Randomized Response: A Survey Technique for Eliminating Evasive Answer Bias

Sampling Techniques, Second Edition

G., C. W. (1963)

Some Theory of Sampling

E., D. W. (1950)

Sample Survey Methods and Theory, Volume I

H., H. M. (1953)

Sample Survey Methods and Theory, Volume II

H., H. M. (1953)

Sampling Opinions

F., S. F. (1963)

Inductive learning and local differential privacy for privacy-preserving offloading in mobile edge intelligent systemsPreprint

Tchaye-Kondi, J., Zhai, Y., & Zhu, L. (2021) · doi:10.36227/techrxiv.13698883

Localized Analysis Framework using Smartphones

Kim, B. (2016) · doi:10.18130/v3gs1z

Political Identity: Experimental Evidence on Anti-Americanism in Pakistan

Bursztyn, L., Ferman, B., Callen, M. J., et al. (2017) · AEA Randomized Controlled Trials · doi:10.1257/rct.2024

Vol. 11, No. 1 (Full Issue)

Editors, J. (2012) · Journal of Modern Applied Statistical Methods · doi:10.22237/jmasm/1335846480

Efficiency-optimized Data Perturbation in Local Differentially Private Federated LearningPreprint

Zhao, J., Yang, M., Zheng, J., Feng, J., & Matwin, S. (2022) · Research Square · doi:10.21203/rs.3.rs-1890894/v1

Accuracy Prediction of Negative Surveys

Liu, R., Yu, F., & Guo, M. (2022) · International Conference on Data Intelligence and Security (ICDIS) · doi:10.1109/icdis55630.2022.00025

Decipher Multi-Objectives gathering with liberate Dates Problem

Tarraya, T. A., Ganie, Z. A., & Khalid, M. (2022) · Journal of scientific research · doi:10.37398/jsr.2022.660516

Repeated Trials in Randomized Response Sampling

Walia, G. S. (2022) · Current Journal of Applied Science and Technology · doi:10.9734/cjast/2022/v41i484038

Privacy Preserving Recommendations for Social Networks

Macwan, K. R., Imine, A., & Rusinowitch, M. (2022) · International Conference on Social Networks Analysis, Management and Security (SNAMS) · doi:10.1109/snams58071.2022.10062760

Drivers and Passengers Maybe the Weakest Link in the CAV Data Privacy Defenses

Xiong, A., Cai, Z., & Wang, T. (2022) · International Workshop on Automotive and Autonomous Vehicle Security (AutoSec) · doi:10.14722/autosec.2022.23024

An optimization model using soft computing with the randomised response technique

Tarray, T. A., & Ganie, Z. A. (2023) · doi:10.1109/piecon56912.2023.10085835

Secure and Efficient Association Rule Mining over Encrypted Cloud Data

Agnihotri, A. (2020) · Türk bilgisayar ve matematik eğitimi dergisi · doi:10.17762/turcomat.v11i3.13610

Item-Oriented Personalized LDP for Discrete Distribution EstimationPreprint

Li, X., Zhu, H., Zhang, Z., et al. (2023) · Preprints.org · doi:10.20944/preprints202306.0289.v1

Item-Oriented Personalized LDP for Discrete Distribution EstimationPreprint

Li, X., Zhu, H., Zhang, Z., et al. (2023) · Preprints.org · doi:10.20944/preprints202306.0289.v2

Frequent Trajectory Mining with Local Differential Privacy

Huang, Y., & Wang, H. (2023) · International Conference on Advanced Computational Intelligence (ICACI) · doi:10.1109/icaci58115.2023.10146158

Research on big data privacy protection technology

Lu, T. (2023) · Applied and Computational Engineering · doi:10.54254/2755-2721/4/2023367

Estimating Location Distribution under Local Differential Privacy

Hong, Y., Zhu, Y., & Wang, W. (2023) · IEEE/CIC International Conference on Communications in China (ICCC) · doi:10.1109/iccc57788.2023.10233522

A class of estimators for finite population mean of a sensitive variable using Optional Randomized Response Technique(ORRT) ModelsPreprint

Kumar, S., Singh, H. P., Rani, C., et al. (2023) · Research Square · doi:10.21203/rs.3.rs-3330961/v1

