{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,15]],"date-time":"2026-03-15T23:00:44Z","timestamp":1773615644954,"version":"3.50.1"},"reference-count":40,"publisher":"Allerton Press","issue":"2","license":[{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Aut. Control Comp. Sci."],"published-print":{"date-parts":[[2025,4]]},"DOI":"10.3103\/s0146411625700178","type":"journal-article","created":{"date-parts":[[2025,7,4]],"date-time":"2025-07-04T15:27:56Z","timestamp":1751642876000},"page":"206-218","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Utilizing Artificial Intelligence to Detect Fraudulent Manipulation in Recommender Systems"],"prefix":"10.3103","volume":"59","author":[{"family":"Kulvinder Singh","sequence":"first","affiliation":[]},{"given":"Sanjeev","family":"Dhawan","sequence":"additional","affiliation":[]},{"given":"Sarika","family":"Gambhir","sequence":"additional","affiliation":[]}],"member":"1627","published-online":{"date-parts":[[2025,7,4]]},"reference":[{"key":"7828_CR1","doi-asserted-by":"publisher","first-page":"102154","DOI":"10.1016\/j.is.2022.102154","volume":"114","author":"Ya. Hao","year":"2023","unstructured":"Hao, Ya., Meng, G., Wang, J., and Zong, Ch., A detection method for hybrid attacks in recommender systems, Inf. Syst., 2023, vol. 114, p. 102154. https:\/\/doi.org\/10.1016\/j.is.2022.102154","journal-title":"Inf. Syst."},{"key":"7828_CR2","doi-asserted-by":"publisher","unstructured":"Jeny, J.R.V., Sowmya, R., Kiran, G.S., Babu, M.K., and Arjun, C.H., Shilling attack detection system for online recommenders, 2022 International Conference on Inventive Computation Technologies (ICICT), IEEE, 2022, pp. 988\u2013992. https:\/\/doi.org\/10.1109\/icict54344.2022.9850464","DOI":"10.1109\/icict54344.2022.9850464"},{"key":"7828_CR3","doi-asserted-by":"publisher","unstructured":"Singh, H. and Malhotra, M., Artificial intelligence based hybrid models for prediction of stock prices, 2023 2nd\u00a0International Conference for Innovation in Technology (INOCON), Bangalore, India, 2023, IEEE, 2023, pp.\u00a01\u20136. https:\/\/doi.org\/10.1109\/inocon57975.2023.10101297","DOI":"10.1109\/inocon57975.2023.10101297"},{"key":"7828_CR4","doi-asserted-by":"publisher","first-page":"79358","DOI":"10.1109\/access.2023.3289404","volume":"11","author":"R.A. Zayed","year":"2023","unstructured":"Zayed, R.A., Ibrahim, L.F., Hefny, H.A., Salman, H.A., and Almohimeed, A., Experimental and theoretical study for the popular shilling attacks detection methods in collaborative recommender system, IEEE Access, 2023, vol. 11, pp. 79358\u201379369. https:\/\/doi.org\/10.1109\/access.2023.3289404","journal-title":"IEEE Access"},{"key":"7828_CR5","doi-asserted-by":"publisher","first-page":"e0196533","DOI":"10.1371\/journal.pone.0196533","volume":"13","author":"W. Zhou","year":"2018","unstructured":"Zhou, W., Wen, J., Qu, Q., Zeng, J., and Cheng, T., Shilling attack detection for recommender systems based on credibility of group users and rating time series, PLoS One, 2018, vol. 13, no. 5, p. e0196533. https:\/\/doi.org\/10.1371\/journal.pone.0196533","journal-title":"PLoS One"},{"key":"7828_CR6","doi-asserted-by":"publisher","unstructured":"Li, W., Gao, M., Li, H., Zeng, J., Xiong, Q., and Hirokawa, S., Shilling attack detection in recommender systems via selecting patterns analysis, IEICE Trans. Inf. Syst., 2016, vol. e99.d, no. 10, pp. 2600\u20132611. https:\/\/doi.org\/10.1587\/transinf.2015edp7500","DOI":"10.1587\/transinf.2015edp7500"},{"key":"7828_CR7","doi-asserted-by":"publisher","unstructured":"Singh, H. and Malhotra, M., A time series analysis-based stock price prediction framework using artificial intelligence, Artificial Intelligence of Things, Challa, R.K., Aujla, G.S., Mathew, L., Kumar, A., Kalra, M., Shimi, S.L., Saini, G., and Sharma, K., Eds., Communications in Computer and Information Science, Cham: Springer, 2023, pp. 280\u2013289. https:\/\/doi.org\/10.1007\/978-3-031-48781-1_22","DOI":"10.1007\/978-3-031-48781-1_22"},{"key":"7828_CR8","doi-asserted-by":"publisher","unstructured":"Chirita, P.