{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,8]],"date-time":"2026-02-08T00:37:03Z","timestamp":1770511023479,"version":"3.49.0"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030432287","type":"print"},{"value":"9783030432294","type":"electronic"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-43229-4_23","type":"book-chapter","created":{"date-parts":[[2020,3,19]],"date-time":"2020-03-19T00:03:53Z","timestamp":1584576233000},"page":"261-271","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Click-Fraud Detection for Online Advertising"],"prefix":"10.1007","author":[{"given":"Roman","family":"Wiatr","sequence":"first","affiliation":[]},{"given":"Vladyslav","family":"Lyutenko","sequence":"additional","affiliation":[]},{"given":"Mi\u0142osz","family":"Demczuk","sequence":"additional","affiliation":[]},{"given":"Renata","family":"S\u0142ota","sequence":"additional","affiliation":[]},{"given":"Jacek","family":"Kitowski","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,3,19]]},"reference":[{"key":"23_CR1","unstructured":"okhttp. \nhttps:\/\/square.github.io\/okhttp\/\n\n. Accessed 31 Mar 2019"},{"key":"23_CR2","unstructured":"p0f. \nhttp:\/\/lcamtuf.coredump.cx\/p0f3\/\n\n. Accessed 31 Mar 2019"},{"issue":"12","key":"23_CR3","doi-asserted-by":"publisher","first-page":"1792","DOI":"10.14778\/2824032.2824076","volume":"8","author":"T Akidau","year":"2015","unstructured":"Akidau, T., et al.: The dataflow model: a practical approach to balancing correctness, latency, and cost in massive-scale, unbounded, out-of-order data processing. Proc. VLDB Endow. 8(12), 1792\u20131803 (2015)","journal-title":"Proc. VLDB Endow."},{"key":"23_CR4","first-page":"1","volume":"33","author":"MH Bhuyan","year":"2014","unstructured":"Bhuyan, M.H., Bhattacharyya, D.K., Kalita, J.K.: Towards an unsupervised method for network anomaly detection in large datasets. Comput. Inform. 33, 1\u201334 (2014)","journal-title":"Comput. Inform."},{"key":"23_CR5","unstructured":"Carbone, P., et\u00a0al.: Apache flink: Stream and batch processing in a single engine. Bull. IEEE Tech. Comm. Data Eng. 38(4), 28\u201338 (2015)"},{"key":"23_CR6","unstructured":"Daswani, N., Stoppelman, M.: The anatomy of Clickbot.A. In: Proceedings of the First Workshop on Hot Topics in Understanding Botnets, p. 11. USENIX (2007)"},{"key":"23_CR7","doi-asserted-by":"crossref","unstructured":"Dave, V., et al.: Measuring and fingerprinting click-spam in ad networks. In: Proceedings of the ACM SIGCOMM 2012, pp. 175\u2013186. ACM (2012)","DOI":"10.1145\/2342356.2342394"},{"key":"23_CR8","doi-asserted-by":"crossref","unstructured":"Dave, V., et al.: ViceROI: catching click-spam in search ad networks. In: Proceedings of the 2013 ACM SIGSAC, pp. 765\u2013776. ACM (2013)","DOI":"10.1145\/2508859.2516688"},{"issue":"3","key":"23_CR9","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1108\/07363760510595986","volume":"22","author":"DL Duffy","year":"2005","unstructured":"Duffy, D.L.: Affiliate marketing and its impact on e-commerce. J. Consum. Mark. 22(3), 161\u2013163 (2005)","journal-title":"J. Consum. Mark."},{"issue":"4","key":"23_CR10","doi-asserted-by":"publisher","first-page":"351","DOI":"10.7494\/csci.2015.16.4.351","volume":"16","author":"G Frankowski","year":"2015","unstructured":"Frankowski, G., et al.: Application of the complex event processing system for anomaly detection and network monitoring. Comput. Sci. 16(4), 351\u2013371 (2015)","journal-title":"Comput. Sci."},{"key":"23_CR11","doi-asserted-by":"publisher","first-page":"27","DOI":"10.4135\/9781849208499","volume-title":"100 Statistical Tests","author":"GK Kanji","year":"2006","unstructured":"Kanji, G.K.: 100 Statistical Tests, p. 27. Thousand Oaks, SAGE (2006)"},{"key":"23_CR12","doi-asserted-by":"crossref","unstructured":"Kim, I.L., et al.: AdBudgetKiller: online advertising budget draining attack. In: Proceedings of the 2018 World Wide Web Conference on World Wide Web, pp. 297\u2013307. International World Wide Web Conferences Steering Committee (2018)","DOI":"10.1145\/3178876.3186096"},{"key":"23_CR13","series-title":"Annals of Information Systems","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1007\/978-3-319-07812-0_10","volume-title":"Real World Data Mining Applications","author":"B Kitts","year":"2015","unstructured":"Kitts, B., et al.: Click fraud detection: adversarial pattern recognition over 5\u00a0years at microsoft. In: Abou-Nasr, M., Lessmann, S., Stahlbock, R., Weiss, G.M. (eds.) Real World Data Mining Applications. AIS, vol. 17, pp. 181\u2013201. Springer, Cham (2015). \nhttps:\/\/doi.org\/10.1007\/978-3-319-07812-0_10"},{"issue":"1","key":"23_CR14","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1109\/MC.2018.2887322","volume":"52","author":"N Kshetri","year":"2019","unstructured":"Kshetri, N., Voas, J.: Online advertising fraud. Computer 52(1), 58\u201361 (2019)","journal-title":"Computer"},{"key":"23_CR15","doi-asserted-by":"crossref","unstructured":"Metwally, A., Paduano, M.: Estimating the number of users behind IP addresses for combating abusive traffic. In: Proceedings of ACM SIGKDD, pp. 249\u2013257. ACM (2011)","DOI":"10.1145\/2020408.2020452"},{"key":"23_CR16","doi-asserted-by":"crossref","unstructured":"Metwally, A., et al.: Detectives: detecting coalition hit inflation attacks in advertising networks streams. In: Proceedings of the WWW Conference, pp. 241\u2013250. ACM (2007)","DOI":"10.1145\/1242572.1242606"},{"issue":"2","key":"23_CR17","doi-asserted-by":"publisher","first-page":"1217","DOI":"10.14778\/1454159.1454161","volume":"1","author":"A Metwally","year":"2008","unstructured":"Metwally, A., et al.: SLEUTH: single-publisher attack detection using correlation hunting. Proc. VLDB Endow. 1(2), 1217\u20131228 (2008)","journal-title":"Proc. VLDB Endow."},{"key":"23_CR18","doi-asserted-by":"crossref","unstructured":"Mouawi, R., et al.: Towards a machine learning approach for detecting click fraud in mobile advertizing. In: 2018 IEEE IIT Conference, pp. 88\u201392. IEEE (2018)","DOI":"10.1109\/INNOVATIONS.2018.8605973"},{"issue":"1","key":"23_CR19","first-page":"99","volume":"15","author":"R Oentaryo","year":"2014","unstructured":"Oentaryo, R., et al.: Detecting click fraud in online advertising: a data mining approach. J. Mach. Learn. Res. 15(1), 99\u2013140 (2014)","journal-title":"J. Mach. Learn. Res."},{"issue":"2","key":"23_CR20","doi-asserted-by":"publisher","first-page":"378","DOI":"10.1016\/j.comnet.2012.07.021","volume":"57","author":"SS Silva","year":"2013","unstructured":"Silva, S.S., et al.: Botnets: a survey. Comput. Netw. 57(2), 378\u2013403 (2013)","journal-title":"Comput. Netw."},{"key":"23_CR21","doi-asserted-by":"crossref","unstructured":"Soldo, F., Metwally, A.: Traffic anomaly detection based on the IP size distribution. In: 2012 IEEE INFOCOM, pp. 2005\u20132013. IEEE (2012)","DOI":"10.1109\/INFCOM.2012.6195581"},{"key":"23_CR22","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/j.procs.2018.08.242","volume":"136","author":"R Wiatr","year":"2018","unstructured":"Wiatr, R., S\u0142ota, R., Kitowski, J.: Optimising Kafka for stream processing in latency sensitive systems. Procedia Comput. Sci. 136, 99\u2013108 (2018)","journal-title":"Procedia Comput. Sci."},{"issue":"2","key":"23_CR23","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1287\/mksc.1080.0397","volume":"28","author":"KC Wilbur","year":"2009","unstructured":"Wilbur, K.C., Zhu, Y.: Click fraud. Mark. Sci. 28(2), 293\u2013308 (2009)","journal-title":"Mark. Sci."},{"key":"23_CR24","doi-asserted-by":"crossref","unstructured":"Yuan, Y., et al.: A survey on real time bidding advertising. In: Proceedings of 2014 IEEE SOLI Conference, pp. 418\u2013423. IEEE (2014)","DOI":"10.1109\/SOLI.2014.6960761"}],"container-title":["Lecture Notes in Computer Science","Parallel Processing and Applied Mathematics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-43229-4_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,3,19]],"date-time":"2020-03-19T00:09:16Z","timestamp":1584576556000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-43229-4_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030432287","9783030432294"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-43229-4_23","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"19 March 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PPAM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Parallel Processing and Applied Mathematics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bialystok","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Poland","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 September 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 September 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ppam2019a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.ppam.pl\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"161","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":"91","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":"0","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":"57% - 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":"2,5","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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}