Public-Key Cryptosystems Based on Composite Degree Residuosity Classes

New directions in cryptography

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A public key cryptosystem and a signature scheme based on discrete logarithms

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Random oracles are practical

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A Public-Key Cryptosystem Based On Algebraic Coding Theory

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Hiding information and signatures in trapdoor knapsacks

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A secure and optimally efficient multi‐authority election scheme

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A new public-key cryptosystem as secure as factoring

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Privacy-preserving anomaly detection in cloud with lightweight homomorphic encryption

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Privacy-Preserving Outsourced Clinical Decision Support System in the Cloud

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SecGrid: A Secure and Efficient SGX-Enabled Smart Grid System With Rich Functionalities

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Resource Fairness and Composability of Cryptographic Protocols

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Security and Privacy Issues in Deep Learning

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Federated Learning for Object Detection in Autonomous Vehicles

Jallepalli, D., Ravikumar, N. C., Badarinath, P. V., Uchil, S., & Suresh, M. A. (2021) · 2021 IEEE Seventh International Conference on Big Data Computing Service and Applications (BigDataService) · doi:10.1109/bigdataservice52369.2021.00018 · Cited by 56

Efficiently Stealing your Machine Learning Models

Reith, R. N., Schneider, T. H., & Tkachenko, O. (2019) · ACM Workshop on Privacy in the Electronic Society (WPES) · doi:10.1145/3338498.3358646 · Cited by 59

Privacy Preserving and Efficient Data Collection Scheme for AMI Networks Using Deep Learning

Ibrahem, M. I., Mahmoud, M. M. E. A., Fouda, M. M., Alsolami, F. J., Alasmary, W., & Shen, X. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3077897 · Cited by 56

Pasta: A Case for Hybrid Homomorphic Encryption

Dobraunig, C., Grassi, L., Helminger, L., Rechberger, C., Schofnegger, M., & Walch, R. (2023) · IACR Transactions on Cryptographic Hardware and Embedded Systems · doi:10.46586/tches.v2023.i3.30-73 · Cited by 56

Healthchain: A Privacy Protection System for Medical Data Based on Blockchain

Wang, B., & Li, Z. (2021) · Future Internet · doi:10.3390/fi13100247 · Cited by 56

Enabling Efficient Spatial Keyword Queries on Encrypted Data With Strong Security Guarantees

Wang, X., Ma, J., Li, F., Liu, X., Miao, Y., & Deng, R. H. (2021) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2021.3118880 · Cited by 56

Secure and Privacy-Preserving Formation Control for Networked Marine Surface Vehicles With Sampled-Data Interactions

Liang, C., Ge, M., Xu, J., Liu, Z., & Liu, F. (2021) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2021.3133902 · Cited by 56

BlindFL: Vertical Federated Machine Learning without Peeking into Your Data

Fu, F., Xue, H., Cheng, Y., Tao, Y., & Cui, B. (2022) · ACM SIGMOD International Conference on Management of Data (SIGMOD) · doi:10.1145/3514221.3526127 · Cited by 60

Edge-Assisted Public Key Homomorphic Encryption for Preserving Privacy in Mobile Crowdsensing

Ganjavi, R., & Sharafat, A. R. (2022) · IEEE Transactions on Services Computing · doi:10.1109/tsc.2022.3172136 · Cited by 56

PriMPSO: A Privacy-Preserving Multiagent Particle Swarm Optimization Algorithm

Zhao, B., Liu, X., Song, A., Chen, W., Lai, K., Zhang, J., & Deng, R. H. (2022) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2022.3224169 · Cited by 56

RFed: Robustness-Enhanced Privacy-Preserving Federated Learning Against Poisoning Attack

Miao, Y., Yan, X., Li, X., Xu, S., Liu, X., Li, H., & Deng, R. H. (2024) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2024.3402113 · Cited by 59

Practical Private DNA String Searching and Matching through Efficient Oblivious Automata Evaluation

Frikken, K. B. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-03007-9_6 · Cited by 56

Outsourced Biometric Identification With Privacy

Hu, S., Li, M., Wang, Q., Chow, S. S. M., & Du, M. (2018) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2018.2819128 · Cited by 56

Privacy Preserving Location-Aware Personalized Web Service Recommendations

Badsha, S., Yi, X., Khalil, I., Liu, D., Nepal, S., Bertino, E., & Lam, K. Y. (2021) · IEEE Transactions on Services Computing · doi:10.1109/tsc.2018.2839587 · Cited by 56

