{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T11:53:16Z","timestamp":1778759596915,"version":"3.51.4"},"publisher-location":"Cham","reference-count":45,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783031160776","type":"print"},{"value":"9783031160783","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-16078-3_9","type":"book-chapter","created":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:16:25Z","timestamp":1661991385000},"page":"155-169","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Boundary-Based Fake Face Anomaly Detection in\u00a0Videos Using Recurrent Neural Networks"],"prefix":"10.1007","author":[{"given":"Yashas","family":"Hariprasad","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"K. J.","family":"Latesh Kumar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"L.","family":"Suraj","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"S. S.","family":"Iyengar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,9,1]]},"reference":[{"key":"9_CR1","unstructured":"Challenges of Big Data in cybersecurity (2019). https:\/\/bigdataldn.com\/intelligence\/challenges-of-big-data-in-cybersecurity\/. Accessed 01 Feb 2022"},{"key":"9_CR2","unstructured":"Cybercrimes Rise (2022). https:\/\/www.beyondidentity.com\/blog\/rise-cybercrime-study\/. Accessed 12 Feb 2022"},{"key":"9_CR3","unstructured":"Zoom: Annual Report, Fiscal 2020. Zoom Video Communications, San Jose, CA (2020)"},{"key":"9_CR4","unstructured":"Mukherjee, S.: Cisco\u2019s Webex Draws Record 324 Million Users in March. Technology News (blog), 3 April 2020"},{"key":"9_CR5","unstructured":"Spencer, M., Nadella, S., Hood, A.: Microsoft Fiscal Year 2020 Third Quarter Earnings Conference Call. Microsoft, Redmond, 29 April 2020"},{"key":"9_CR6","unstructured":"Sandvine, F.: The Global Internet Phenomena Report: COVID-19 Spotlight. CA (2020)"},{"key":"9_CR7","unstructured":"Frame Rate (2022). https:\/\/www.techsmith.com\/blog\/frame-rate-beginners-guide\/. Accessed 12 Feb 2022"},{"key":"9_CR8","doi-asserted-by":"crossref","unstructured":"Isola, P., Zhu, J.-Y., Zhou, T., Efros, A.A.: Image-to-image translation with conditional adversarial networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1125\u20131134 (2017)","DOI":"10.1109\/CVPR.2017.632"},{"key":"9_CR9","doi-asserted-by":"crossref","unstructured":"Zhu, J.-Y., Park, T., Isola, P., Efros, A.A.: Unpaired image-to-image translation using cycle-consistent adversarial networks. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2223\u20132232 (2017)","DOI":"10.1109\/ICCV.2017.244"},{"key":"9_CR10","unstructured":"Goodfellow, I., et al.: Generative adversarial nets. In: Advances in Neural Information Processing Systems, vol. 27 (2014)"},{"key":"9_CR11","unstructured":"Liu, M.-Y., Breuel, T., Kautz, J.: Unsupervised image-to-image translation networks. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"key":"9_CR12","doi-asserted-by":"crossref","unstructured":"Li, Y., Chang, M.-C., Lyu, S.: In ictu oculi: exposing AI created fake videos by detecting eye blinking. In: 2018 IEEE International Workshop on Information Forensics and Security (WIFS), pp. 1\u20137. IEEE (2018)","DOI":"10.1109\/WIFS.2018.8630787"},{"key":"9_CR13","unstructured":"Lorant, S.: Lincoln: A Picture Story of His Life. WW Norton, New York (1969)"},{"key":"9_CR14","unstructured":"Chesney, R., Citron, D.: (2018). https:\/\/www.lawfareblog.com\/deepfakes-looming-crisis-national-security-democracy-and-privacy. Accessed 12 Feb 2022"},{"key":"9_CR15","unstructured":"Abadi, M., et al.: TensorFlow: a system for large-scale machine learning. In: 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI 2016), pp. 265\u2013283 (2016)"},{"key":"9_CR16","doi-asserted-by":"publisher","first-page":"132306","DOI":"10.1016\/j.physd.2019.132306","volume":"404","author":"A Sherstinsky","year":"2020","unstructured":"Sherstinsky, A.: Fundamentals of recurrent neural network (RNN) and long short-term memory (LSTM) network. Physica D: Nonlinear Phenom. 