Advances in estimation by the item sum technique in two move successive sampling

Priyanka, K., & Trisandhya, P. (2023) · Statistics in Transition New Series · doi:10.59170/stattrans-2023-055

การพฒนาเครองมอวดตวแปรทมความออนไหว: การประยกตอารอารทและเอสดเอสในการวดเจตคตของครตอเพศวถ

เข็มกลัด, ภ., & แกมเกตุ, ว. (2019) · doi:10.58837/chula.the.2019.1176

ESTIMATING SENSITIVE POPULATION PROPORTION USING A COMBINATION OF BINOMIAL AND HYPERGEOMETRIC RANDOMIZED RESPONSES BY DIRECT AND INVERSE MECHANISM

Dihidar, K., & Bhattacharya, M. (2017) · Statistics in Transition New Series · doi:10.59170/stattrans-2017-010

Joint Distribution Analysis of Multi-Dimensional Randomized Response

Wang, W., Zhang, Y., Yan, J., Zhou, Y., & Lu, L. (2023) · International Conference on Networking and Network Applications (NaNA) · doi:10.1109/nana60121.2023.00076

Trajectory Data Publishing Method with Local Differential Privacy

Wu, H., Shen, X., & Geng, C. (2023) · IEEE International Conference on Unmanned Systems (ICUS) · doi:10.1109/icus58632.2023.10318347

Disentangling the Linguistic Competence of Privacy-Preserving BERT

Arnold, S., Kemmerzell, N., & Schreiner, A. (2023) · BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP (BlackboxNLP) · doi:10.18653/v1/2023.blackboxnlp-1.5

Matching Noisy Keys for Obfuscation

Dickens, C., & Bax, E. T. (2023) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata59044.2023.10386396

Biases in responding

Streiner, D. L., Norman, G. R., & Cairney, J. (2024) · doi:10.1093/med/9780192869487.003.0006

Robust Optimal Control of Electric Vehicles Charging for Stochastic and Differentially Private DemandPreprint

Wu, T., Nikhil, R., Scaglione, A., et al. (2024) · doi:10.36227/techrxiv.171043423.30224326/v1

Indirect Questioning Technique Related to Sensitive Quantitative Variables with Options for Direct, Randomized and Item Count Responses

Shaw, P., & Pal, S. (2024) · International Journal of Statistical Sciences · doi:10.3329/ijss.v24i1.72035

Estimating Gain in Efficiency in Complicated Randomized Response Surveys versus Simpler Alternatives

Chaudhuri, A., & Patra, D. (2024) · International Journal of Statistical Sciences · doi:10.3329/ijss.v24i1.72021

On the Sample Size Determination based on the Randomized Response Surveys

Dihidar, K. (2024) · International Journal of Statistical Sciences · doi:10.3329/ijss.v24i1.72030

Data Stream Aggregation Mechanism Under Local Differential Privacy

Wang, J., & Wang, Y. (2024) · Communications in computer and information science · doi:10.1007/978-981-97-1332-5_17

Streaming Data Collection With a Private Sketch-Based Protocol

Li, Y., Lee, X., Peng, B., Palpanas, T., & Xue, J. (2024) · IEEE Internet of Things Journal · doi:10.1109/jiot.2024.3397908

A trajectory protection method based on differential privacy and semantic attributes

Liu, L. (2024) · Academic Journal of Computing & Information Science · doi:10.25236/ajcis.2024.070504

Personalized Privacy-Preserving Semi-Centralized Recommendation System in a Trust-Based Agent Network

Wen, Q., Leung, C. K.-S., & Pazdor, A. G. M. (2023) · IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) · doi:10.1109/trustcom60117.2023.00369

Collecting Clustering Coefficient of Distributed Graph Data with Shuffled Differential Privacy

Ding, H., Fu, P., Luo, Y., et al. (2024) · IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA) · doi:10.1109/ispa63168.2024.00103

Differentially Private Distributed Inference for Multicenter Clinical StudiesPreprint

Papachristou, M., & Rahimian, M. A. (2025) · medRxiv · doi:10.1101/2025.03.10.25323686

Active Gradient Manipulation for Privacy Breaching in Vertical Federated Learning