Verify-Your-Vote: A Verifiable Blockchain-Based Online Voting Protocol

Chaieb, M., Yousfi, S., Lafourcade, P., & Robbana, R. (2019) · Lecture notes in business information processing · doi:10.1007/978-3-030-11395-7_2 · Cited by 56

Privacy-Preserving Reinforcement Learning Design for Patient-Centric Dynamic Treatment Regimes

Liu, X., Deng, R. H., Choo, K. R., & Yang, Y. (2019) · IEEE Transactions on Emerging Topics in Computing · doi:10.1109/tetc.2019.2896325 · Cited by 56

CryptDICE: Distributed data protection system for secure cloud data storage and computation

Rafique, A., Landuyt, D. V., Beni, E. H., Lagaisse, B., & Joosen, W. (2020) · Information Systems · doi:10.1016/j.is.2020.101671 · Cited by 56

Five Practical Attacks for “Optimistic Mixing for Exit-Polls”

Wikström, D. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-24654-1_12 · Cited by 56

FLASHE: Additively Symmetric Homomorphic Encryption for Cross-Silo Federated LearningPreprint

Jiang, Z., Wang, W., & Liu, Y. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2109.00675 · Cited by 78

On Security in Publish/Subscribe Services: A Survey

Esposito, C., & Ciampi, M. (2015) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2014.2364616 · Cited by 55

Highly Efficient Privacy Preserving Location-Based Services with Enhanced One-Round Blind Filter

Li, X., Zhu, Y., & Wang, J. (2019) · IEEE Transactions on Emerging Topics in Computing · doi:10.1109/tetc.2019.2926385 · Cited by 55

Efficient Function Queryable and Privacy Preserving Data Aggregation Scheme in Smart Grid

Zhan, Y., Zhou, L., Wang, B., Duan, P., & Zhang, B. (2022) · IEEE Transactions on Parallel and Distributed Systems · doi:10.1109/tpds.2022.3153930 · Cited by 55

A privacy-preserving decentralized credit scoring method based on multi-party information

He, H., Wang, Z., Jain, H. K., Jiang, C., & Yang, S. (2022) · Decision Support Systems · doi:10.1016/j.dss.2022.113910 · Cited by 56

A privacy preserving federated learning scheme using homomorphic encryption and secret sharing

Shi, Z., Yang, Z., Hassan, A., Li, F., & Ding, X. (2022) · Telecommunication Systems · doi:10.1007/s11235-022-00982-3 · Cited by 58

Quantized Distributed Economic Dispatch for Microgrids: Paillier Encryption–Decryption Scheme

Chen, W., Wang, Z., Ge, Q., Dong, H., & Liu, G. P. (2024) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2023.3348816 · Cited by 55

A Privacy-Enhancing Content-Based Publish/Subscribe System Using Scalar Product Preserving Transformations

Choi, S., Ghinita, G., & Bertino, E. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-15364-8_32 · Cited by 55

On the Practical and Security Issues of Batch Content Distribution Via Network Coding

Li, Q., Chiu, D. M., & Lui, J. C. S. (2006) · IEEE International Conference on Network Protocols (ICNP) · doi:10.1109/icnp.2006.320209 · Cited by 55

Performance Comparison of Secure Comparison Protocols

Kerschbaum, F., Biswas, D., & de Hoogh, S. J. A. (2009) · International Workshop on Database and Expert Systems Applications (DEXA) · doi:10.1109/dexa.2009.37 · Cited by 55

SHADE: Secure HAmming DistancE Computation from Oblivious Transfer

Bringer, J., Chabanne, H., & Patey, A. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-41320-9_11 · Cited by 55

A secure data aggregation protocol for fog computing based smart grids

Okay, F. Y., & Özdemi̇r, S. (2018) · IEEE International Conference on Compatibility, Power Electronics and Power Engineering · doi:10.1109/cpe.2018.8372598 · Cited by 55

Efficient Privacy-Preserving Multi-Dimensional Data Aggregation Scheme in Smart Grid

Ming, Y., Zhang, X., & Shen, X. (2019) · IEEE Access · doi:10.1109/access.2019.2903533 · Cited by 55

Privacy-preserving and high-accurate outsourced disease predictor on random forest

