{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T22:11:17Z","timestamp":1768515077917,"version":"3.49.0"},"reference-count":29,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2023,2,27]],"date-time":"2023-02-27T00:00:00Z","timestamp":1677456000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Basic Research Program of Qinghai Province","award":["2020-ZJ-701"],"award-info":[{"award-number":["2020-ZJ-701"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Due to the rapid development of machine-learning technology, companies can build complex models to provide prediction or classification services for customers without resources. A large number of related solutions exist to protect the privacy of models and user data. However, these efforts require costly communication and are not resistant to quantum attacks. To solve this problem, we designed a new secure integer-comparison protocol based on fully homomorphic encryption and proposed a client-server classification protocol for decision-tree evaluation based on the secure integer-comparison protocol. Compared to existing work, our classification protocol has a relatively low communication cost and requires only one round of communication with the user to complete the classification task. Moreover, the protocol was built on a fully homomorphic-scheme-based lattice that is resistant to quantum attacks, as opposed to conventional schemes. Finally, we conducted an experimental analysis comparing our protocol with the traditional approach on three datasets. The experimental results showed that the communication cost of our scheme was 20% of the cost of the traditional scheme.<\/jats:p>","DOI":"10.3390\/s23052624","type":"journal-article","created":{"date-parts":[[2023,2,28]],"date-time":"2023-02-28T02:01:51Z","timestamp":1677549711000},"page":"2624","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Privacy-Preserving Decision-Tree Evaluation with Low Complexity for Communication"],"prefix":"10.3390","volume":"23","author":[{"given":"Yidi","family":"Hao","sequence":"first","affiliation":[{"name":"School of Cyberspace Security, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7617-5462","authenticated-orcid":false,"given":"Baodong","family":"Qin","sequence":"additional","affiliation":[{"name":"School of Cyberspace Security, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yitian","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Cyberspace Security, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,27]]},"reference":[{"key":"ref_1","unstructured":"Witten, I.H., Frank, E., and Hall, M.A. (2011). Data Mining: Practical Machine Learning Tools and Techniques, Morgan Kaufmann. [3rd ed.]."},{"key":"ref_2","unstructured":"Berry, M.W., Dayal, U., Kamath, C., and Skillicorn, D.B. (2004, January 22\u201324). Privacy-Preserving Multivariate Statistical Analysis: Linear Regression and Classification. Proceedings of the Proceedings of the Fourth SIAM International Conference on Data Mining, Lake Buena Vista, FL, USA."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"37343","DOI":"10.1186\/1687-417X-2007-037343","article-title":"Oblivious Neural Network Computing via Homomorphic Encryption","volume":"2007","author":"Orlandi","year":"2007","journal-title":"EURASIP J. Inf. Secur."},{"key":"ref_4","unstructured":"A, S.M., and K, V. (2013, January 11\u201312). A novel privacy preserving decision tree induction. Proceedings of the 2013 IEEE Conference on Information & Communication Technologies, Thuckalay, India."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1351","DOI":"10.1109\/TC.2015.2470255","article-title":"Privacy Preserving Deep Computation Model on Cloud for Big Data Feature Learning","volume":"65","author":"Zhang","year":"2016","journal-title":"IEEE Trans. Comput."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1109\/TDSC.2013.43","article-title":"A Random Decision Tree Framework for Privacy-Preserving Data Mining","volume":"11","author":"Vaidya","year":"2014","journal-title":"IEEE Trans. Dependable Secur. Comput."},{"key":"ref_7","first-page":"243","article-title":"Private yet Efficient Decision Tree Evaluation","volume":"Volume 10980","author":"Kerschbaum","year":"2018","journal-title":"Proceedings of the Data and Applications Security and Privacy XXXII\u201432nd Annual IFIP WG 11.3 Conference, DBSec 2018"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.jpdc.2019.10.009","article-title":"Edge-based differential privacy computing for sensor-cloud systems","volume":"136","author":"Wang","year":"2020","journal-title":"J. Parallel Distrib. Comput."},{"key":"ref_9","unstructured":"Mitzenmacher, M. (June, January 31). Fully homomorphic encryption using ideal lattices. Proceedings of the Proceedings of the 41st Annual ACM Symposium on Theory of Computing, STOC 2009, Bethesda, MD, USA."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Yao, A.C. (1982, January 3\u20135). Protocols for Secure Computations (Extended Abstract). Proceedings of the 23rd Annual Symposium on Foundations of Computer Science, Chicago, IL, USA.","DOI":"10.1109\/SFCS.1982.38"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1007\/978-3-319-66399-9_27","article-title":"Privacy-Preserving Decision Trees Evaluation via Linear Functions","volume":"Volume 10493","author":"Foley","year":"2017","journal-title":"Proceedings of the Computer Security\u2014ESORICS 2017\u201422nd European Symposium on Research in Computer Security"},{"key":"ref_12","unstructured":"Fan, J., and Vercauteren, F. (2012). Somewhat Practical Fully Homomorphic Encryption. IACR Cryptol. ePrint Arch., 144."