Towards Enabling Trusted Artificial Intelligence via Blockchain

Communication-Efficient Learning of Deep Networks from Decentralized Data

McMahan, H. B., Moore, E., Ramage, D., Hampson, S., & Arcas, B. A. Y. (2016) · arXiv · doi:10.48550/arxiv.1602.05629 · Cited by 14,215 · see citing works

A Extensible Markup Language XML

Hitzler, P., Krotzsch, M., & Rudolph, S. (2009) · Chapman & Hall/CRC eBooks · doi:10.1201/9781420090512-18 · Cited by 4,836 · see citing works

The emergence of edge computing

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UML Distilled: A Brief Guide to the Standard Object Modeling Language

Fowler, M. (1997) · Cited by 1,472 · see citing works

Why and Where: A Characterization of Data Provenance

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Adversarial machine learning

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Can machine learning be secure?

Barreno, M., Nelson, B. A., Sears, R., Joseph, A. D., & Tygar, J. D. (2006) · ACM Asia Conference on Computer and Communications Security (ASIA CCS) · doi:10.1145/1128817.1128824 · Cited by 852 · see citing works

ProvChain: A Blockchain-Based Data Provenance Architecture in Cloud Environment with Enhanced Privacy and Availability

Liang, X., Shetty, S. S., Tosh, D. K., Kamhoua, C., Kwiat, K., & Njilla, L. (2017) · IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid) · doi:10.1109/ccgrid.2017.8 · Cited by 745 · see citing works

Security Evaluation of Pattern Classifiers under Attack

Biggio, B., Fumera, G., & Roli, F. (2013) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2013.57 · Cited by 412 · see citing works

Declarative networking

Loo, B. T., Condie, T., Garofalakis, M., Gay, D. E., Hellerstein, J. M., Maniatis, P., Ramakrishnan, R., Roscoe, T., & Stoica, I. G. (2006) · ACM SIGMOD International Conference on Management of Data (SIGMOD) · doi:10.1145/1142473.1142485 · Cited by 268 · see citing works

Casting out Demons: Sanitizing Training Data for Anomaly Sensors

Cretu, G. F., Stavrou, A., Locasto, M. E., Stolfo, S. J., & Keromytis, A. D. (2008) · 2008 IEEE Symposium on Security and Privacy (sp 2008) · doi:10.1109/sp.2008.11 · Cited by 226 · see citing works

Supporting fine-grained data lineage in a database visualization environment

Woodruff, A., & Stonebraker, M. R. (2002) · Proceedings - International Conference on Data Engineering · doi:10.1109/icde.1997.581742 · Cited by 199 · see citing works

Adversarial Label Flips Attack on Support Vector Machines

Xiao, H., Huang, X. X., & Claudia, E. (2012) · Frontiers in artificial intelligence and applications · doi:10.3233/978-1-61499-098-7-870 · Cited by 180 · see citing works

Mitigating Poisoning Attacks on Machine Learning Models: A Data Provenance Based Approach

Baracaldo, N., Chen, B., Ludwig, H., & Safavi, J. A. (2017) · Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security · doi:10.1145/3128572.3140450 · Cited by 108 · see citing works

SmartProvenance

Ramachandran, A., & Kantarcıoğlu, M. (2018) · ACM Conference on Data and Application Security and Privacy (CODASPY) · doi:10.1145/3176258.3176333 · Cited by 88 · see citing works

Feature Cross-Substitution in Adversarial Classification

Li, B., & Vorobeychik, Y. (2014) · Cited by 81 · see citing works

Automatically Tracking Metadata and Provenance of Machine Learning Experiments

Schelter, S., Böse, J.-H., Kirschnick, J., Klein, T., & Seufert, S. (2017) · Cited by 78 · see citing works

Poisoning attacks to compromise face templates

Biggio, B., Didaci, L., Fumera, G., & Roli, F. (2013) · International Conference on Biometrics · doi:10.1109/icb.2013.6613006 · Cited by 76 · see citing works

Towards a secure and efficient system for end-to-end provenance

McDaniel, P. D., Butler, K. R. B., McLaughlin, S., Sion, R., Zadok, E., & Winslett, M. (2010) · doi:10.5555/1855795.1855797 · Cited by 32 · see citing works

Storing, Tracking, and Querying Provenance in Linked Data

Wylot, M., Cudré-Mauroux, P., Hauswirth, M., & Groth, P. (2017) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2017.2690299 · Cited by 25 · see citing works

Data Provenance at Internet Scale: Architecture, Experiences, and the Road Ahead.

