{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T17:35:09Z","timestamp":1772300109367,"version":"3.50.1"},"reference-count":45,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2021,6,10]],"date-time":"2021-06-10T00:00:00Z","timestamp":1623283200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61702318"],"award-info":[{"award-number":["61702318"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"2020 Li Ka Shing Foundation Cross-Disciplinary Research Grant","award":["2020LKSFG08D"],"award-info":[{"award-number":["2020LKSFG08D"]}]},{"name":"Shantou  University Scientific Research Start-up Fund Project","award":["NTF18024"],"award-info":[{"award-number":["NTF18024"]}]},{"name":"2019 Guangdong province  special fund for science and technology (\u201cmajor special projects + task list\u201d) project","award":["2019ST043"],"award-info":[{"award-number":["2019ST043"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Blockchain is an innovative distributed ledger technology that is widely used to build next-generation applications without the support of a trusted third party. With the ceaseless evolution of the service-oriented computing (SOC) paradigm, Blockchain-as-a-Service (BaaS) has emerged, which facilitates development of blockchain-based applications. To develop a high-quality blockchain-based system, users must select highly reliable blockchain services (peers) that offer excellent quality-of-service (QoS). Since the vast number of blockchain services leading to sparse QoS data, selecting the optimal personalized services is challenging. Hence, we improve neural collaborative filtering and propose a QoS-based blockchain service reliability prediction algorithm under BaaS, named modified neural collaborative filtering (MNCF). In this model, we combine a neural network with matrix factorization to perform collaborative filtering for the latent feature vectors of users. Furthermore, multi-task learning for sharing different parameters is introduced to improve the performance of the model. Experiments based on a large-scale real-world dataset validate its superior performance compared to baselines.<\/jats:p>","DOI":"10.3390\/info12060242","type":"journal-article","created":{"date-parts":[[2021,6,10]],"date-time":"2021-06-10T03:48:08Z","timestamp":1623296888000},"page":"242","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["MNCF: Prediction Method for Reliable Blockchain Services under a BaaS Environment"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2826-9282","authenticated-orcid":false,"given":"Jianlong","family":"Xu","sequence":"first","affiliation":[{"name":"Colleage of Engineering, Shantou University, Shantou 515041, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zicong","family":"Zhuang","sequence":"additional","affiliation":[{"name":"Colleage of Engineering, Shantou University, Shantou 515041, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiyu","family":"Xia","sequence":"additional","affiliation":[{"name":"Colleage of Engineering, Shantou University, Shantou 515041, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuhui","family":"Li","sequence":"additional","affiliation":[{"name":"Colleage of Engineering, Shantou University, Shantou 515041, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Zheng, P., Zheng, Z., Luo, X., Chen, X., and Liu, X. (June, January 30). A Detailed and Real-Time Performance Monitoring Framework for Blockchain Systems. Proceedings of the 2018 IEEE\/ACM 40th International Conference on Software Engineering: Software Engineering in Practice Track (ICSE-SEIP), Gothenburg, Sweden.","DOI":"10.1145\/3183519.3183546"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1594","DOI":"10.1109\/JIOT.2018.2847705","article-title":"Smart Contract-Based Access Control for the Internet of Things","volume":"6","author":"Zhang","year":"2019","journal-title":"IEEE Internet Things J."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2266","DOI":"10.1109\/TSMC.2019.2895123","article-title":"Blockchain-Enabled Smart Contracts: Architecture, Applications, and Future Trends","volume":"49","author":"Wang","year":"2019","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1273","DOI":"10.1109\/JIOT.2019.2954128","article-title":"Tornado: Enabling Blockchain in Heterogeneous Internet of Things Through a Space-Structured Approach","volume":"7","author":"Liu","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"6392","DOI":"10.1109\/JIOT.2020.2974281","article-title":"Deep Reinforcement Learning for Resource Protection and Real-Time Detection in IoT Environment","volume":"7","author":"Liang","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1002\/jcaf.22433","article-title":"Blockchain security risk assessment and the auditor","volume":"31","author":"White","year":"2020","journal-title":"J. Corp. Account. Financ."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"6543","DOI":"10.1109\/TII.2020.2966069","article-title":"Secure Data Storage and Recovery in Industrial Blockchain Network Environments","volume":"16","author":"Liang","year":"2020","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"564","DOI":"10.1016\/j.future.2019.05.051","article-title":"uBaaS: A unified blockchain as a service platform","volume":"101","author":"Lu","year":"2019","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_9","unstructured":"Liu, J., and Chen, Y. (2019). HAP: A Hybrid QoS Prediction Approach in Cloud Manufacturing combining Local Collaborative Filtering and Global Case-based Reasoning. IEEE Trans. Serv. Comput."