{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T21:46:42Z","timestamp":1743112002985,"version":"3.40.3"},"publisher-location":"Cham","reference-count":31,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030926373"},{"type":"electronic","value":"9783030926380"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-92638-0_26","type":"book-chapter","created":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T13:02:45Z","timestamp":1641042165000},"page":"435-450","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["PATR: A\u00a0Novel Poisoning Attack Based on\u00a0Triangle Relations Against Deep Learning-Based Recommender Systems"],"prefix":"10.1007","author":[{"given":"Meiling","family":"Chao","sequence":"first","affiliation":[]},{"given":"Min","family":"Gao","sequence":"additional","affiliation":[]},{"given":"Junwei","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Zongwei","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Quanwu","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Yulin","family":"He","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,1,1]]},"reference":[{"issue":"3","key":"26_CR1","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1145\/245108.245121","volume":"40","author":"P Resnick","year":"1997","unstructured":"Resnick, P., Varian, H.R.: Recommender systems. Commun. ACM 40(3), 56\u201358 (1997)","journal-title":"Commun. ACM"},{"issue":"8","key":"26_CR2","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1109\/MC.2009.263","volume":"42","author":"Y Koren","year":"2009","unstructured":"Koren, Y., Bell, R., Volinsky, C.: Matrix factorization techniques for recommender systems. Computer 42(8), 30\u201337 (2009)","journal-title":"Computer"},{"key":"26_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-0-387-85820-3_1","volume-title":"Recommender Systems Handbook","author":"F Ricci","year":"2011","unstructured":"Ricci, F., Rokach, L., Shapira, B.: Introduction to Recommender Systems Handbook. In: Ricci, F., Rokach, L., Shapira, B., Kantor, P.B. (eds.) Recommender Systems Handbook, pp. 1\u201335. Springer, Boston (2011). https:\/\/doi.org\/10.1007\/978-0-387-85820-3_1"},{"issue":"4","key":"26_CR4","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., et al.: Collaborative recommendation: a robustness analysis. ACM Trans. Internet Technol. (TOIT) 4(4), 344\u2013377 (2004)","journal-title":"ACM Trans. Internet Technol. (TOIT)"},{"key":"26_CR5","doi-asserted-by":"crossref","unstructured":"Hurley, N.J.: Robustness of recommender systems. In: Proceedings of the fifth ACM Conference on Recommender Systems, pp. 9\u201310 (2011)","DOI":"10.1145\/2043932.2043937"},{"key":"26_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1007\/3-540-45748-8_24","volume-title":"Peer-to-Peer Systems","author":"JR Douceur","year":"2002","unstructured":"Douceur, J.R.: The Sybil attack. In: Druschel, P., Kaashoek, F., Rowstron, A. (eds.) IPTPS 2002. LNCS, vol. 2429, pp. 251\u2013260. Springer, Heidelberg (2002). https:\/\/doi.org\/10.1007\/3-540-45748-8_24"},{"key":"26_CR7","doi-asserted-by":"crossref","unstructured":"Wilson, D.C., Seminario, C.E.: When power users attack: assessing impacts in collaborative recommender systems. In: Proceedings of the 7th ACM Conference on Recommender Systems, pp. 427\u2013430 (2013)","DOI":"10.1145\/2507157.2507220"},{"key":"26_CR8","unstructured":"Li, B., Wang, Y., Singh, A., et al.: Data poisoning attacks on factorization-based collaborative filtering. In: Proceedings of the 30th International Conference on Neural Information Processing Systems, pp. 1893\u20131901 (2016)"},{"key":"26_CR9","unstructured":"Pang, M., Gao, W., Tao, M., et al.: Unorganized malicious attacks detection. In: Proceedings of the 32nd International Conference on Neural Information Processing Systems, pp. 6976\u20136985 (2018)"},{"issue":"4","key":"26_CR10","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., et al.: Shilling attacks against recommender systems: a comprehensive survey. Artif. Intell. Rev. 42(4), 767\u2013799 (2014)","journal-title":"Artif. Intell. Rev."