-A., Nejdl, W., and Zamfir, C., Preventing shilling attacks in online recommender systems, Proceedings of the 7th Annual ACM International Workshop on Web Information and Data Management, Bremen, 2005, New York: Association for Computing Machinery, 2005, pp. 67\u201374. https:\/\/doi.org\/10.1145\/1097047.1097061","DOI":"10.1145\/1097047.1097061"},{"key":"7828_CR9","doi-asserted-by":"publisher","unstructured":"Wang, Y., Zhang, L., Tao, H., Wu, Z., and Cao, J., A comparative study of shilling attack detectors for recommender systems, 2015 12th International Conference on Service Systems and Service Management (ICSSSM), Guangzhou, China, 2015, IEEE, 2015, pp. 1\u20136. https:\/\/doi.org\/10.1109\/ICSSSM.2015.7170330","DOI":"10.1109\/ICSSSM.2015.7170330"},{"key":"7828_CR10","doi-asserted-by":"publisher","unstructured":"He, F., Wang, X., and Liu, B., Attack detection by rough set theory in recommendation system, 2010 IEEE International Conference on Granular Computing, San Jose, CA, 2010, IEEE, 2010, pp. 692\u2013695. https:\/\/doi.org\/10.1109\/grc.2010.130","DOI":"10.1109\/grc.2010.130"},{"key":"7828_CR11","doi-asserted-by":"publisher","first-page":"368","DOI":"10.1109\/tnet.2021.3113916","volume":"30","author":"N. Chen","year":"2021","unstructured":"Chen, N., Qiu, T., Lu, Z., and Wu, D.O., An adaptive robustness evolution algorithm with self-competition and its 3D deployment for Internet of Things, IEEE\/ACM Trans. Networking, 2021, vol. 30, no. 1, pp. 368\u2013381. https:\/\/doi.org\/10.1109\/tnet.2021.3113916","journal-title":"IEEE\/ACM Trans. Networking"},{"key":"7828_CR12","doi-asserted-by":"publisher","first-page":"767","DOI":"10.1007\/s10462-012-9364-9","volume":"42","author":"I. Gunes","year":"2014","unstructured":"Gunes, I., Kaleli, C., Bilge, A., and Polat, H., Shilling attacks against recommender systems: A comprehensive survey, Artif. Intell. Rev., 2014, vol. 42, no. 4, pp. 767\u2013799. https:\/\/doi.org\/10.1007\/s10462-012-9364-9","journal-title":"Artif. Intell. Rev."},{"key":"7828_CR13","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1145\/1278366.1278372","volume":"7","author":"B. Mobasher","year":"2007","unstructured":"Mobasher, B., Burke, R., Bhaumik, R., and Williams, C., Toward trustworthy recommender systems: An analysis of attack models and algorithm robustness, ACM Trans. Internet Technol., 2007, vol. 7, no. 4, p. 23. https:\/\/doi.org\/10.1145\/1278366.1278372","journal-title":"ACM Trans. Internet Technol."},{"key":"7828_CR14","doi-asserted-by":"publisher","first-page":"1189","DOI":"10.1109\/tcss.2020.3013878","volume":"7","author":"F. Zhang","year":"2020","unstructured":"Zhang, F. and Wang, Sh., Detecting group shilling attacks in online recommender systems based on bisecting K-means clustering, IEEE Trans. Comput. Soc. Syst., 2020, vol. 7, no. 5, pp. 1189\u20131199. https:\/\/doi.org\/10.1109\/tcss.2020.3013878","journal-title":"IEEE Trans. Comput. Soc. Syst."},{"key":"7828_CR15","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1016\/j.knosys.2019.04.012","volume":"178","author":"Yi. Xu","year":"2019","unstructured":"Xu, Yi. and Zhang, F., Detecting shilling attacks in social recommender systems based on time series analysis and trust features, Knowl.-Based Syst., 2019, vol. 178, pp. 25\u201347. https:\/\/doi.org\/10.1016\/j.knosys.2019.04.012","journal-title":"Knowl.-Based Syst."},{"key":"7828_CR16","doi-asserted-by":"publisher","first-page":"1950011","DOI":"10.1142\/s0219649219500114","volume":"18","author":"J.M. Alostad","year":"2019","unstructured":"Alostad, J.M., Improving the shilling attack detection in recommender systems using an SVM Gaussian mixture model, J. Inf. Knowl. Manage., 2019, vol. 18, no. 1, p. 1950011. https:\/\/doi.org\/10.1142\/s0219649219500114","journal-title":"J. Inf. Knowl. Manage."