Ma, Z., Ma, J., Miao, Y., & Liu, X. (2019) · Information Sciences · doi:10.1016/j.ins.2019.05.025 · Cited by 55

Privacy-Preserving Implicit Authentication Protocol Using Cosine Similarity for Internet of Things

Wei, F., Vijayakumar, P., Kumar, N., Zhang, R., & Cheng, Q. (2020) · IEEE Internet of Things Journal · doi:10.1109/jiot.2020.3031486 · Cited by 55

An Efficient Learning Framework for Federated XGBoost Using Secret Sharing and Distributed Optimization

Xie, L., Liu, J., Lu, S., Chang, T., & Shi, Q. (2022) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3523061 · Cited by 57

TrustWorker: A Trustworthy and Privacy-Preserving Worker Selection Scheme for Blockchain-Based Crowdsensing

Gao, S., Chen, X., Zhu, J., Dong, X., & Ma, J. (2021) · IEEE Transactions on Services Computing · doi:10.1109/tsc.2021.3103938 · Cited by 54

Privacy-enhancing distributed protocol for data aggregation based on blockchain and homomorphic encryption

Regueiro, C., Seco-Aguirre, I., de Diego, S., Lage, Ó., & Etxebarria, L. (2021) · Information Processing & Management · doi:10.1016/j.ipm.2021.102745 · Cited by 54

Efficient Data Collaboration Using Multi-Party Privacy Preserving Machine Learning Framework

Salam, A., Abrar, M. Y. B. T., Ullah, F., Khan, I. A., Amin, F., & Choi, G. S. (2023) · IEEE Access · doi:10.1109/access.2023.3339750 · Cited by 54

A Multi-Modal Vertical Federated Learning Framework Based on Homomorphic Encryption

Gong, M., Zhang, Y., Gao, Y., Qin, A. K., Wu, Y., Wang, S., & Zhang, Y. (2023) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2023.3340994 · Cited by 54

Distributed Paillier Cryptosystem without Trusted Dealer

Nishide, T., & Sakurai, K. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-17955-6_4 · Cited by 54

Preserving privacy of feedback providers in decentralized reputation systems

Hasan, O., Brunie, L., & Bertino, E. (2011) · Computers & Security · doi:10.1016/j.cose.2011.12.003 · Cited by 54

An efficient and probabilistic secure bit-decomposition

Samanthula, B. K., Hu, C., & Jiang, W. (2013) · ACM Asia Conference on Computer and Communications Security (ASIA CCS) · doi:10.1145/2484313.2484386 · Cited by 54

Privacy preserving ID3 using Gini Index over horizontally partitioned data

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Homomorphic Encryption with CCA Security

Prabhakaran, M., & Rosulek, M. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-70583-3_54 · Cited by 54

Privacy-preserving matching of dna profiles

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Cryptographic Assumptions: A Position Paper

Goldwasser, S., & Kalai, Y. T. (2015) · Lecture notes in computer science · doi:10.1007/978-3-662-49096-9_21 · Cited by 54

A Protocol for Privately Reporting Ad Impressions at Scale

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Location Privacy in Cognitive Radio Networks: A Survey

Grissa, M., Hamdaoui, B., & Yavuz, A. A. (2017) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2017.2693965 · Cited by 54

Privacy-Preserving Comparison of Variable-Length Data With Application to Biometric Template Protection

Gomez‐Barrero, M., Javier Galbally, A., Morales, A., & Fiérrez, J. (2017) · IEEE Access · doi:10.1109/access.2017.2691578 · Cited by 54

SPABox: Safeguarding Privacy During Deep Packet Inspection at a MiddleBox

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Privacy-Preserving Data Aggregation against False Data Injection Attacks in Fog Computing

Zhang, Y., Zhao, J., Zheng, D., Deng, K., Ren, F., Zheng, X., & Shu, J. (2018) · Sensors · doi:10.3390/s18082659 · Cited by 54

Privacy-Preserving Deep Learning Based on Multiparty Secure Computation: A Survey

Zhang, Q., Xin, C., & Wu, H. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3058638 · Cited by 53

Fairness-Aware and Privacy-Preserving Friend Matching Protocol in Mobile Social Networks

Zhu, H., Du, S., Li, M., & Gao, Z. (2013) · IEEE Transactions on Emerging Topics in Computing · doi:10.1109/tetc.2013.2279541 · Cited by 53