Chen, A., Wu, Y., Haeberlen, A., Loo, B. T., & Zhou, W. (2017) · Conference on Innovative Data Systems Research · Cited by 22 · see citing works

LAMP: data provenance for graph based machine learning algorithms through derivative computation

Ma, S., Aafer, Y., Xu, Z., Lee, W., Zhai, J., Liu, Y., & Zhang, X. (2017) · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · doi:10.1145/3106237.3106291 · Cited by 20 · see citing works

Federated AI for building AI Solutions across Multiple AgenciesPreprint

Verma, D. C., Julier, S., & Cirincione, G. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1809.10036 · Cited by 15 · see citing works

SimP: Secure interoperable multi-granular provenance framework

Jabal, A. A., & Bertino, E. (2016) · IEEE International Conference on eScience · doi:10.1109/escience.2016.7870908 · Cited by 13 · see citing works

Flexible Privacy and High Trust in the Next Generation Internet : The Use Case of a Cloud-based Marketplace for AI

Mehri, V. A., & Tutschku, K. (2017) · Cited by 5 · see citing works

Policy enabled caching for distributed AI

Verma, D. C., & Bent, G. A. (2017) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata.2017.8258273 · Cited by 3 · see citing works

Generation and management of training data for AI-based algorithms targeted at coalition operations

Verma, D. C., Cirincione, G., Pham, T., & Ko, B. J. (2018) · Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR · doi:10.1117/12.2305244 · Cited by 2 · see citing works

Trustworthy artificial intelligence

Thiebes, S., Lins, S., & Sunyaev, A. (2021) · Electronic Markets · doi:10.1007/s12525-020-00441-4 · Cited by 595 · see citing works

Blockchain for deep learning: review and open challenges

Shafay, M., Ahmad, R. W., Salah, K., Yaqoob, I., Jayaraman, R., & Omar, M. (2022) · Cluster Computing · doi:10.1007/s10586-022-03582-7 · Cited by 202 · see citing works

A Survey of Blockchain and Artificial Intelligence for 6G Wireless Communications

Zuo, Y., Guo, J., Gao, N., Zhu, Y., Jin, S., & Li, X. (2023) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2023.3315374 · Cited by 206 · see citing works

Blockchain technology and application: an overview

Dong, S., Abbas, K., Li, M., & Kamruzzaman, J. (2023) · PeerJ Computer Science · doi:10.7717/peerj-cs.1705 · Cited by 222 · see citing works

Towards Blockchain-Based Reputation-Aware Federated Learning

Rehman, M. H. U., Salah, K., Damiani, E., & Svetinović, D. (2020) · IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) · doi:10.1109/infocomwkshps50562.2020.9163027 · Cited by 181 · see citing works

On the Convergence of Artificial Intelligence and Distributed Ledger Technology: A Scoping Review and Future Research Agenda

Pandl, K. D., Thiebes, S., Schmidt-Kraepelin, M., & Sunyaev, A. (2020) · IEEE Access · doi:10.1109/access.2020.2981447 · Cited by 115 · see citing works

Artificial Intelligence and Blockchain for Transparency in Governance

Alshamsi, M., Salloum, S. A., Alshurideh, M. T., & Abdallah, S. (2020) · Studies in computational intelligence · doi:10.1007/978-3-030-51920-9_11 · Cited by 108 · see citing works

Provenance documentation to enable explainable and trustworthy AI: A literature review

Kale, A., Nguyen, T., Harris, F. C., Li, C., Zhang, J., & Ma, X. (2022) · Data Intelligence · doi:10.1162/dint_a_00119 · Cited by 88 · see citing works

Blockchain for Healthcare: Securing Patient Data and Enabling Trusted Artificial Intelligence.