},{"key":"7828_CR17","unstructured":"Teacy, W., Jennings, N.R., Rogers, A., and Luck, M., A hierarchical bayesian trust model based on reputation and group behaviour, 6th European Workshop on Multi-Agent Systems, Bath, United Kingdom, 2008."},{"key":"7828_CR18","doi-asserted-by":"crossref","unstructured":"Vogiatzis, G., Macgillivray, I., and Chli, M., A probabilistic model for trust and reputation, Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems, Toronto, 2010, Richland, SC: International Foundation for Autonomous Agents and Multiagent Systems, 2010, vol. 1, pp. 225\u2013232.","DOI":"10.65109\/JOPU1790"},{"key":"7828_CR19","doi-asserted-by":"publisher","first-page":"375","DOI":"10.1109\/tdsc.2011.64","volume":"9","author":"E. Ayday","year":"2011","unstructured":"Ayday, E. and Fekri, F., Iterative trust and reputation management using belief propagation, IEEE Trans. Dependable Secure Comput., 2011, vol. 9, no. 3, pp. 375\u2013386. https:\/\/doi.org\/10.1109\/tdsc.2011.64","journal-title":"IEEE Trans. Dependable Secure Comput."},{"key":"7828_CR20","doi-asserted-by":"publisher","first-page":"344","DOI":"10.1145\/1031114.1031116","volume":"4","author":"M. O\u2019Mahony","year":"2004","unstructured":"O\u2019Mahony, M., Hurley, N., Kushmerick, N., and Silvestre, G., Collaborative recommendation, ACM Trans. Internet Technol., 2004, vol. 4, no. 4, pp. 344\u2013377. https:\/\/doi.org\/10.1145\/1031114.1031116","journal-title":"ACM Trans. Internet Technol."},{"key":"7828_CR21","doi-asserted-by":"publisher","first-page":"2601","DOI":"10.1007\/s12652-019-01321-2","volume":"11","author":"Z. Batmaz","year":"2020","unstructured":"Batmaz, Z., Yilmazel, B., and Kaleli, C., Shilling attack detection in binary data: A classification approach, Journal of Ambient Intelligence and Humanized Computing, 2020, vol. 11, no. 6, pp. 2601\u20132611. https:\/\/doi.org\/10.1007\/s12652-019-01321-2","journal-title":"Journal of Ambient Intelligence and Humanized Computing"},{"key":"7828_CR22","doi-asserted-by":"publisher","first-page":"41782","DOI":"10.1109\/access.2019.2905862","volume":"7","author":"S. Alonso","year":"2019","unstructured":"Alonso, S., Bobadilla, J., Ortega, F., and Moya, R., Robust model-based reliability approach to tackle shilling attacks in collaborative filtering recommender systems, IEEE Access, 2019, vol. 7, pp. 41782\u201341798. https:\/\/doi.org\/10.1109\/access.2019.2905862","journal-title":"IEEE Access"},{"key":"7828_CR23","doi-asserted-by":"publisher","first-page":"683","DOI":"10.1016\/j.ins.2021.07.041","volume":"578","author":"F. Wu","year":"2021","unstructured":"Wu, F., Gao, M., Yu, J., Wang, Z., Liu, K., and Wang, X., Ready for emerging threats to recommender systems? A graph convolution-based generative shilling attack, Inf. Sci. (N. Y.), 2021, vol. 578, pp. 683\u2013701. https:\/\/doi.org\/10.1016\/j.ins.2021.07.041","journal-title":"Inf. Sci. (N. Y.)"},{"key":"7828_CR24","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1007\/s11257-008-9050-4","volume":"19","author":"B. Mehta","year":"2009","unstructured":"Mehta, B. and Nejdl, W., Unsupervised strategies for shilling detection and robust collaborative filtering, User Model. User-Adapted Interact., 2009, vol. 19, nos. 1\u20132, pp. 65\u201397. https:\/\/doi.org\/10.1007\/s11257-008-9050-4","journal-title":"User Model. User-Adapted Interact."},{"key":"7828_CR25","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1016\/j.procs.2014.05.257","volume":"31","author":"A. Bilge","year":"2014","unstructured":"Bilge, A., Ozdemir, Z., and Polat, H., A novel shilling attack detection method, Procedia Computer Science, 2014, vol. 31, pp. 165\u2013174. https:\/\/doi.org\/10.1016\/j.procs.2014.05.257","journal-title":"Procedia Computer Science"},{"key":"7828_CR26","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1049\/iet-ifs.2016.0345","volume":"11","author":"L. Yang","year":"2017","unstructured":"Yang, L., Huang, W., and Niu, X., Defending shilling attacks in recommender systems using soft co-clustering, IET Inf. Secur., 2017, vol. 11, no. 6, pp. 319\u2013325. https:\/\/doi.org\/10.1049\/iet-ifs.2016.0345","journal-title":"IET Inf. Secur."