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1007\/978-3-540-71677-8_22","article-title":"Practical and Secure Solutions for Integer Comparison","volume":"Volume 4450","author":"Okamoto","year":"2007","journal-title":"Proceedings of the Public Key Cryptography\u2014PKC 2007, tenth International Conference on Practice and Theory in Public-Key Cryptography"},{"key":"ref_14","unstructured":"Ning, P., di Vimercati, S.D.C., and Syverson, P.F. (2007, January 28\u201331). Privacy-preserving remote diagnostics. Proceedings of the 2007 ACM Conference on Computer and Communications Security, CCS 2007, Alexandria, VA, USA."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Bost, R., Popa, R.A., Tu, S., and Goldwasser, S. (2014). Machine Learning Classification over Encrypted Data. IACR Cryptol. ePrint Arch., 331.","DOI":"10.14722\/ndss.2015.23241"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1515\/popets-2016-0043","article-title":"Privately Evaluating Decision Trees and Random Forests","volume":"2016","author":"Wu","year":"2016","journal-title":"Proc. Priv. Enhancing Technol."},{"key":"ref_17","unstructured":"Rabin, M.O. (2005). How To Exchange Secrets with Oblivious Transfer. IACR Cryptol. ePrint Arch., 187."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1504\/IJACT.2009.028031","article-title":"A correction to \u2018efficient and secure comparison for on-line auctions\u2019","volume":"1","author":"Geisler","year":"2009","journal-title":"Int. J. Appl. Cryptogr."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1109\/TIT.1985.1057074","article-title":"A public key cryptosystem and a signature scheme based on discrete logarithms","volume":"31","author":"Gamal","year":"1985","journal-title":"IEEE Trans. Inf. Theory"},{"key":"ref_20","unstructured":"Kim, J., Ahn, G., Kim, S., Kim, Y., L\u00f3pez, J., and Kim, T. (2018, January 4\u20138). Non-interactive and Output Expressive Private Comparison from Homomorphic Encryption. Proceedings of the 2018 on Asia Conference on Computer and Communications Security, AsiaCCS 2018, Incheon, Republic of Korea."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2633600","article-title":"(Leveled) Fully Homomorphic Encryption without Bootstrapping","volume":"6","author":"Brakerski","year":"2014","journal-title":"ACM Trans. Comput. Theory"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"266","DOI":"10.2478\/popets-2019-0015","article-title":"Private Evaluation of Decision Trees using Sublinear Cost","volume":"2019","author":"Tueno","year":"2019","journal-title":"Proc. Priv. Enhancing Technol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"187","DOI":"10.2478\/popets-2019-0026","article-title":"SoK: Modular and Efficient Private Decision Tree Evaluation","volume":"2019","author":"Kiss","year":"2019","journal-title":"Proc. Priv. Enhancing Technol."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Ma, J.P.K., Tai, R.K.H., Zhao, Y., and Chow, S.S.M. (2021, January 21\u201325). Let us Stride Blindfolded in a Forest: Sublinear Multi-Client Decision Trees Evaluation. Proceedings of the 28th Annual Network and Distributed System Security Symposium, NDSS 2021, Virtual.","DOI":"10.14722\/ndss.2021.23166"},{"key":"ref_25","unstructured":"Suga, Y., Sakurai, K., Ding, X., and Sako, K. (June, January 30). Scalable Private Decision Tree Evaluation with Sublinear Communication. Proceedings of the ASIA CCS \u201922: ACM Asia Conference on Computer and Communications Security, Nagasaki, Japan."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Veugen, T. (2022). Lightweight Secure Integer Comparison. Mathematics, 10.","DOI":"10.3390\/math10030305"},{"key":"ref_27","unstructured":"Gabow, H.N., and Fagin, R. (2005, January 22\u201324). On lattices, learning with errors, random linear codes, and cryptography. Proceedings of the 37th Annual ACM Symposium on Theory of Computing, Baltimore, MD, USA."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"424","DOI":"10.1007\/978-3-642-04444-1_26","article-title":"Secure Evaluation of Private Linear Branching Programs with Medical Applications","volume":"Volume 5789","author":"Backes","year":"2009","journal-title":"Proceedings of the Computer Security\u2014ESORICS 2009, 14th European Symposium on Research in Computer Security"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1109\/TDSC.2017.2679189","article-title":"Efficient and Private Scoring of Decision Trees, Support Vector Machines and Logistic Regression Models Based on Pre-Computation","volume":"16","author":"Cock","year":"2019","journal-title":"IEEE Trans. Dependable Secur. Comput."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/5\/2624\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:43:58Z","timestamp":1760121838000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/5\/2624"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,27]]},"references-count":29,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2023,3]]}},"alternative-id":["s23052624"],"URL":"https:\/\/doi.org\/10.3390\/s23052624","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,2,27]]}}}