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Research Article

Facial expression recognition: a novel approach to captcha design

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Pages 921-943 | Received 19 Oct 2023, Accepted 24 Feb 2024, Published online: 11 Mar 2024

References

  • Ahmad, A. S. E., J. Yan, and M. Tayara. 2011. The Robustness of Google Captchas. Technical report. NewcastleUniversity.
  • Baird, H., and K. Popat. 2002. “Human Interactive Proofs and Document Image Analysis.” In Proc of the 5th Workshop on Document Analysis System V, 507–518. Berlin: Springer.
  • Bakariya, B., A. Singh, H. Singh, P. Raju, and R. Rajpoot. 2023. “Facial Emotion Recognition and Music Recommendation System Using CNN-Based Deep Learning Techniques.” Evolving Systems 14: 1–18.
  • Brodić, D., S. Petrovska, M. Jevtić, and Z. N. Milivojević. 2016. “The Influence of the CAPTCHA Types to its Solving Times.” In 2016 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), 1274–1277. IEEE.
  • Bursztein, E., M. Martin, and J. Mitchell. 2011. “Text-Based Captcha Strengths and Weaknesses.” Proc. of the 18th ACM Conference on Computer and Communications Security (ACM CCS), 125–138.
  • Chew, M., and H. S. Baird. 2003. “BaffleText: A Human Interactive Proof.” Proc. 10th SPIE/IS & T Document Recognition and Retrieval Conf. (DRR2003), January 23–24.
  • Coates, A. L., R. J. Fateman, and H. S. Baird. 2001. “Pessimal Print: A Reverse Turing Test.” Proceeding of the 6th International Conference on Document Analysis and Recognition, 1154–1158.
  • Elson, J., J. R. Douceur, J. Howell, and J. Saul. 2007. “Asirra: A CAPTCHA That Exploits Interest-Aligned Manual Image Categorization.” Proceedings of the 14th ACM Conference on Computer and Communications Security, 366–374.
  • Gao, H., H. Liu, D. Yao, X. Liu, and U. Aickelin. 2010. “An Audio CAPTCHA to Distinguish Humans from Computers.” 2010 third International Symposium on Electronic Commerce and Security, 265–269. https://doi.org/10.1109/ISECS.2010.65.
  • Gao, H., W. Wang, J. Qi, X. Wang, X. Liu, and J. Yan. 2013. “The Robustness of Hollow CAPTCHAs.” In Proceedings of the 2013 ACM SIGSAC Conference on Computer &Communications Security, 1075–1086. ACM.
  • Gossweiler, R., M. Kamvar, and S. Baluja. 2009. “What's up CAPTCHA? A CAPTCHA Based on Image Orientation.” In Proceedings of the 18th International Conference on World Wide web, 841–850.
  • Goswami, G., B. M. Powell, M. Vatsa, R. Singh, and A. Noore. 2014. “FR-CAPTCHA: CAPTCHA Based on Recognizing Human Faces.” PLoS One 9 (4): e91708. https://doi.org/10.1371/journal.pone.0091708
  • Goswami, G., R. Singh, M. Vatsa, B. Powell, and A. Noore. 2012. “Face Recognition CAPTCHA.” In 2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS), 412–417. https://doi.org/10.1109/BTAS.2012.6374608.
  • Hu, Y., L. Chen, and J. Cheng. 2018. “A CAPTCHA Recognition Technology Based on Deep Learning.” IEEE Conference on Industrial Electronics and Applications.
  • Jiang, Xingxun, Yuan Zong, Wenming Zheng, Chuangao Tang, Wanchuang Xia, Cheng Lu, and Jiateng Liu. 2020. “Dfew: A Large-Scale Database for Recognizing Dynamic Facial Expressions in the Wild.” In Proceedings of the 28th ACM International Conference on Multimedia, 2881–2889.
  • Miyuki Kamachi, Michael Lyons, and Jiro Gyoba. 1997. “The Japanese Female Facial Expression (jaffe) database.” http://www.kasrl.org/jaffe.html.
  • Kaur, K., and S. Behal. 2014. “Captcha and its Techniques: A Review.” International Journal of Computer Science and Information Technologies 5 (5): 6341–6344.