Jennath, H. S., Anoop, V. S., & Asharaf, S. (2020) · International Journal of Interactive Multimedia and Artificial Intelligence · doi:10.9781/ijimai.2020.07.002 · Cited by 71 · see citing works

Blockchains for Artificial Intelligence of Things: A Comprehensive Survey

Shen, M., Gu, A., Kang, J., Tang, X., Lin, X., Zhu, L., & Niyato, D. (2023) · IEEE Internet of Things Journal · doi:10.1109/jiot.2023.3268705 · Cited by 54 · see citing works

Blockchain and NFTs for Trusted Ownership, Trading, and Access of AI Models

Battah, A. A., Madine, M. M., Yaqoob, I., Salah, K., Hasan, H. R., & Jayaraman, R. (2022) · IEEE Access · doi:10.1109/access.2022.3215660 · Cited by 56 · see citing works

An Overview on Blockchain for Smartphones: State-of-the-Art, Consensus, Implementation, Challenges and Future Trends

Ometov, A., Bardinova, Y., Afanasyeva, A., Mašek, P., Александрович, Ж. К., Vanurin, S., Sayfullin, M., Shubina, V., Komarov, M. M., & Bezzateev, S. V. (2020) · IEEE Access · doi:10.1109/access.2020.2998951 · Cited by 53 · see citing works

Decentralizing construction AI applications using blockchain technology

Adel, K., Elhakeem, A., & Marzouk, M. M. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2022.116548 · Cited by 59 · see citing works

A Decade of Blockchain: Review of the Current Status, Challenges, and Future Directions

Paulavičius, R., Grigaitis, S., Igumenov, A., & Filatovas, E. (2019) · Informatica · doi:10.15388/informatica.2019.227 · Cited by 52 · see citing works

The Applications of Blockchain in Artificial Intelligence

Wang, R., Luo, M., Wen, Y., Wang, L., Choo, K. R., & He, D. (2021) · Security and Communication Networks · doi:10.1155/2021/6126247 · Cited by 43 · see citing works

Adversarial learning techniques for security and privacy preservation: A comprehensive review

Hathaliya, J. J., Tanwar, S., & Sharma, P. (2022) · Security and Privacy · doi:10.1002/spy2.209 · Cited by 30 · see citing works

Blockchain and Deep Learning Integration for Various Application: A Review

Afaq, Y., & Manocha, A. (2023) · Journal of Computer Information Systems · doi:10.1080/08874417.2023.2173330 · Cited by 23 · see citing works

Survey on Blockchain-Enhanced Machine Learning

Ural, Ö., & Yoshigoe, K. (2023) · IEEE Access · doi:10.1109/access.2023.3344669 · Cited by 23 · see citing works

Distributed Ledger for Provenance Tracking of Artificial Intelligence Assets

Lüthi, P., Gagnaux, T., & Gygli, M. (2020) · IFIP advances in information and communication technology · doi:10.1007/978-3-030-42504-3_26 · Cited by 20 · see citing works

Blockchain for AI: A Disruptive Integration

Tian, R., Kong, L., Min, X., & Qu, Y. (2022) · International Conference on Computer Supported Cooperative Work in Design (CSCWD) · doi:10.1109/cscwd54268.2022.9776023 · Cited by 13 · see citing works

Zero Knowledge Proofs Towards Verifiable Decentralized AI Pipelines

Singh, N. K., Dayama, P. S., & Pandit, V. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-18283-9_12 · Cited by 13 · see citing works

Secure Linear Aggregation Using Decentralized Threshold Additive Homomorphic Encryption For Federated LearningPreprint

Tian, H., Zhang, F., Shao, Y., & Li, B. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2111.10753 · Cited by 11 · see citing works

Lattice based distributed threshold additive homomorphic encryption with application in federated learning

Tian, H., Wen, Y., Zhang, F., Shao, Y., & Li, B. (2023) · Computer Standards & Interfaces · doi:10.1016/j.csi.2023.103765 · Cited by 10 · see citing works

Blockchain-enhanced computer vision approach for remote safety inspection in construction