},{"key":"26_CR11","doi-asserted-by":"crossref","unstructured":"Lam, S.K., Riedl, J.: Shilling recommender systems for fun and profit. In: Proceedings of the 13th International Conference on World Wide Web, pp. 393\u2013402 (2004)","DOI":"10.1145\/988672.988726"},{"issue":"1","key":"26_CR12","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1007\/s10462-018-9655-x","volume":"53","author":"M Si","year":"2020","unstructured":"Si, M., Li, Q.: Shilling attacks against collaborative recommender systems: a review. Artif. Intell. Rev. 53(1), 291\u2013319 (2020)","journal-title":"Artif. Intell. Rev."},{"issue":"3","key":"26_CR13","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1007\/s11761-007-0013-0","volume":"1","author":"CA Williams","year":"2007","unstructured":"Williams, C.A., Mobasher, B., Burke, R.: Defending recommender systems: detection of profile injection attacks. Serv. Oriented Comput. Appl. 1(3), 157\u2013170 (2007)","journal-title":"Serv. Oriented Comput. Appl."},{"key":"26_CR14","doi-asserted-by":"crossref","unstructured":"Meng, W., Xing, X., Sheth, A., et al.: Your online interests: Pwned! A pollution attack against targeted advertising. In: Proceedings of the ACM SIGSAC Conference on Computer and Communications Security, vol. 2014, pp. 129\u2013140 (2014)","DOI":"10.1145\/2660267.2687258"},{"key":"26_CR15","doi-asserted-by":"crossref","unstructured":"Lin, C., Chen, S., Li, H., et al.: Attacking recommender systems with augmented user profiles. In: Proceedings of the 29th ACM International Conference on Information & Knowledge Management, pp. 855\u2013864 (2020)","DOI":"10.1145\/3340531.3411884"},{"key":"26_CR16","unstructured":"Brendel, W., Rauber, J., Bethge, M.: Decision-based adversarial attacks: reliable attacks against black-box machine learning models. In: International Conference on Learning Representations (2018)"},{"issue":"1","key":"26_CR17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3158369","volume":"52","author":"S Zhang","year":"2019","unstructured":"Zhang, S., Yao, L., Sun, A., et al.: Deep learning based recommender system: a survey and new perspectives. ACM Comput. Surv. (CSUR) 52(1), 1\u201338 (2019)","journal-title":"ACM Comput. Surv. (CSUR)"},{"issue":"2","key":"26_CR18","doi-asserted-by":"publisher","first-page":"25","DOI":"10.3390\/computation7020025","volume":"7","author":"AK Sahoo","year":"2019","unstructured":"Sahoo, A.K., Pradhan, C., Barik, R.K., et al.: DeepReco: deep learning based health recommender system using collaborative filtering. Computation 7(2), 25 (2019)","journal-title":"Computation"},{"key":"26_CR19","unstructured":"van den Berg, R., Kipf, T.N., Welling, M.: Graph convolutional matrix completion (2017)"},{"key":"26_CR20","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1007\/978-3-642-21735-7_7","volume-title":"Artificial Neural Networks and Machine Learning \u2013 ICANN 2011","author":"J Masci","year":"2011","unstructured":"Masci, J., Meier, U., Cire\u015fan, D., Schmidhuber, J.: Stacked convolutional auto-encoders for hierarchical feature extraction. In: Honkela, T., Duch, W., Girolami, M., Kaski, S. (eds.) ICANN 2011. LNCS, vol. 6791, pp. 52\u201359. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-21735-7_7"},{"key":"26_CR21","doi-asserted-by":"crossref","unstructured":"Herlocker, J.L., Konstan, J.A., Riedl, J.: Explaining collaborative filtering recommendations. In: Proceedings of the ACM Conference on Computer Supported Cooperative Work, vol. 2000, pp. 241\u2013250 (2000)","DOI":"10.1145\/358916.358995"},{"key":"26_CR22","unstructured":"Burke, R., Mobasher, B., Bhaumik, R., et al.: Segment-based injection attacks against collaborative filtering recommender systems. In: Fifth IEEE International Conference on Data Mining (ICDM\u201905). IEEE (2005)"},{"key":"26_CR23","doi-asserted-by":"crossref","unstructured":"Mobasher, B., Burke, R., Bhaumik, R., et al.: Toward trustworthy recommender systems: an analysis of