Jeter, T. R., Vu, M. N., Alharbi, R., Seo, J. T., & Thai, M. T. (2025) · IEEE Transactions on Artificial Intelligence · doi:10.1109/tai.2025.3556094

Private Selection with Heterogeneous Sensitivities

Antonova, D., Laro, A., McMillan, A., et al. (2025) · IEEE Conference on Secure and Trustworthy Machine Learning (SaTML) · doi:10.1109/satml64287.2025.00040

Ensemble Clustering Algorithm Based on Cluster Space Features Under Local Differential Privacy

Zhu, Z., Zhao, D., & Zhang, N. (2025) · International Conference on Cloud Computing and Big Data Analytics (ICCCBDA) · doi:10.1109/icccbda64898.2025.11030503

Collaborative Optimization of Label Protection in Large Language Models with an Adaptive Rényi Divergence Approach

Zhang, S., Liang, X., Du, R., et al. (2025) · International Conference on Computer Supported Cooperative Work in Design (CSCWD) · doi:10.1109/cscwd64889.2025.11033458

New and efficient estimators of population mean of sensitive study variable using optional randomized response model

Grover, L. K., & Kaur, A. (2025) · Communications in Statistics - Simulation and Computation · doi:10.1080/03610918.2025.2527889

GFD: An Effective Defense Against Targeted Poisoning Attacks for Local Differential Privacy Frequency Estimation

Wang, Y. Y., Zhu, Y., Wang, S., Xue, Q., & Wang, J. (2025) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2025.3597536 · Cited by 1

Privacy-Preserving Triangle Counting in Directed Graphs

Wei, Z., Liu, Q., Zhang, Z., et al. (2025) · Proceedings - International Conference on Data Engineering · doi:10.1109/icde65448.2025.00195

Numerical Data Collection Under Input-Discriminative Local Differential Privacy

Zhu, Y., Dai, S., Zhang, P., et al. (2025) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2025.3610932

An Efficient Private Set Frequency Query Scheme Under Local Differential Privacy

Zhang, E. Z., Guan, Y., Lu, R., et al. (2025) · International Conference on Communications · doi:10.1109/icc52391.2025.11161185

Lightweight Local Differential Privacy For High-dimensional Data

Zheng, T., Zhao, X., Liu, Z., Song, C., Li, Y., & Huang, Y. (2025) · International Conference on Computer Information Science and Application Technology (CISAT) · doi:10.1109/cisat66811.2025.11181983

New Randomization Technique to Estimate the Population Mean of Quantitative Sensitive Variable

Singh, C., Singh, V. L., & Singh, S. (2025) · International Journal of Mathematical Engineering and Management Sciences · doi:10.33889/ijmems.2025.10.6.090

Private Spectral Clustering Over Binary Stochastic Block Models

Seif, M., Koskela, A., & Goldsmith, A. J. (2025) · IEEE International Symposium on Information Theory (ISIT) · doi:10.1109/isit63088.2025.11195399

Online Frequency Estimation with Adaptive Locally Differentially Private Mechanisms

Düzel, G., & Yuldırım, S. (2025) · IEEE International Workshop on Machine Learning for Signal Processing (MLSP) · doi:10.1109/mlsp62443.2025.11204275

ELSS-LDP: A Local Differential Privacy Framework for Secure Emergency Logistics Management

Hu, C.-E., Peng, S., Xiao, X., et al. (2025) · International Conference on Mobile Internet, Cloud Computing and Information Security (MICCIS) · doi:10.1109/miccis66057.2025.00055

FedMPQ: Secure and Efficient Federated Learning with Multi-codebook Product Quantization

Xu, Y., Tang, Z., Hao, B., Xiao, X., & Zhang, J. (2025) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme59968.2025.11209457

Efficient Privacy-Preserving Image Retrieval With User Revocation in Mobile Cloud

Tang, Z., Fan, H., Ma, H., Chang, S., Gu, X., Fu, Z., & Li, B. (2025) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2025.3627185

Approx-PSI: Efficient Differentially Private Set Intersection-Based Analysis

Long, J., Liang, Z., Li, C., et al. (2025) · IEEE Transactions on Dependable and Secure Computing · doi:10.1109/tdsc.2025.3629820