},{"key":"7828_CR27","doi-asserted-by":"publisher","first-page":"171703","DOI":"10.1109\/access.2020.3022962","volume":"8","author":"A.P. Sundar","year":"2020","unstructured":"Sundar, A.P., Li, F., Zou, X., Gao, T., and Russomanno, E.D., Understanding shilling attacks and their detection traits: a comprehensive survey, IEEE Access, 2020, vol. 8, pp. 171703\u2013171715. https:\/\/doi.org\/10.1109\/access.2020.3022962","journal-title":"IEEE Access"},{"key":"7828_CR28","doi-asserted-by":"publisher","first-page":"150","DOI":"10.1016\/j.ins.2015.02.019","volume":"306","author":"H. Xia","year":"2015","unstructured":"Xia, H., Fang, B., Gao, M., Ma, H., Tang, Yu., and Wen, J., A novel item anomaly detection approach against shilling attacks in collaborative recommendation systems using the dynamic time interval segmentation technique, Inf. Sci. (N. Y.), 2015, vol. 306, pp. 150\u2013165. https:\/\/doi.org\/10.1016\/j.ins.2015.02.019","journal-title":"Inf. Sci. (N. Y.)"},{"key":"7828_CR29","doi-asserted-by":"publisher","first-page":"579","DOI":"10.1093\/comjnl\/bxy124","volume":"62","author":"H. Cai","year":"2019","unstructured":"Cai, H. and Zhang, F., An unsupervised method for detecting shilling attacks in recommender systems by mining item relationship and identifying target items, Comput. J., 2019, vol. 62, no. 4, pp. 579\u2013597. https:\/\/doi.org\/10.1093\/comjnl\/bxy124","journal-title":"Comput. J."},{"key":"7828_CR30","doi-asserted-by":"publisher","first-page":"499","DOI":"10.1111\/coin.12579","volume":"39","author":"T.T. Kaya","year":"2023","unstructured":"Kaya, T.T., Yalcin, E., and Kaleli, C., A novel classification-based shilling attack detection approach for multi-criteria recommender systems, Comput. Intell., 2023, vol. 39, no. 3, pp. 499\u2013528. https:\/\/doi.org\/10.1111\/coin.12579","journal-title":"Comput. Intell."},{"key":"7828_CR31","doi-asserted-by":"publisher","first-page":"2929","DOI":"10.1007\/s40747-021-00357-2","volume":"9","author":"L. Yang","year":"2023","unstructured":"Yang, L. and Niu, X., A genre trust model for defending shilling attacks in recommender systems, Complex Intell. Syst., 2023, vol. 9, no. 3, pp. 2929\u20132942. https:\/\/doi.org\/10.1007\/s40747-021-00357-2","journal-title":"Complex Intell. Syst."},{"key":"7828_CR32","doi-asserted-by":"publisher","first-page":"108673","DOI":"10.1016\/j.compeleceng.2023.108673","volume":"108","author":"N. Praveena","year":"2023","unstructured":"Praveena, N., Juneja, K., Rashid, M., Almagrabi, A.O., Sekaran, K., Ramalingam, R., and Usman, M., Hybrid gated recurrent unit and convolutional neural network-based deep learning mechanism for efficient shilling attack detection in social networks, Comput. Electr. Eng., 2023, vol. 108, p. 108673. https:\/\/doi.org\/10.1016\/j.compeleceng.2023.108673","journal-title":"Comput. Electr. Eng."},{"key":"7828_CR33","doi-asserted-by":"publisher","first-page":"321","DOI":"10.5829\/ije.2023.36.02b.12","volume":"36","author":"R. Moradi","year":"2023","unstructured":"Moradi, R. and Hamidi, H., A new mechanism for detecting shilling attacks in recommender systems based on social network analysis and Gaussian rough neural network with emotional learning, Int. J. Eng., 2023, vol. 36, no. 2, pp. 321\u2013334. https:\/\/doi.org\/10.5829\/ije.2023.36.02b.12","journal-title":"Int. J. Eng."},{"key":"7828_CR34","doi-asserted-by":"publisher","first-page":"845897","DOI":"10.1155\/2014\/845897","volume":"2014","author":"M. Gao","year":"2014","unstructured":"Gao, M., Yuan, Q., Ling, B., and Xiong, Q., Detection of abnormal item based on time intervals for recommender systems, Sci. World J., 2014, vol. 2014, p. 845897. https:\/\/doi.org\/10.1155\/2014\/845897","journal-title":"Sci. World J."