  • Kim, J. W., W. K. Chung, and H. G. Cho. 2010. “A New Image-Based CAPTCHA Using the Orientation of The Polygonally Cropped sub-Images.” The Visual Computer 26 (6-8): 1135–1143. https://doi.org/10.1007/s00371-010-0469-3
  • Kollias, Dimitrios, Irene Kotsia, Elnar Hajiyev, and Stefanos Zafeiriou. 2021. “Analysing Affective Behavior in the Second abaw2 Competition.” arXiv preprint arXiv:2106.15318.
  • Korayem, M., A. A. Mohamed, D. Crandall, and R. V. Yampolskiy. 2012. “Learning Visual Features for the Avatar Captcha Recognition Challenge.” In Vol. 2 of 2012 11th International Conference on Machine Learning and Applications, 584–587. IEEE.
  • Kumar, M., M. K. Jindal, and M. Kumar. 2022. “A Systematic Survey on CAPTCHA Recognition: Types, Creation and Breaking Techniques.” Archives of Computational Methods in Engineering 28.
  • Lillibridge, M. D., M. Abadi, K. Bharat, and A. Z. Broder. 2001. U.S. Patent No. 6,195,698. Washington, DC: U.S. Patent and Trademark Office.
  • Meena, G., and K. K. Mohbey. 2023. “Sentiment Analysis on Images Using Different Transfer Learning Models.” Procedia Computer Science 218: 1640–1649. https://doi.org/10.1016/j.procs.2023.01.142
  • Meena, G., K. K. Mohbey, A. Indian, and M. Z. Khan. 2023. “Identifying Emotions from Facial Expressions Using a Deep Convolutional Neural Network-Based Approach.” Multimedia Tools and Applications 82: 1–22.
  • Meena, G., K. K. Mohbey, and S. Kumar. 2023. “Sentiment Analysis on Images Using Convolutional Neural Networks Based Inception-V3 Transfer Learning Approach.” International Journal of Information Management Data Insights 3 (1): 100174. https://doi.org/10.1016/j.jjimei.2023.100174
  • Meena, G., K. K. Mohbey, S. Kumar, and R. K. Chawda. 2023. “Image-Based Sentiment Analysis Using InceptionV3 Transfer Learning Approach.” SN Computer Science 4 (3): 242. https://doi.org/10.1007/s42979-023-01695-3
  • Mollahosseini, Ali, Behzad Hasani, and Mohammad H Mahoor. 2017. “Affectnet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild.” IEEE Transactions on Affective Computing 10 (1): 18–31. https://doi.org/10.1109/TAFFC.2017.2740923
  • Moradi, M., and M. R. Keyvanpour. 2020. “A Novel CAPTCHA Scheme Based on Facial Expression Reconstruction.” International Journal of Electronic Business 15 (4): 368–388. https://doi.org/10.1504/IJEB.2020.111061
  • Parkhi, O. M., A. Vedaldi, A. Zisserman, and C. V. Jawahar. 2012. “Cats and Dogs.” In 2012 IEEE Conference on Computer Vision and Pattern Recognition, 3498–3505. IEEE.
  • Pope, C., and K. Kaur. 2005. “Is It Human or Computer? Defending E-Commerce with Captchas.” IT Professional 7 (2): 43–49. https://doi.org/10.1109/MITP.2005.37
  • Raavi, R., M. Alqarni, and P. C. K. Hung. 2022. Implementation of Machine Learning for CAPTCHAs Authentication Using Facial Recognition. Piscataway, NJ: IEEE.
  • Ray, P., D. Giri, S. Kumar, and P. Sahoo. 2020. “FP-Captcha: An Improved Captcha Design Scheme Based on Face Points.” In Recent Advances in Intelligent Information Systems and Applied Mathematics. Vol. 863, edited by O. Castillo, D. Jana, D. Giri, and A. Ahmed, 218–233. Haldia Institute of Technology, India: ICITAM 2019.
  • Romero-Herrera, R., M. O. Marín, et al. 2021. “Public and Automated Functional Testing (Captcha) with Animations Based on Facial Expressions.” Journal of Theoretical and Applied Information Technology 99 (15): 3881–3891.
  • Rui, Y., and Z. Liu. 2003. “Artifacial: Automated Reverse Turing Test Using Facial Features.” In Proceedings of the Eleventh ACM International Conference on Multimedia, 295–298.
  • Sauer, G., H. Hochheiser, J. Feng, and J. Lazar. 2008. “Towards a Universally Usable CAPTCHA.” Proceedings of the Symposium on Accessible Privacy and Security ACM Symposium on Usable Privacy and security (SOUPS'08).