Differentially Private Diffusion Model for Graph Generation

Zhang, G., Cheng, X., Zhang, Y., et al. (2025) · doi:10.1109/ijcnn64981.2025.11229325

Bayesian randomized item response modeling for sensitive measurements

Avetisyan, M. (2012) · doi:10.3990/1.9789036534802

Leveraging Homophily Under Local Differential Privacy for Effective Graph Neural Networks

Xie, Y., Ding, J., Xue, P., et al. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-06096-9_22

Privacy Mechanism Design based on Empirical Distributions

Grosse, L., Saeidian, S., Skoglund, M., et al. (2026) · Proceedings - Computer Security Foundations Workshop/Proceedings · doi:10.1109/csf68417.2026.00007

Necessity of Block Designs for Optimal Locally Private Distribution Estimation

Gentle, A. (2025) · IEEE Information Theory Workshop (ITW) · doi:10.1109/itw62417.2025.11240420 · Cited by 2

Multi-Task Semantic Communications With Bounded Privacy Leakage Constraint

Zamani, A., & Skoglund, M. (2026) · IEEE Transactions on Information Theory · doi:10.1109/tit.2026.3654430 · Cited by 1

Privacy-Preserving Model Transcription With Differentially Private Synthetic Distillation

Liu, B., Ge, S., Wang, P., Li, S., & Liu, T. (2026) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2026.3659110

Hierarchy-Aware Generative Modeling for Enhanced Label Differential Privacy

Hu, Y., & Wan, C. (2025) · Proceedings · doi:10.1109/icdm65498.2025.00137

Accurate and Efficient Frequency Estimation for Traffic Monitoring under Local Differential Privacy

Zhang, E. Z., Lu, R., & Hassanein, H. S. (2025) · Globecom · doi:10.1109/globecom59602.2025.11432675

CSyncProxy: Differentially Private Third-party Cookie Synchronization

Bellemare, S., Migault, D., Fung, B. C. M., et al. (2025) · Globecom · doi:10.1109/globecom59602.2025.11432524

Marginal Effect-Driven Participant Selection With Local Differential Privacy for Mobile Crowdsensing

Tian, M., Sun, Y., Han, A., Wang, Y., & Ji, H. (2026) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2026.3676248

PULSE-LDP: Pattern-Aware Unified Local Sampling for Efficient Local Differential Privacy

Tao, T., Cheng, S., Mo, L., & Wang, X. (2026) · IEEE Internet of Things Journal · doi:10.1109/jiot.2026.3682480

PEEL: A Poisoning-Exposing Encoding Mechanism for Local Differential Privacy

Shuai, L., Zhang, N., Tan, S., et al. (2026) · IEEE Open Journal of the Communications Society · doi:10.1109/ojcoms.2026.3687926

Prevalence and perceptions of performance-enhancing substances in esports

Schubert, M., Hufft, R., Richardson, A., et al. (2026) · Managing Sport and Leisure · doi:10.1080/23750472.2026.2663926

Walking a Private Road: Direction-Guided Perturbation for Trajectory Data Under Local Differential Privacy

Cao, X., Miao, Y., Zhang, X., et al. (2026) · IEEE Transactions on Dependable and Secure Computing · doi:10.1109/tdsc.2026.3707872

Protecting Individual Identities in Wastewater Data Through Statistical and Differential Privacy Analysis

Gao, J., Shah, R., Trieu, N., et al. (2026) · doi:10.1109/spw72489.2026.00017

Hadal: Centralized Label DP without a Trusted Party

Choncholas, J., Peceny, S., Agarwal, A., Raykova, M., Li, B., & Seth, K. (2026) · IEEE Symposium on Security and Privacy (S&P) · doi:10.1109/sp63933.2026.00122

CBUE: Conclusion Based Utility Evaluation for Differentially Private Categorical Data

Sarıkaya, F., Lu, S., Bater, J., & Hempstead, M. (2026) · IEEE Symposium on Security and Privacy (S&P) · doi:10.1109/sp63933.2026.00058