Effective Activation Functions for Homomorphic Evaluation of Deep Neural Networks

Obla, S., Gong, X., Aloufi, A., Hu, P., & Takabi, D. (2020) · IEEE Access · doi:10.1109/access.2020.3017436 · Cited by 53

Practical Privacy-Preserving Data Science With Homomorphic Encryption: An Overview

Iezzi, M. (2020) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata50022.2020.9377989 · Cited by 53

Privacy-Preserving Decentralized Aggregation for Federated Learning

Jeon, B., Ferdous, S. M., Rahman, M. R., & Walid, A. (2021) · IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) · doi:10.1109/infocomwkshps51825.2021.9484437 · Cited by 56

A Verifiable Privacy-Preserving Machine Learning Prediction Scheme for Edge-Enhanced HCPSs

Li, X., He, J., Vijayakumar, P., Zhang, X., & Chang, V. I. C. (2021) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2021.3110808 · Cited by 53

On preserving user privacy in Smart Grid advanced metering infrastructure applications

Saputro, N., & Akkaya, K. (2013) · Security and Communication Networks · doi:10.1002/sec.706 · Cited by 53

Genodroid

Cristofaro, E. D., Faber, S., Gasti, P., & Tsudik, G. (2012) · ACM Workshop on Privacy in the Electronic Society (WPES) · doi:10.1145/2381966.2381980 · Cited by 53

A Commitment-Consistent Proof of a Shuffle

Wikström, D. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-02620-1_28 · Cited by 53

Efficient and Privacy-Preserving Polygons Spatial Query Framework for Location-Based Services

Zhu, H., Liu, F., & Li, H. (2016) · IEEE Internet of Things Journal · doi:10.1109/jiot.2016.2553083 · Cited by 53

Lightweight and efficient privacy-preserving data aggregation approach for the Smart Grid

Badra, M., & Zeadally, S. (2017) · Ad Hoc Networks · doi:10.1016/j.adhoc.2017.05.011 · Cited by 53

Secure Model Fusion for Distributed Learning Using Partial Homomorphic Encryption

Liu, C., Chakraborty, S., & Verma, D. C. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-17277-0_9 · Cited by 55

Cloud-Based Outsourcing for Enabling Privacy-Preserving Large-Scale Non-Negative Matrix Factorization

Fu, A., Chen, Z., Mu, Y., Susilo, W., Sun, Y., & Jie, W. (2019) · IEEE Transactions on Services Computing · doi:10.1109/tsc.2019.2937484 · Cited by 53

A Survey on Deep Learning Techniques for Privacy-Preserving

Tanuwidjaja, H. C., Choi, R., & Kim, K. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-30619-9_4 · Cited by 53

Group Encryption

Kiayias, A., Tsiounis, Y., & Yung, M. M. (2007) · Springer eBooks · doi:10.1007/978-3-540-76900-2_11 · Cited by 53

Privacy-aware and Resource-saving Collaborative Learning for Healthcare in Cloud Computing

Hao, M., Li, H., Xu, G., Liu, Z., & Chen, Z. (2020) · ICC 2020 - 2020 IEEE International Conference on Communications (ICC) · doi:10.1109/icc40277.2020.9148979 · Cited by 52

Boosting Privately: Privacy-Preserving Federated Extreme Boosting for Mobile Crowdsensing

Liu, Y., Ma, Z., Liu, X., Ma, S., Nepal, S., & Deng, R. (2019) · arXiv · doi:10.48550/arxiv.1907.10218 · Cited by 52

lpRide: Lightweight and Privacy-Preserving Ride Matching Over Road Networks in Online Ride Hailing Systems

Yu, H., Shu, J., Jia, X., Zhang, H., & Yu, X. (2019) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2019.2941761 · Cited by 52

A Survey on Privacy-Preserving Machine Learning with Fully Homomorphic Encryption

Pulido-Gaytan, L. B., Tchernykh, A. N., Cortés-Mendoza, J. M., Babenko, M. G., & Radchenko, G. (2021) · Communications in computer and information science · doi:10.1007/978-3-030-68035-0_9 · Cited by 52

Large Message Homomorphic Secret Sharing from DCR and Applications

Roy, L., & Singh, J. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-84252-9_23 · Cited by 52

Dubhe: Towards Data Unbiasedness with Homomorphic Encryption in Federated Learning Client Selection