},{"key":"7828_CR35","doi-asserted-by":"publisher","unstructured":"Hurley, N., Cheng, Z., and Zhang, M., Statistical attack detection, Proceedings of the Third ACM Conference on Recommender Systems, New York, 2009, New York: Association for Computing Machinery, 2009, pp. 149\u2013156. https:\/\/doi.org\/10.1145\/1639714.1639740","DOI":"10.1145\/1639714.1639740"},{"key":"7828_CR36","doi-asserted-by":"publisher","unstructured":"Burke, R., Mobasher, B., Williams, C., and Bhaumik, R., Detecting profile injection attacks in collaborative recommender systems, The 8th IEEE International Conference on E-Commerce Technology and The 3rd IEEE International Conference on Enterprise Computing, E-Commerce, and E-Services (CEC\/EEE\u201906), San Francisco, 2006, IEEE, 2006, pp. 23\u201323. https:\/\/doi.org\/10.1109\/cec-eee.2006.34","DOI":"10.1109\/cec-eee.2006.34"},{"key":"7828_CR37","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1145\/2382438.2382442","volume":"30","author":"G. Adomavicius","year":"2012","unstructured":"Adomavicius, G. and Zhang, J., Stability of recommendation algorithms, ACM Trans. Inf. Syst., 2012, vol. 30, no. 4, p. 23. https:\/\/doi.org\/10.1145\/2382438.2382442","journal-title":"ACM Trans. Inf. Syst."},{"key":"7828_CR38","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, Yu., Xu, Yi., and Wang, Sh., Graph embedding-based approach for detecting group shilling attacks in collaborative recommender systems, Knowl.-Based Syst., 2020, vol. 199, p. 105984. https:\/\/doi.org\/10.1016\/j.knosys.2020.105984","journal-title":"Knowl.-Based Syst."},{"key":"7828_CR39","doi-asserted-by":"publisher","unstructured":"Zhang, F., Deng, Z.-J., He, Z.-M., Lin, X.-C., and Sun, L.-L., Detection of shilling attack in collaborative filtering recommender system by PCA and data complexity, 2018 International Conference on Machine Learning and Cybernetics (ICMLC), Chengdu, China, 2018, IEEE, 2018, vol. 2, pp. 673\u2013678. https:\/\/doi.org\/10.1109\/icmlc.2018.8526965","DOI":"10.1109\/icmlc.2018.8526965"},{"key":"7828_CR40","doi-asserted-by":"publisher","first-page":"823","DOI":"10.1007\/s42979-023-02349-0","volume":"4","author":"H. Singh","year":"2023","unstructured":"Singh, H. and Malhotra, M., A novel approach of stock price direction and price prediction based on investor\u2019s sentiments, SN Computer Science, 2023, vol. 4, no. 6, p. 823. https:\/\/doi.org\/10.1007\/s42979-023-02349-0","journal-title":"SN Computer Science"}],"container-title":["Automatic Control and Computer Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.3103\/S0146411625700178.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.3103\/S0146411625700178","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.3103\/S0146411625700178.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,15]],"date-time":"2026-03-15T22:02:41Z","timestamp":1773612161000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.3103\/S0146411625700178"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4]]},"references-count":40,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,4]]}},"alternative-id":["7828"],"URL":"https:\/\/doi.org\/10.3103\/s0146411625700178","relation":{},"ISSN":["0146-4116","1558-108X"],"issn-type":[{"value":"0146-4116","type":"print"},{"value":"1558-108X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4]]},"assertion":[{"value":"17 January 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 June 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 June 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 July 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors of this work declare that they have no conflicts of interest.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"CONFLICT OF INTEREST"}}]}}