Kim, D., Yang, J., Lee, D., Lee, D., Rahimian, F. P., & Park, C. (2024) · Engineering Construction & Architectural Management · doi:10.1108/ecam-03-2024-0385 · Cited by 7 · see citing works

Smarter Contracts to Predict using Deep-Learning Algorithms

Badruddoja, S., Dantu, R., He, Y., Thompson, M., Salau, A., & Upadhyay, K. (2022) · International Conference on Blockchain Computing and Applications (BCCA) · doi:10.1109/bcca55292.2022.9922240 · Cited by 6 · see citing works

Blockchain Based E-Medical Data Storage for Privacy Protection

Alex, S. A., Jhanjhi, N. Z., & Ray, S. K. (2023) · Advances in intelligent systems and computing · doi:10.1007/978-981-99-3611-3_10 · Cited by 6 · see citing works

HealthGuard: Blockchain-Powered Healthcare Data Security

Alex, S. A., Chuma, E. L., Vaz, G. C., & de Oliveira, G. G. (2023) · International Conference on Intelligent Computing and Next Generation Networks (ICNGN) · doi:10.1109/icngn59831.2023.10396708 · Cited by 5 · see citing works

Recent advances and future prospects for blockchain in biomedicine

Ni, E., Tang, X., Zhou, X., Lee, D. H., Elhussein, A., Knight, E., Gürsoy, G., & Gerstein, M. (2025) · Cell Reports Methods · doi:10.1016/j.crmeth.2025.101114 · Cited by 4 · see citing works

Emergent Technologies for Supply Chain Risk and Disruption Management

Tripathi, P. K., Deshmukh, A. K., & Nath, T. (2023) · Flexible systems management · doi:10.1007/978-981-99-2629-9_4 · Cited by 5 · see citing works

A Hybrid-DLT Based Trustworthy AI Framework

Pelosi, A., Felicioli, C., Canciani, A., & Severino, F. E. (2023) · IEEE International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE) · doi:10.1109/wetice57085.2023.10477792 · Cited by 4 · see citing works

Trusted artificial intelligence: Strengthening digital protection

Avdoshin, S. M., & Pesotskaya, E. (2022) · Бизнес-информатика · doi:10.17323/2587-814x.2022.2.62.73 · Cited by 3 · see citing works

Ensuring Trustworthy Neural Network Training via Blockchain

Navarro, E., Standing, K. J., Dagher, G. G., & Andersen, T. (2023) · IEEE International Conference on Cognitive Machine Intelligence (CogMI) · doi:10.1109/cogmi58952.2023.00015 · Cited by 3 · see citing works

Advancing Research Reproducibility in Machine Learning through Blockchain Technology

Filatovas, E., Stripinis, L., Orts, F. J., & Paulavičius, R. (2024) · Informatica · doi:10.15388/24-infor553 · Cited by 3 · see citing works

" توظیف تطبیقات الذکاء الاصطناعی فی إنتاج المحتوى الإعلامی وعلاقتها بمصداقیته لدى الجمهور المصری"

الحمید, ع. م. م. ع. (2020) · مجلة البحوث الإعلامیة · doi:10.21608/jsb.2020.126573 · Cited by 5 · see citing works

Blockchain Based Trusted Distributed Machine Learning for Credit Scoring

Djolev, D., Lazarova, M. K., & Nakov, O. (2023) · International Scientific Conference on Computer Science (COMSCI) · doi:10.1109/comsci59259.2023.10315878 · Cited by 2 · see citing works

Transparent and Accountable Training Data Sharing in Decentralized Machine Learning Systems

Noh, S., & Rhee, K.-H. (2024) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2024.050949 · Cited by 2 · see citing works

Using Hyperledger Fabric Blockchain to Improve Information Assurance of IoT Devices for AI Model Development

Kendall, A., Das, A., Nagy, B., Johnson, B. J., & Ghosh, A. (2022) · Internet of things · doi:10.1007/978-3-030-93646-4_11 · Cited by 2 · see citing works

Artificial Intelligence as a Factor in State and Society Transformation: Finding Balance between Administrative Efficiency and Human-Centricity