Sparse Estimation Under Local Differential Privacy at All Privacy Levels

Zhao, P., Ye, Q., Wang, S., Feng, J., Yue, S., Chen, Z., & Cao, X. (2026) · IEEE Symposium on Security and Privacy (S&P) · doi:10.1109/sp63933.2026.00234

Quantum Advantage in Locally Differentially Private Hypothesis Testing

Nam, S.-H., Park, H.-Y., Lee, S.-H., & Bae, J. (2026) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2026.3709807

A Locally Differential Private Coding-Assisted Succinct Histogram Data Collection Protocol

Liu, H.-P., & Mahdavifar, H. (2026) · International Conference on Communications · doi:10.1109/icc59461.2026.11587896

Multi-Shuffler: Decentralized Shuffling for Differential Privacy in Mobile Edge Computing

Chen, W., Huang, X., Zhu, Y., Han, T., Tong, W., & Zhong, S. (2026) · IEEE International Conference on Distributed Computing Systems (ICDCS) · doi:10.1109/2575-8411.2026.00040

ABC: Numerical Data Collection Under Local Differential Privacy Without Prior Knowledge

Baek, I., Kim, H., & Chung, Y. D. (2026) · Proceedings - International Conference on Data Engineering · doi:10.1109/icde65706.2026.00174

Achieving Personalized Edge-Level Privacy-Preserving Graph Neural Networks on Decentralized Graphs

Song, Z., Lei, D., Yuan, Y., et al. (2026) · IEEE Internet of Things Journal · doi:10.1109/jiot.2026.3721975

LLM-Powered KG Utility Evaluation Framework

Wu, P., Li, X., Fan, W., & Li, Q. (2026) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2026.3718940

Answering Federated Range Queries with Local Differential Privacy

Zhang, Y., Ye, Q., Liu, J., & Dong, W. (2026) · IEEE International Conference on Data Engineering (ICDE) · doi:10.1109/icde65706.2026.00216

Embedding-Space Anonymization for Privacy-Preserving AI Systems

Panagoulias, D. P., Tsichrintzi, E.-A., & Sakkopoulos, E. (2026) · International Conference on Computer, Information and Telecommunication Systems · doi:10.1109/cits70307.2026.11637145

Auditing Unexpected Leakage in Label Differential Privacy

Sekiguchi, H., Takagi, S., Hasegawa, S., et al. (2026) · IEEE Annual Computers, Software, and Applications Conference (COMPSAC) · doi:10.1109/compsac69091.2026.00093

Setup Protocols for Sender Anonymity

Huang, T., Zhang, J., & Ando, M. (2026) · IEEE Computer Security Foundations Workshop (CSFW) · doi:10.1109/csf68417.2026.00020 · Cited by 1

Bayesian Techniques in Randomized Response

Krzykowski, G. (2009) · Przegląd Statystyczny Statistical Review · doi:10.59139/ps.2009.02.5

Filtered Randomized Response Technique

Choi, K.-H. (2006) · Communications for Statistical Applications and Methods · doi:10.5351/ckss.2006.13.2.319

A ZIP model accounting for response bias in randomized response

Cruyff, M., Böckenholt, U., & van der Heijden, P. G. M. (2007) · Utrecht University Repository (Utrecht University)

Estimation of a Finite Population Mean and Total Using Population Ranks of Sample Units

Öztürk, Ö. (2015) · Journal of Agricultural Biological and Environmental Statistics · doi:10.1007/s13253-015-0231-4 · Cited by 14

Randomized Response Procedure for the Estimation of the Population Ratio using Ranked Set Sampling

Moreno, A. S., Bouza, C. N., Sautto, J. M., et al. (2016) · Journal of Mathematics and Statistics · doi:10.3844/jmssp.2016.107.114 · Cited by 6

On Comparisons of With and Without Replacement Sampling Strategies for Estimating Finite Population Mean in Randomized Response Surveys

Sengupta, S. (2015) · Sankhya B · doi:10.1007/s13571-015-0107-1 · Cited by 3

Estimation of Population Parameters Using the Technique of Sub-sampling from Non-respondents in Sample Surveys: A Review

Khare, B. B. (2014) · Proceedings of the National Academy of Sciences India Section A Physical Sciences · doi:10.1007/s40010-013-0107-3 · Cited by 2