Zhang, S., Li, Z., Chen, Q., Zheng, W., Leng, J., & Guo, M. (2021) · Proceedings of the International Conference on Parallel Processing · doi:10.1145/3472456.3473513 · Cited by 52

Secure Multiparty Computation from Threshold Encryption Based on Class Groups

Braun, L., Damgård, I., & Orlandi, C. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-38557-5_20 · Cited by 52

Privacy preserving data mining over vertically partitioned data

Vaidya, J. S., & Clifton, C. (2004) · Cited by 52

Multi-lateral privacy-preserving localization in pervasive environments

Shu, T., Chen, Y. J., Yang, J., & Williams, A. (2014) · IEEE Conference on Computer Communications (INFOCOM) · doi:10.1109/infocom.2014.6848176 · Cited by 52

A flexible approach to distributed data anonymization

Kohlmayer, F., Praßer, F., Eckert, C. M., & Kuhn, K. A. (2013) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2013.12.002 · Cited by 55

Group homomorphic encryption: characterizations, impossibility results, and applications

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A Framework for Practical Universally Composable Zero-Knowledge Protocols

Camenisch, J. L., Krenn, S., & Shoup, V. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-25385-0_24 · Cited by 52

VD-PSI: Verifiable Delegated Private Set Intersection on Outsourced Private Datasets

Abadi, A., Terzis, S., & Dong, C. (2017) · Lecture notes in computer science · doi:10.1007/978-3-662-54970-4_9 · Cited by 52

A privacy-preserving mobile application recommender system based on trust evaluation

Xu, K., Zhang, W., & Yan, Z. (2018) · Journal of Computational Science · doi:10.1016/j.jocs.2018.04.001 · Cited by 52

Homomorphic Encryption-Based Reversible Data Hiding for 3D Mesh Models

Shah, M., Zhang, W., Hu, H., Zhou, H., & Mahmood, T. (2018) · Arabian Journal for Science and Engineering · doi:10.1007/s13369-018-3354-4 · Cited by 52

Communication-Efficient Unconditional MPC with Guaranteed Output Delivery

Goyal, V., Liu, Y., & Song, Y. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-26951-7_4 · Cited by 53

Using Level-1 Homomorphic Encryption to Improve Threshold DSA Signatures for Bitcoin Wallet Security

Boneh, D., Gennaro, R., & Goldfeder, S. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-25283-0_19 · Cited by 52

Privacy-Preserving Association Rule Mining Using Homomorphic Encryption in a Multikey Environment

Pang, H., & Wang, B. (2020) · IEEE Systems Journal · doi:10.1109/jsyst.2020.3001316 · Cited by 52

Trust Negotiation with Hidden Credentials, Hidden Policies, and Policy Cycles

Frikken, K. B., Li, J., & Atallah, M. J. (2006) · Cited by 52

Introduction to IoT Security

Jurcut, A. D., Ranaweera, P. S., & Xu, L. (2019) · Wiley eBooks · doi:10.1002/9781119527978.ch2 · Cited by 54

End-To-End Security for Video Distribution: The Combination of Encryption, Watermarking, and Video Adaptation

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Security and privacy in the Internet of Things

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On Fully Homomorphic Encryption for Privacy-Preserving Deep Learning

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BUA: A Blockchain-based Unlinkable Authentication in VANETs

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Secure and Privacy-Preserving Federated Learning via Co-Utility

Domingo‐Ferrer, J., Blanco-Justicia, A., Manjón, J., & Sánchez, D. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3102155 · Cited by 51

The Past, Evolving Present, and Future of the Discrete Logarithm

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A privacy-preserving multidimensional data aggregation scheme with secure query processing for smart grid

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FLDID: Federated Learning Enabled Deep Intrusion Detection in Smart Manufacturing Industries

Verma, P., Breslin, J. G., & O’Shea, D. (2022) · Sensors · doi:10.3390/s22228974 · Cited by 51

A Survey on the use of Federated Learning in Privacy-Preserving Recommender Systems

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A secure and privacy-preserving communication scheme for Advanced Metering Infrastructure

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A new public key cryptosystem based on higher residues

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Efficient Public-Key Cryptosystems Provably Secure Against Active Adversaries

Paillier, P., Pointcheval, D., International, G. C., & Cryptography Department (1999)

Paillier Algorithm

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A new public-key cryptosystem as secure as factoring

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