Slavin, B. B. (2024) · Russian Journal of Philosophical Sciences · doi:10.30727/0235-1188-2024-67-3-99-122 · Cited by 2 · see citing works

Enhancing corporate governance with decentralized AI: a structuration theory perspective

Jain, G., Singh, H., & Hashimy, L. (2025) · Journal of Science and Technology Policy Management · doi:10.1108/jstpm-10-2024-0425 · Cited by 1 · see citing works

Challenges for Swarm of UAV-Based Intelligence

Ağca, M. A., Sarvari, P. A., Faye, S., & Khadraoui, D. (2021) · Transactions on computational science and computational intelligence · doi:10.1007/978-3-030-69984-0_45 · Cited by 1 · see citing works

Blockchain and Machine Learning as Deep Reinforcement

Mahdi, H. S. (2023) · Wasit Journal of Computer and Mathematics Science · doi:10.31185/wjcm.103 · Cited by 1 · see citing works

Application of Artificial Intelligence Towards Digital Government Establishment

Avdoshin, S. M., Pesotskaya, E., & Borevskiy, A. (2022) · Lecture notes in networks and systems · doi:10.1007/978-3-030-98015-3_22

Blockchain for AI: Smarter Contracts to Secure Artificial Intelligence Algorithms

Badruddoja, S. (2023) · doi:10.12794/metadc2179338

Hybrid Learning Blockchain assisted approach to Secure Software Defined Networks

Hamdi, H., Mhamdi, L., & Mahmood, M. A. (2023) · Globecom · doi:10.1109/globecom54140.2023.10437606

A novel pipeline for privacy-preserving of medical data using federated learning and blockchain

Sharma, A., Mukherjee, R., & Subalalitha, C. N. (2024) · AIP conference proceedings · doi:10.1063/5.0220674

Towards Reproducible Research in Machine Learning via Blockchain

Filatovas, E., Stripinis, L., Orts, F. J., & Paulavičius, R. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-81247-7_24

Revolutionizing Banking Integrating Non-Fungible Tokens for Secure Financial Transactions

RajanBabu, M. T. (2025) · International Journal for Research in Applied Science and Engineering Technology · doi:10.22214/ijraset.2025.70711

Artificial Intelligence and Blockchain Used for Sustainability Reporting in Supply Chain Management – A Literature Review

Fiolka, M., Jornitz, T., & Strehl, L. M. (2026) · Lecture notes in mechanical engineering · doi:10.1007/978-3-032-21154-5_23

Exploring blockchain technology as a governance layer for responsible artificial intelligence

Ahmed, W. A. H. (2026) · AI and Ethics · doi:10.1007/s43681-026-01192-2

1. Blockchain based Data Provenance for Trusted Artificial Intelligence

Soldatos, J. K., Despotopoulou, A.-M., Kefalakis, N., & Ipektsidis, C. (2021) · doi:10.1561/9781680838770.ch1 · Cited by 5 · see citing works

SAIaaS: A Blockchain-Based Solution for Secure Artificial Intelligence as-a-Service

Six, N., Perrichon-Chrétien, A., & Herbaut, N. (2021) · Lecture notes in networks and systems · doi:10.1007/978-3-030-84337-3_6 · Cited by 3 · see citing works

Enhancing Trust and Reliability in AI and ML: Assessing Blockchain's Potential to Ensure Data Integrity and Security

Siddika, A., & Zhao, L. (2023) · IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) · doi:10.1109/dasc/picom/cbdcom/cy59711.2023.10361446 · Cited by 4 · see citing works

Verifiable Machine Learning Models in Industrial IoT via Blockchain

Stodt, J., Ghajar, F. G., Reich, C., & Clarke, N. (2023) · Communications in computer and information science · doi:10.1007/978-3-031-35644-5_6 · Cited by 5 · see citing works

Blockchain-based Low-cost and Lightweight Storage and Provenance for Training Data

Lu, Y., Wu, Q., Wang, Y., Yao, W., & Lu, H. (2026) · Mechanisms and machine science · doi:10.1007/978-3-032-11169-2_63