attack models and algorithm robustness. ACM Trans. Internet Technol. (TOIT) 7, 23-es (2007)","DOI":"10.1145\/1278366.1278372"},{"key":"26_CR24","doi-asserted-by":"crossref","unstructured":"Fang, M., Yang, G., Gong, N.Z., et al.: Poisoning attacks to graph-based recommender systems. In: Proceedings of the 34th Annual Computer Security Applications Conference, pp. 381\u2013392 (2018)","DOI":"10.1145\/3274694.3274706"},{"key":"26_CR25","doi-asserted-by":"crossref","unstructured":"Zhang, H., Li, Y., Ding, B., et al.: Practical data poisoning attack against next-item recommendation. In: Proceedings of The Web Conference 2020, pp. 2458\u20132464 (2020)","DOI":"10.1145\/3366423.3379992"},{"key":"26_CR26","unstructured":"Mescheder, L., Geiger, A., Nowozin, S.: Which training methods for GANs do actually converge? In: International Conference on Machine Learning, PMLR, pp. 3481\u20133490 (2018)"},{"issue":"1","key":"26_CR27","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3301282","volume":"52","author":"Y Hong","year":"2019","unstructured":"Hong, Y., Hwang, U., Yoo, J., et al.: How generative adversarial networks and their variants work: an overview. ACM Comput. Surv. (CSUR) 52(1), 1\u201343 (2019)","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"26_CR28","doi-asserted-by":"crossref","unstructured":"He, X., Liao, L., Zhang, H., et al.: Neural collaborative filtering. In: Proceedings of the 26th International Conference on World Wide Web, pp. 173\u2013182 (2017)","DOI":"10.1145\/3038912.3052569"},{"key":"26_CR29","doi-asserted-by":"crossref","unstructured":"Xue, H.J., Dai, X., Zhang, J., et al.: Deep matrix factorization models for recommender systems. In: International Joint Conference on Artificial Intelligence, vol. 17, pp. 3203\u20133209 (2017)","DOI":"10.24963\/ijcai.2017\/447"},{"key":"26_CR30","first-page":"102493","volume":"52","author":"Q Zhou","year":"2020","unstructured":"Zhou, Q., Wu, J., Duan, L.: Recommendation attack detection based on deep learning. J. Inf. Secur. Appl. 52, 102493 (2020)","journal-title":"J. Inf. Secur. Appl."},{"issue":"10","key":"26_CR31","doi-asserted-by":"publisher","first-page":"2600","DOI":"10.1587\/transinf.2015EDP7500","volume":"99","author":"W Li","year":"2016","unstructured":"Li, W., Gao, M., Li, H., et al.: Shilling attack detection in recommender systems via selecting patterns analysis. IEICE Trans. Inf. Syst. 99(10), 2600\u20132611 (2016)","journal-title":"IEICE Trans. Inf. Syst."}],"container-title":["Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","Collaborative Computing: Networking, Applications and Worksharing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-92638-0_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,21]],"date-time":"2023-01-21T12:17:32Z","timestamp":1674303452000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-92638-0_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030926373","9783030926380"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-92638-0_26","relation":{},"ISSN":["1867-8211","1867-822X"],"issn-type":[{"type":"print","value":"1867-8211"},{"type":"electronic","value":"1867-822X"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"1 January 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CollaborateCom","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Collaborative Computing: Networking, Applications and Worksharing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 October 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 October 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"colcom2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/collaboratecom.eai-conferences.org\/2021\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Confy +","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"206","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"62","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"7","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"30% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}