  • Selvaraju, Ramprasaath R, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra. 2017. “Grad-cam: Visual Explanations from Deep Networks via Gradient-Based Localization.” In Proceedings of the IEEE International Conference on Computer Vision, 618–626.
  • Tam, J., J. Simsa, S. Hyde, and L. Von Ahn. 2008. “Breaking Audio CAPTCHAs.” Advances in Neural Information Processing Systems. https://proceedings.neurips.cc/paper/2008.
  • Tang, M., H. Gao, Y. Zhang, Y. Liu, P. Zhang, and P. Wang. 2018. “Research on Deep Learning Techniques InBreaking Text-Based Captchas and Designing Image-Based Captcha.” IEEE Transactions on Information Forensics and Security 99: 1556–6013.
  • United Nations. 2020. “World Population Aging 2019”. https://www.un.org/en/development/desa/population/publications/pdf/ageing/WorldPopulationAgeing2019-Report.pdf.
  • Von Ahn, L., M. Blum, N. J. Hopper, and J. Langford. 2003. “CAPTCHA: Using Hard AI Problems for Security.” In Vol. 2656 of Eurocrypt, 294–311.
  • Von Ahn, L., M. Blum, and J. Langford. 2004. “Telling Human and Computers Apart Automatically.” Communications of the ACM 47 (2): 56–60. https://doi.org/10.1145/966389.966390
  • Yamamoto, T., J. D. Tygar, and M. Nishigaki. 2010. “CAPTCHA Using Strangeness in Machine Translation.” In 2010 24th IEEE International Conference on Advanced Information Networking and Applications, 430–437. Doi:10.1109/AINA.2010.55. >
  • Yan, J., and A. S. El Ahmad. 2008. “A Low-Cost Attack on a Microsoft CAPTCHA.” In Proceedings Ofthe 15th ACM Conference on Computer and Communications Security, 543–554. ACM.
  • Zafeiriou, Stefanos, Dimitrios Kollias, Mihalis A Nicolaou, Athanasios Papaioannou, Guoying Zhao, and Irene Kotsia. 2017. “Aff-wild: Valence and Arousal ‘in-the-Wild’challenge.” In Computer Vision and Pattern Recognition Workshops (CVPRW), 2017 IEEE Conference on, 1980–1987. IEEE.
  • Zhang, Y., H. Gao, G. Pei, S. Luo, G. Chang, and N. Cheng. 2019. “A Survey of Research on CAPTCHA Designing and Breaking Techniques.” 2019 18th IEEE International Conference On Trust, Security and Privacy In Computing and Communications/13th IEEE International Conference On Big Data Science and Engineering (TrustCom/BigDataSE), Rotorua, New Zealand, 75–84. https://doi.org/10.1109/TrustCom/BigDataSE.2019.00020.
  • Zhang, Zheng, Jeff M Girard, Yue Wu, PengLiu Xing Zhang, Umur Ciftci, Shaun Canavan, AndyHorowitz Michael Reale, Huiyuan Yang, et al. 2016. “Multimodal Spontaneous Emotion Corpus for Human Behavior Analysis.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 3438–3446.
  • Zhang, Wei, Xianpeng Ji, Keyu Chen, Yu Ding, and Changjie Fan. 2021. “Learning a Facial Expression Embedding Disentangled from Identity.” In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 6759–6768.
  • Zhang, X., X. Liu, T. Sarkodie-Gyan, and Z. Li. 2021b. “Development of a Character CAPTCHA Recognition System for the Visually Impaired Community Using Deep Learning.” Machine Vision and Applications 32: 1–19.
  • Zhang, Xing, Lijun Yin, Jeffrey F Cohn, Shaun Canavan, Michael Reale, Andy Horowitz, Peng Liu, and Jeffrey M Girard. 2014. “Bp4d-spontaneous: A High-Resolution Spontaneous 3d Dynamic Facial Expression Database.” Image and Vision Computing 32 (10): 692–706. https://doi.org/10.1016/j.imavis.2014.06.002
  • Zhu, B. B., J. Yan, Q. Li, C. Yang, J. Liu, N. Xu, and K. Cai. 2010. “Attacks and Design of Image Recognition CAPTCHAs.” In Proceedings of the 17th ACM Conference on Computer and Communications Security, 187–200.

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