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1016\/j.comcom.2020.04.018","article-title":"Multi-dimensional quality-driven service recommendation with privacy-preservation in mobile edge environment","volume":"157","author":"Zhong","year":"2020","journal-title":"Comput. Commun."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Yakubu, I.Z., and Malathy, C. (2020, January 24\u201325). Priority Based Delay Time Scheduling for Quality of Service in Cloud Computing Networks. Proceedings of the 2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE), Vellore, India.","DOI":"10.1109\/ic-ETITE47903.2020.379"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1016\/j.jss.2017.09.011","article-title":"Time series forecasting for dynamic quality of web services: An empirical study","volume":"134","author":"Syu","year":"2017","journal-title":"J. Syst. Softw."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"55721","DOI":"10.1109\/ACCESS.2019.2912505","article-title":"Personalized QoS Prediction for Service Recommendation With a Service-Oriented Tensor Model","volume":"7","author":"Guo","year":"2019","journal-title":"IEEE Access"},{"key":"ref_14","unstructured":"Yang, Y., Zheng, Z., Niu, X., Tang, M., Lu, Y., and Liao, X. (2018). A Location-Based Factorization Machine Model for Web Service QoS Prediction. IEEE Trans. Serv. Comput."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Meiappane, A., Prabavadhi, J., Dharani, R., Kaviya, R., and Malathy, R. (2020, January 3\u20134). Web Service Recommendation and QoS Prediction via Matrix Factorization. Proceedings of the 2020 International Conference on System, Computation, Automation and Networking (ICSCAN), Pondicherry, India.","DOI":"10.1109\/ICSCAN49426.2020.9262307"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Manju, K., David Peter, S., and Idicula, S.M. (2021). A Framework for Generating Extractive Summary from Multiple Malayalam Documents. Information, 12.","DOI":"10.3390\/info12010041"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Semenkov, A., Bragin, D., Usoltsev, Y., Konev, A., and Kostuchenko, E. (2021). Generation of an EDS Key Based on a Graphic Image of a Subject\u2019s Face Using the RC4 Algorithm. Information, 12.","DOI":"10.3390\/info12010019"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"456","DOI":"10.1109\/TCSS.2019.2906181","article-title":"N2VSCDNNR: A Local Recommender System Based on Node2vec and Rich Information Network","volume":"6","author":"Chen","year":"2019","journal-title":"IEEE Trans. Comput. Soc. Syst."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"43752","DOI":"10.1109\/ACCESS.2020.2978452","article-title":"Enhanced QoS-Based Model for Trust Assessment in Cloud Computing Environment","volume":"8","author":"Hassan","year":"2020","journal-title":"IEEE Access"},{"key":"ref_20","unstructured":"Ling, G., King, I., and Lyu, M.R. (2013, January 3\u20139). A Unified Framework for Reputation Estimation in Online Rating Systems. Proceedings of the IJCAI \u201913, 23th International Joint Conference on Artificial Intelligence, Beijing, China."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"916","DOI":"10.1007\/s10922-015-9357-5","article-title":"Cloud Service Recommendation Based on a Correlated QoS Ranking Prediction","volume":"24","author":"Jayapriya","year":"2016","journal-title":"J. Netw. Syst. Manag."},{"key":"ref_22","unstructured":"Mei, H., Xie, B., Zhao, J., Shao, L., Wei, Y., and Zhang, J. (2007, January 9\u201313). Personalized QoS Prediction forWeb Services via Collaborative Filtering. Proceedings of the 2007 IEEE International Conference on Web Services, Salt Lake City, UT, USA."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1109\/MIC.2003.1167344","article-title":"Amazon.Com Recommendations: Item-to-Item Collaborative Filtering","volume":"7","author":"Linden","year":"2003","journal-title":"IEEE Internet Comput."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Zheng, Z., Ma, H., Lyu, M.R., and King, I. (2009, January 6\u201310). WSRec: A Collaborative Filtering Based Web Service Recommender System. Proceedings of the ICWS \u201909, 2009 IEEE International Conference on Web Services, Los Angeles, CA, USA.","DOI":"10.1109\/ICWS.2009.30"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/j.future.2020.03.062","article-title":"An accurate and efficient web service QoS prediction model with wide-range awareness","volume":"109","author":"Chen","year":"2020","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_26","first-page":"1257","article-title":"Probabilistic Matrix Factorization","volume":"20","author":"Mnih","year":"2007","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Lo, W., Yin, J., Deng, S., Li, Y., and Wu, Z. (2012, January 24\u201329). An Extended Matrix Factorization Approach for QoS Prediction in Service Selection. Proceedings of the SCC \u201912. 