{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T13:37:07Z","timestamp":1767706627893,"version":"3.37.3"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,12,2]],"date-time":"2021-12-02T00:00:00Z","timestamp":1638403200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,12,2]],"date-time":"2021-12-02T00:00:00Z","timestamp":1638403200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62172331"],"award-info":[{"award-number":["62172331"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62102310"],"award-info":[{"award-number":["62102310"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Youth Innovation Team Construction of Shaanxi Provincial Department of Education","award":["21JP081"],"award-info":[{"award-number":["21JP081"]}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2020M683689XB"],"award-info":[{"award-number":["2020M683689XB"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Founds of Shaanxi","award":["2020JQ-646"],"award-info":[{"award-number":["2020JQ-646"]}]},{"name":"Natural Science Founds of Shaanxi","award":["2021JQ-486"],"award-info":[{"award-number":["2021JQ-486"]}]},{"name":"the Youth Innovation Team of Shaanxi Universities","award":["2019-38"],"award-info":[{"award-number":["2019-38"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Intell Inf Syst"],"published-print":{"date-parts":[[2022,8]]},"DOI":"10.1007\/s10844-021-00689-y","type":"journal-article","created":{"date-parts":[[2021,12,2]],"date-time":"2021-12-02T10:06:51Z","timestamp":1638439611000},"page":"93-119","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Rating behavior evaluation and abnormality forensics analysis for injection attack detection"],"prefix":"10.1007","volume":"59","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1590-2587","authenticated-orcid":false,"given":"Zhihai","family":"Yang","sequence":"first","affiliation":[]},{"given":"Qindong","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Zhaoli","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Jinpei","family":"Yan","sequence":"additional","affiliation":[]},{"given":"Yaling","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,12,2]]},"reference":[{"key":"689_CR1","doi-asserted-by":"crossref","unstructured":"Burke, R., Mobasher, B., & Williams, C. (2006). Classification features for attack detection in collaborative recommender systems. In International conference on knowledge discovery and data mining (pp. 17\u201320).","DOI":"10.1145\/1150402.1150465"},{"issue":"1","key":"689_CR2","doi-asserted-by":"publisher","first-page":"314","DOI":"10.1016\/j.dss.2013.01.020","volume":"55","author":"C Chung","year":"2013","unstructured":"Chung, C., Hsu, P., & Huang, S. (2013). BP: A novel approach to filter out malicious rating profiles from recommender systems. Journal of Decision Support Systems, 55(1), 314\u2013325.","journal-title":"Journal of Decision Support Systems"},{"key":"689_CR3","doi-asserted-by":"crossref","unstructured":"Fang, M., Yang, G., Gong, N., & Liu, J. (2018). Poisoning attacks to graph-based recommender systems. In Proceedings of the 34th annual computer security applications conference (ACSAC) (pp. 381\u2013392).","DOI":"10.1145\/3274694.3274706"},{"issue":"4","key":"689_CR4","first-page":"1","volume":"42","author":"I Gunes","year":"2012","unstructured":"Gunes, I., Kaleli, C., Bilge, A., & Polat, H. (2012). Shilling attacks against recommender systems: A comprehensive survey. Artificial Intelligence Review, 42(4), 1\u201333.","journal-title":"Artificial Intelligence Review"},{"key":"689_CR5","doi-asserted-by":"crossref","unstructured":"Jiang, M., Cui, P., Beutel, A., Faloutsos, C., & Yang, S. (2014). Catchsync: catching synchronized behavior in large directed graphs. In Proceedings of the 20th ACM SIGKDD international conference on knowledge discovery and data mining (pp. 941\u2013950).","DOI":"10.1145\/2623330.2623632"},{"key":"689_CR6","doi-asserted-by":"crossref","unstructured":"Luo, X., Zhou, M., Li, S., & Shang, M. (2017). An inherently non-negative latent factor model for high-dimensional and sparse matrices from industrial applications. IEEE Transactions on Industrial Informatics.","DOI":"10.1109\/TII.2017.2766528"},{"key":"689_CR7","doi-asserted-by":"crossref","unstructured":"McAuley, J., & Leskovec, J. (2013). Hidden factors and hidden topics: understanding rating dimensions with review text. In ACM Conference on recommender systems (RecSys) (pp. 165\u2013172).","DOI":"10.1145\/2507157.2507163"},{"key":"689_CR8","doi-asserted-by":"crossref","unstructured":"McAuley, J., Pandey, R., & Leskovec, J. (2015). Inferring networks of substitutable and complementary products. Knowledge Discovery and Data Mining.","DOI":"10.1145\/2783258.2783381"},{"key":"689_CR9","doi-asserted-by":"crossref","unstructured":"Mehta, B., Hofmann, T., & Fankhauser, P. (2007). Lies and propaganda: detecting spam users in collaborative filtering. In Proceedings of the 12th international conference on intelligent user interfaces (pp. 14\u201321).","DOI":"10.1145\/1216295.1216307"},{"issue":"4","key":"689_CR10","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1145\/1278366.1278372","volume":"7","author":"B Mobasher","year":"2007","unstructured":"Mobasher, B., Burke, R., Bhaumik, R., & Williams, C. (2007). Toward trustworthy recommender systems: An analysis of attack models and algorithm robustness. ACM Transactions on Internet Technology, 7(4), 38.","journal-title":"ACM Transactions on Internet Technology"},{"key":"689_CR11","doi-asserted-by":"crossref","unstructured":"Seminario, C.E., & Wilson, D.C. (2014). Attacking item-based recommender systems with power items. In ACM Conference on recommender systems (pp. 57\u201364).","DOI":"10.1145\/2645710.2645722"},{"key":"689_CR12","doi-asserted-by":"crossref","unstructured":"Song, J., Li, Z., Hu, Z., Wu, Y., Li, Z., Li, J., & Gao, J. (2020). PoisonRec: An adaptive data poisoning framework for attacking black-box recommender systems. In The 36th IEEE international conference on data engineering (ICDE\u201920) (pp. 157\u2013168).","DOI":"10.1109\/ICDE48307.2020.00021"},{"issue":"5","key":"689_CR13","doi-asserted-by":"publisher","first-page":"855","DOI":"10.1109\/TKDE.2019.2893638","volume":"32","author":"J Tang","year":"2019","unstructured":"Tang, J., Du, X., He, X., Yuan, F., Tian, Q., & Chua, T. (2019). Adversarial training towards robust multimedia recommender system. IEEE Transactions on Knowledge and Data Engineering, 32(5), 855\u2013867.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"689_CR14","doi-asserted-by":"crossref","unstructured":"Ting, K. M., Zhu, Y., Carman, M., Zhu, Y., & Zhou, Z. H. (2016). Overcoming key weaknesses of distance-based neighbourhood methods using a data dependent dissimilarity measure. In Proceedings of the 22nd ACM SIGKDD conference on knowledge discovery and data mining (KDD\u201916) (pp. 1205\u20131214).","DOI":"10.1145\/2939672.2939779"},{"key":"689_CR15","doi-asserted-by":"crossref","unstructured":"Wang, Y., Zhang, L., Tao, H., Wu, Z., & Cao, J. (2015). A comparative study of shilling attack detectors for recommender systems. In The 12th international conference on service systems and service management (ICSSSM) (pp. 1\u20136).","DOI":"10.1109\/ICSSSM.2015.7170330"},{"key":"689_CR16","unstructured":"Wilson, D.C., & Seminario, C.E. (2015). Mitigating power user attacks on a user-based collaborative recommender system. In Association for the advancement of artificial intelligence (pp. 513\u2013318)."},{"issue":"7","key":"689_CR17","first-page":"551","volume":"59","author":"Z Wu","year":"2014","unstructured":"Wu, Z., Wang, Y., & Cao, J. (2014). A survey on shilling attack models and detection techniques for recommender systems. Science China, 59(7), 551\u2013560.","journal-title":"Science China"},{"key":"689_CR18","unstructured":"Xing, X., Meng, W., Doozan, D., Snoeren, A., Feamster, N., & Lee, W. (2013). Take this personally: pollution attacks on personalized services. USENIX Security, 671\u2013686."},{"issue":"15","key":"689_CR19","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1016\/j.knosys.2019.04.012","volume":"178","author":"Y Xu","year":"2019","unstructured":"Xu, Y., & Zhang, F. (2019). Detecting shilling attacks in social recommender systems based on time series analysis and trust features. Knowledge-Based Systems, 178(15), 25\u201347.","journal-title":"Knowledge-Based Systems"},{"key":"689_CR20","doi-asserted-by":"crossref","unstructured":"Yang, G., Gong, N., & Cai, Y. (2017). Fake co-visitation injection attacks to recommender systems. Network and Distributed System Security Symposium (NDSS), 1\u201315.","DOI":"10.14722\/ndss.2017.23020"},{"key":"689_CR21","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1016\/j.knosys.2016.08.011","volume":"111","author":"Z Yang","year":"2016","unstructured":"Yang, Z., Cai, Z., & Guan, X. (2016). Estimating user behavior toward detecting anomalous ratings in rating systems. Knowledge-Based Systems, 111, 144\u2013158.","journal-title":"Knowledge-Based Systems"},{"key":"689_CR22","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1016\/j.neucom.2017.02.052","volume":"240","author":"Z Yang","year":"2017","unstructured":"Yang, Z., Cai, Z., & Yang, Y (2017). Spotting anomalous ratings for rating systems by analyzing target users and items. Neurocomputing, 240, 25\u201346.","journal-title":"Neurocomputing"},{"key":"689_CR23","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1016\/j.neucom.2018.05.001","volume":"308","author":"Z Yang","year":"2018","unstructured":"Yang, Z., Sun, Q., Zhang, Y., & Zhang, B. (2018). Uncovering anomalous rating behaviors for rating systems. Neurocomputing, 308, 205\u2013226.","journal-title":"Neurocomputing"},{"key":"689_CR24","doi-asserted-by":"publisher","first-page":"2766","DOI":"10.1109\/TIFS.2020.2977023","volume":"15","author":"Z Yang","year":"2020","unstructured":"Yang, Z., Sun, Q., Zhang, Y., Zhu, L., & Ji, W. (2020). Inference of suspicious co-visitation