang 003; Changjiang Li; Rongyi Zhu; Tanqiu Jiang; Neil Gong 001; Ting Wang 006 (CoRR, 2025)

Safety at Scale: A Comprehensive Survey of Large Model Safety. - Xingjun Ma; Yifeng Gao; Yixu Wang; Ruofan Wang; Xin Wang; Ye Sun; Yifan Ding; Hengyuan Xu; Yunhao Chen; Yunhan Zhao; Hanxun Huang; Yige Li; et al. (CoRR, 2025)

On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective. - Yue Huang 001; Chujie Gao; Siyuan Wu 001; Haoran Wang 005; Xiangqi Wang; Yujun Zhou 010; Yanbo Wang 005; Jiayi Ye; Jiawen Shi; Qihui Zhang; Yuan Li 032; Han Bao 003; et al. (CoRR, 2025)

A Survey of Model Extraction Attacks and Defenses in Distributed Computing Environments. - Kaixiang Zhao; Lincan Li; Kaize Ding; Neil Zhenqiang Gong; Yue Zhao 016; Yushun Dong (CoRR, 2025)

SafeText: Safe Text-to-image Models via Aligning the Text Encoder. - Yuepeng Hu; Zhengyuan Jiang; Neil Zhenqiang Gong (CoRR, 2025)

Jailbreaking Safeguarded Text-to-Image Models via Large Language Models. - Zhengyuan Jiang; Yuepeng Hu; Yuchen Yang 001; Yinzhi Cao; Neil Zhenqiang Gong (CoRR, 2025)

A Survey on Post-training of Large Language Models. - Guiyao Tie; Zeli Zhao; Dingjie Song; Fuyang Wei; Rong Zhou; Yurou Dai; Wen Yin; Zhejian Yang; Jiangyue Yan; Yao Su 003; Zhenhan Dai; Yifeng Xie; et al. (CoRR, 2025)

Poisoned-MRAG: Knowledge Poisoning Attacks to Multimodal Retrieval Augmented Generation. - Yinuo Liu; Zenghui Yuan; Guiyao Tie; Jiawen Shi; Pan Zhou 001; Lichao Sun 001; Neil Zhenqiang Gong (CoRR, 2025)

Large Reasoning Models in Agent Scenarios: Exploring the Necessity of Reasoning Capabilities. - Xueyang Zhou; Guiyao Tie; Guowen Zhang; Weidong Wang; Zhigang Zuo; Di Wu; Duanfeng Chu; Pan Zhou 001; Lichao Sun 001; Neil Zhenqiang Gong (CoRR, 2025)

Instance-Level Data-Use Auditing of Visual ML Models. - Zonghao Huang; Neil Zhenqiang Gong; Michael K. Reiter (CoRR, 2025)

Zero-shot Autonomous Microscopy for Scalable and Intelligent Characterization of 2D Materials. - Jingyun Yang; Ruoyan Avery Yin; Chi Jiang; Yuepeng Hu; Xiaokai Zhu; Xingjian Hu; Sutharsika Kumar; Xiao Wang 012; Xiaohua Zhai; Keran Rong; Yunyue Zhu; Tianyi Zhang; et al. (CoRR, 2025)

Prompt Injection Attack to Tool Selection in LLM Agents. - Jiawen Shi; Zenghui Yuan; Guiyao Tie; Pan Zhou 001; Neil Zhenqiang Gong; Lichao Sun 001 (CoRR, 2025)

EnvInjection: Environmental Prompt Injection Attack to Multi-modal Web Agents. - Xilong Wang; John Bloch; Zedian Shao; Yuepeng Hu; Shuyan Zhou; Neil Zhenqiang Gong (CoRR, 2025)

Automating Safety Enhancement for LLM-based Agents with Synthetic Risk Scenarios. - Xueyang Zhou; Weidong Wang; Lin Lu; Jiawen Shi; Guiyao Tie; Yongtian Xu; Lixing Chen; Pan Zhou 001; Neil Zhenqiang Gong; Lichao Sun 001 (CoRR, 2025)

A Critical Evaluation of Defenses against Prompt Injection Attacks. - Yuqi Jia; Zedian Shao; Yupei Liu; Jinyuan Jia 001; Dawn Song; Neil Zhenqiang Gong (CoRR, 2025)

VideoMarkBench: Benchmarking Robustness of Video Watermarking. - Zhengyuan Jiang; Moyang Guo; Kecen Li; Yuepeng Hu; Yupu Wang; Zhicong Huang; Cheng Hong; Neil Zhenqiang Gong (CoRR, 2025)

A Survey on Model Extraction Attacks and Defenses for Large Language Models. - Kaixiang Zhao; Lincan Li; Kaize Ding; Neil Zhenqiang Gong; Yue Zhao 016; Yushun Dong (CoRR, 2025)

Mitigating Watermark Stealing Attacks in Generative Models via Multi-Key Watermarking. - Toluwani Aremu; Noor Hussein; Munachiso Nwadike; Samuele Poppi; Jie Zhang; Karthik Nandakumar; Neil Gong 001; Nils Lukas (CoRR, 2025)

PromptArmor: Simple yet Effective Prompt Injection Defenses. - Tianneng Shi; Kaijie Zhu; Zhun Wang; Yuqi Jia; Will Cai; Weida Liang; Haonan Wang; Hend Alzahrani; Joshua Lu; Kenji Kawaguchi; Basel Alomair; Xuandong Zhao; et al. (CoRR, 2025)