2012 IEEE Ninth International Conference on Services Computing, Honolulu, HI, USA.","DOI":"10.1109\/SCC.2012.36"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Zhang, R., Li, C., Sun, H., Wang, Y., and Huai, J. (July, January 27). Quality of Web Service Prediction by Collective Matrix Factorization. Proceedings of the 2014 IEEE International Conference on Services Computing (SCC), Anchorage, AK, USA.","DOI":"10.1109\/SCC.2014.64"},{"key":"ref_29","unstructured":"Tang, M., Jiang, Y., Liu, J., and Liu, X.F. (2012, January 24\u201329). Location-Aware Collaborative Filtering for QoS-Based Service Recommendation. Proceedings of the 2012, ICWS \u201912, 2012 IEEE 19th International Conference on Web Services, Honolulu, HI, USA."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"He, P., Zhu, J., Zheng, Z., Xu, J., and Lyu, M.R. (July, January 27). Location-Based Hierarchical Matrix Factorization for Web Service Recommendation. Proceedings of the ICWS \u201914, 2014 IEEE International Conference on Web Services, Anchorage, AK, USA.","DOI":"10.1109\/ICWS.2014.51"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Yu, D., Liu, Y., Xu, Y., and Yin, Y. (July, January 27). Personalized QoS Prediction for Web Services Using Latent Factor Models. Proceedings of the SCC \u201914, 2014 IEEE International Conference on Services Computing, Anchorage, AK, USA.","DOI":"10.1109\/SCC.2014.23"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Wu, Y., DuBois, C., Zheng, A.X., and Ester, M. (2016, January 22\u201325). Collaborative Denoising Auto-Encoders for Top-N Recommender Systems. Proceedings of the WSDM \u201916, Ninth ACM International Conference on Web Search and Data Mining, San Francisco, CA, USA.","DOI":"10.1145\/2835776.2835837"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"He, X., Liao, L., Zhang, H., Nie, L., Hu, X., and Chua, T.S. (2017, January 3\u20137). Neural Collaborative Filtering. Proceedings of the WWW \u201917, 26th International Conference on World Wide Web, Perth, Australia.","DOI":"10.1145\/3038912.3052569"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Liang, W., Zhang, D., Lei, X., Tang, M., Li, K.C., and Zomaya, A. (2020). Circuit Copyright Blockchain: Blockchain-based Homomorphic Encryption for IP Circuit Protection. IEEE Trans. Emerg. Top. Comput.","DOI":"10.1109\/TETC.2020.2993032"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Lei, K., Zhang, Q., Xu, L., and Qi, Z. (2018, January 11\u201313). Reputation-Based Byzantine Fault-Tolerance for Consortium Blockchain. Proceedings of the 2018 IEEE 24th International Conference on Parallel and Distributed Systems (ICPADS), Singapore.","DOI":"10.1109\/PADSW.2018.8644933"},{"key":"ref_36","unstructured":"Zheng, P., Zheng, Z., and Chen, L. (2019). Selecting Reliable Blockchain Peers via Hybrid Blockchain Reliability Prediction. arXiv."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"134422","DOI":"10.1109\/ACCESS.2019.2941905","article-title":"NutBaaS: A Blockchain-as-a-Service Platform","volume":"7","author":"Zheng","year":"2019","journal-title":"IEEE Access"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1145\/3065386","article-title":"ImageNet Classification with Deep Convolutional Neural Networks","volume":"60","author":"Krizhevsky","year":"2017","journal-title":"Commun. ACM"},{"key":"ref_39","unstructured":"Glorot, X., Bordes, A., and Bengio, Y. (2011, January 11\u201313). Deep Sparse Rectifier Neural Networks. Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, Lauderdale, FL, USA."},{"key":"ref_40","unstructured":"Ioffe, S., and Szegedy, C. (2015). Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift. arXiv."},{"key":"ref_41","unstructured":"Kingma, D.P., and Ba, J. (2014). Adam: A Method for Stochastic Optimization. arXiv."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., and Riedl, J. (1994, January 22\u201326). GroupLens: An Open Architecture for Collaborative Filtering of Netnews. Proceedings of the CSCW \u201994, 1994 ACM Conference on Computer Supported Cooperative Work, Chapel Hill, NC, USA.","DOI":"10.1145\/192844.192905"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Sarwar, B., Karypis, G., Konstan, J., and Riedl, J. (2001, January 1\u20135). Item-Based Collaborative Filtering Recommendation Algorithms. Proceedings of the WWW \u201901, 10th International Conference on World Wide Web, Hong Kong.","DOI":"10.1145\/371920.372071"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Zheng, Z., and Lyu, M.R. (2010, January 1\u20138). Collaborative Reliability Prediction of Service-Oriented Systems. Proceedings of the ICSE \u201910, 32nd ACM\/IEEE International Conference on Software Engineering, Cape Town, South Africa.","DOI":"10.1145\/1806799.1806809"},{"key":"ref_45","unstructured":"Wu, H., Zhang, Z., Luo, J., Yue, K., and Hsu, C. (2018). Multiple Attributes QoS Prediction via Deep Neural Model with Contexts. IEEE Trans. Serv. Comput."}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/12\/6\/242\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:12:44Z","timestamp":1760163164000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/12\/6\/242"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,10]]},"references-count":45,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2021,6]]}},"alternative-id":["info12060242"],"URL":"https:\/\/doi.org\/10.3390\/info12060242","relation":{},"ISSN":["2078-2489"],"issn-type":[{"value":"2078-2489","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,6,10]]}}}