and co-rating behaviors and abnormality forensics for recommender systems. IEEE Transactions on Information Forensics and Security, 15, 2766\u20132781.","journal-title":"IEEE Transactions on Information Forensics and Security"},{"key":"689_CR25","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1016\/j.knosys.2016.02.008","volume":"100","author":"Z Yang","year":"2016","unstructured":"Yang, Z., Xu, L., Cai, Z., & Xu, Z. (2016). Re-scale AdaBoost for attack detection in collaborative filtering recommender systems. Knowledge-Based Systems, 100, 74\u201388.","journal-title":"Knowledge-Based Systems"},{"issue":"8","key":"689_CR26","doi-asserted-by":"publisher","first-page":"105984","DOI":"10.1016\/j.knosys.2020.105984","volume":"199","author":"F Zhang","year":"2020","unstructured":"Zhang, F., Qu, Y., Xu, Y., & Wang, S. (2020). Graph embedding-based approach for detecting group shilling attacks in collaborative recommender systems. Knowledge-Based Systems, 199(8), 105984.","journal-title":"Knowledge-Based Systems"},{"issue":"5","key":"689_CR27","doi-asserted-by":"publisher","first-page":"1189","DOI":"10.1109\/TCSS.2020.3013878","volume":"7","author":"F Zhang","year":"2020","unstructured":"Zhang, F., & Wang, S. (2020). Detecting group shilling attacks in online recommender systems based on bisecting k-means clustering. IEEE Transactions on Computational Social Systems, 7(5), 1189\u20131199.","journal-title":"IEEE Transactions on Computational Social Systems"},{"key":"689_CR28","doi-asserted-by":"crossref","unstructured":"Zhang, H., Li, Y., Ding, B., & Gao, J. (2020). Practical data poisoning attack against next-item recommendation. In Proceedings of the web conference (WWW\u201919) (pp. 2458\u20132464).","DOI":"10.1145\/3366423.3379992"},{"key":"689_CR29","unstructured":"Zhang, Y., Tan, Y., Zhang, M., Liu, Y., Chua, T., & Ma, S. (2015). Catch the black sheep Unified framework for shilling attack detection based on fraudulent action propagation. In Proceedings of the twenty-fourth international joint conference on artificial intelligence (IJCAI 2015) (pp. 2408\u20132414)."},{"key":"689_CR30","doi-asserted-by":"crossref","unstructured":"Zhou, W., Koh, Y. S., Wen, J. H., Burki, S., & Dobbie, G. (2014). Detection of abnormal profiles on group attacks in recommender systems. In Proceedings of the 37th international ACM SIGIR conference on Research on development in information retrieval (pp. 955\u2013958).","DOI":"10.1145\/2600428.2609483"},{"issue":"1","key":"689_CR31","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3158369","volume":"52","author":"S Zhang","year":"2019","unstructured":"Zhang, S., Yao, L., Sun, A., & Tay, Y. (2019). Deep learning based recommender system: A survey and new perspectives. ACM Computing Surveys, 52(1), 1\u201338.","journal-title":"ACM Computing Surveys"},{"key":"689_CR32","doi-asserted-by":"crossref","unstructured":"Gras, B., Brun, A., & Boyer, A. (2016). Identifying grey sheep users in collaborative filtering: a distribution-based technique. In Proceedings of the 2016 conference on user modeling adaptation and personalization (pp. 17\u201326).","DOI":"10.1145\/2930238.2930242"},{"key":"689_CR33","doi-asserted-by":"crossref","unstructured":"Zheng, Y., Agnani, M., & Singh, M. (2017). Identifying grey sheep users by the distribution of user similarities in collaborative filtering. In Proceedings of the 6th annual conference on research in information technology (pp. 1\u20136).","DOI":"10.1145\/3125649.3125651"}],"container-title":["Journal of Intelligent Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10844-021-00689-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10844-021-00689-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10844-021-00689-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,26]],"date-time":"2022-07-26T13:08:40Z","timestamp":1658840920000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10844-021-00689-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,2]]},"references-count":33,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,8]]}},"alternative-id":["689"],"URL":"https:\/\/doi.org\/10.1007\/s10844-021-00689-y","relation":{},"ISSN":["0925-9902","1573-7675"],"issn-type":[{"type":"print","value":"0925-9902"},{"type":"electronic","value":"1573-7675"}],"subject":[],"published":{"date-parts":[[2021,12,2]]},"assertion":[{"value":"10 June 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 November 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 November 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 December 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All authors read and approved the final version of the manuscript.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"All authors have checked the manuscript and have agreed to the submission.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Consent for Publication"}},{"value":"The authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Competing interests"}}]}}