404, 132306 (2020)","journal-title":"Physica D: Nonlinear Phenom."},{"key":"9_CR17","unstructured":"(2018). https:\/\/www.technologyreview.com\/2018\/10\/16\/139747\/actors-are-digitally-preserving-themselves-to-continue-their-careers-beyond-the-grave\/. Accessed 12 Feb 2022"},{"key":"9_CR18","unstructured":"Jaiman, A.: (2020). https:\/\/towardsdatascience.com\/positive-use-cases-of-deepfakes-49f510056387. Accessed 12 Feb 2022"},{"key":"9_CR19","unstructured":"(2020). https:\/\/malariamustdie.com\/news\/david-beckham-launches-worlds-first-voice-petition-end-malaria. Accessed 12 Feb 2022"},{"key":"9_CR20","unstructured":"(2021). https:\/\/www.techtarget.com\/searchenterpriseai\/news\/252494572\/Doubts-about-Trump-video-show-how-hard-deepfakes-are-to-detect. Accessed 12 Feb 2022"},{"key":"9_CR21","unstructured":"(2018). https:\/\/www.cnbc.com\/2018\/12\/07\/deepfake-ai-trump-impersonator-highlights-election-fake-news-threat.html. Accessed 12 Feb 2022"},{"key":"9_CR22","unstructured":"(2020). https:\/\/www.wired.com\/story\/what-happened-deepfake-threat-election\/. Accessed 12 Feb 2022"},{"key":"9_CR23","unstructured":"(2020). https:\/\/www.vox.com\/2020\/6\/8\/21284005\/urgent-threat-deepfakes-politics-porn-kristen-bell. Accessed 12 Feb 2022"},{"key":"9_CR24","doi-asserted-by":"crossref","unstructured":"Sencar, H.T., Memon, N.: Digital image forensics. Counter-Forensics: Attacking Image Forensics (2013)","DOI":"10.1007\/978-1-4614-0757-7"},{"key":"9_CR25","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/10451.001.0001","volume-title":"Photo Forensics","author":"H Farid","year":"2016","unstructured":"Farid, H.: Photo Forensics. MIT Press, Cambridge (2016)"},{"key":"9_CR26","doi-asserted-by":"crossref","unstructured":"G\u00fcera, D., Wang, Y., Bondi, L., Bestagini, P., Tubaro, S., Delp, E.J.: A counter-forensic method for CNN-based camera model identification. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 1840\u20131847. IEEE (2017)","DOI":"10.1109\/CVPRW.2017.230"},{"key":"9_CR27","doi-asserted-by":"crossref","unstructured":"G\u00fcera, D., Zhu, F., Yarlagadda, S.K., Tubaro, S., Bestagini, P., Delp, E.J.: Reliability map estimation for CNN-based camera model attribution. In: 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 964\u2013973. IEEE (2018)","DOI":"10.1109\/WACV.2018.00111"},{"key":"9_CR28","doi-asserted-by":"crossref","unstructured":"Conotter, V., Bodnari, E., Boato, G., Farid, H.: Physiologically-based detection of computer generated faces in video. In: 2014 IEEE International Conference on Image Processing (ICIP), pp. 248\u2013252. IEEE (2014)","DOI":"10.1109\/ICIP.2014.7025049"},{"key":"9_CR29","doi-asserted-by":"crossref","unstructured":"Rahmouni, N., Nozick, V., Yamagishi, J., Echizen, I.: Distinguishing computer graphics from natural images using convolution neural networks. In: 2017 IEEE Workshop on Information Forensics and Security (WIFS), pp. 1\u20136. IEEE (2017)","DOI":"10.1109\/WIFS.2017.8267647"},{"key":"9_CR30","unstructured":"Raja, K., Venkatesh, S., Christoph Busch, R.B.: Transferable deep-CNN features for detecting digital and print-scanned morphed face images. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 10\u201318 (2017)"},{"key":"9_CR31","doi-asserted-by":"crossref","unstructured":"Zhou, P., Han, X., Morariu, V.I., Davis, L.S.: Two-stream neural networks for tampered face detection. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 1831\u20131839. IEEE (2017)","DOI":"10.1109\/CVPRW.2017.229"},{"key":"9_CR32","unstructured":"R\u00f6ssler, A., Cozzolino, D., Verdoliva, L., Riess, C., Thies, J., Nie\u00dfner, M.: Faceforensics: a large-scale video dataset for forgery detection in human faces. arXiv preprint arXiv:1803.09179 (2018)"},{"key":"9_CR33","doi-asserted-by":"crossref","unstructured":"Nasir, J.A., Khan, O.S., Varlamis, I.: Fake news detection: a hybrid CNN-RNN based deep learning approach. Int. J. Inf. Manag. Data Insights 1(1) (2021)","DOI":"10.1016\/j.jjimei.2020.100007"},{"key":"9_CR34","doi-asserted-by":"crossref","unstructured":"Li, Y., Chang, M.-C., Lyu, S.: In ictu oculi: exposing AI created fake videos by detecting eye blinking. In: 2018 IEEE International Workshop on Information Forensics and Security (WIFS), pp. 1\u20137. IEEE (2018)","DOI":"10.1109\/WIFS.2018.8630787"},{"key":"9_CR35","doi-asserted-by":"crossref","unstructured":"G\u00fcera, D., Delp, E.J.: Deepfake video detection using recurrent neural networks. In: 2018 15th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), pp. 1\u20136. IEEE (2018)","DOI":"10.1109\/AVSS.2018.8639163"},{"key":"9_CR36","doi-asserted-by":"crossref","unstructured":"Laptev, I., Marszalek, M., Schmid, C., Rozenfeld, B.: Learning realistic human actions from movies. In: 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1\u20138. IEEE (2008)","DOI":"10.1109\/CVPR.2008.4587756"},{"key":"9_CR37","doi-asserted-by":"publisher","first-page":"104229","DOI":"10.1016\/j.imavis.2021.104229","volume":"112","author":"RF Mansour","year":"2021","unstructured":"Mansour, R.F., Escorcia-Gutierrez, J., Gamarra, M., Villanueva, J.A., Leal, N.: Intelligent video anomaly detection and classification using faster RCNN with deep reinforcement learning model. Image Vis. Comput. 112, 104229 (2021)","journal-title":"Image Vis. Comput."},{"key":"9_CR38","unstructured":"Faceswap: Deepfakes software for all. https:\/\/github.com\/deepfakes\/faceswap"},{"key":"9_CR39","unstructured":"FakeApp 2.2.0. https:\/\/www.malavida.com\/en\/soft\/fakeapp\/"},{"key":"9_CR40","doi-asserted-by":"crossref","unstructured":"Karras, T., Laine, S., Aila, T.: A style-based generator architecture for generative adversarial networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4401\u20134410 (2019)","DOI":"10.1109\/CVPR.2019.00453"},{"key":"9_CR41","unstructured":"Faceswap-GAN. https:\/\/github.com\/shaoanlu\/faceswap-GAN"},{"key":"9_CR42","unstructured":"CycleGAN. https:\/\/github.com\/junyanz\/pytorchCycleGAN-and-pix2pix"},{"key":"9_CR43","unstructured":"GAN Architecture. https:\/\/medium.com\/@Packt_Pub\/inside-the-generative-adversarial-networks-gan-architecture-2435afbd6b3b. Accessed 12 Feb 2022"},{"key":"9_CR44","doi-asserted-by":"crossref","unstructured":"Wolf, L., Hassner, T., Maoz, I.: Face recognition in unconstrained videos with matched background similarity. In: CVPR 2011, pp. 529\u2013534. IEEE (2011)","DOI":"10.1109\/CVPR.2011.5995566"},{"key":"9_CR45","unstructured":"YouTube Faces Dataset with Facial Key points. https:\/\/www.kaggle.com\/selfishgene\/youtube-faces-with-facial-keypoints"}],"container-title":["Lecture Notes in Networks and Systems","Intelligent Systems and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-16078-3_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:21:15Z","timestamp":1661991675000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-16078-3_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,1]]},"ISBN":["9783031160776","9783031160783"],"references-count":45,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-16078-3_9","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"value":"2367-3370","type":"print"},{"value":"2367-3389","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,1]]},"assertion":[{"value":"1 September 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IntelliSys","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Proceedings of SAI Intelligent Systems Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Amsterdam","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"The Netherlands","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 September 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 September 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"intellisys2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/saiconference.com\/IntelliSys","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}