A PKI-integrated cryptographic framework for deepfake detection via facial micro-expression analysis
Surbhi Sharmasurbhi.sharma@jaipur.manipal.eduDepartment of Computer Science and Engineering Manipal University JaipurDepartment of Computer Science and Engineering Manipal University JaipurJaipur, Rajasthan, 303007, IndiaView full profile → , Priti Sharmapritisharma@ndimdelhi.inNew Delhi Institute of Management NCT of Delhi New Delhi, 110062, IndiaView full profile → , Surabhi Shankersurabhi.shanker@krmangalam.edu.inCentre of Excellence - Cyber Security School of Engineering and Technology K R Mangalam UniversityCentre of Excellence-Cyber Security, School of Engineering and Technology K. R. Mangalam UniversityGurugram, Haryana, 122103, IndiaView full profile → , Parimala Veluvalidirector_ssodl@siu.edu.inSymbiosis School for Online and Digital Learning Symbiosis International (Deemed University)Pune, Maharashtra, 411036, IndiaView full profile → , *Sushama TanwarCorresponding authorsushama.tanwar@jaipur.manipal.eduDepartment of Computer Science and Engineering Manipal University JaipurDepartment of Computer Science and Engineering Manipal University JaipurJaipur, Rajasthan, 303007, IndiaView full profile → , Prashant Vatsprashant.vats@jaipur.manipal.eduDepartment of Computer Science and Engineering Manipal University JaipurDepartment of Computer Science & Engineering Manipal University JaipurJaipur, Rajasthan, 303007, IndiaView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 08 Jul 2025
- Published Online:
- 08 Dec 2025
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JDMSC-2586
- Pages:
- 3101–3109
Abstract
Keywords
Subject Classifications
References
[1] D. Afchar, V. Nozick, J. Yamagishi, and I. Echizen, “Mesonet: A compact facial video forgery detection network,” in Proc. IEEE Int. Workshop Inf. Forensics Security (WIFS) (2018).
[2] I. Ahmed, M. Ahmad, J. J. Rodrigues, and G. Jeon, “Edge computing-based person detection system for top view surveillance: Using CenterNet with transfer learning,” Appl. Soft Comput., vol. 107, pp. 107489 (2021).
[3] Z. Akhtar, M. R. Mouree, and D. Dasgupta, “Utility of deep learning features for facial attributes manipulation detection,” in Proc. IEEE Int. Conf. Humanized Comput. Commun. Artif. Intell. (HCCAI) (2020).
[4] M. Albahar and J. Almalki, “Deepfakes: Threats and countermeasures systematic review,” J. Theor. Appl. Inf. Technol., vol. 97, no. 22, pp. 3242–3250 (2019).
[5] L. Aversano, M. L. Bernardi, M. Cimitile, and R. Pecori, “A systematic review on deep learning approaches for IoT security,” Comput. Sci. Rev., vol. 40, pp. 100389 (2021).
[6] T. Balaji, C. S. R. Annavarapu, and A. Bablani, “Machine learning algorithms for social media analysis: A survey,” Comput. Sci. Rev., vol. 40, pp. 100395 (2021).
[7] M. Baygin, O. Yaman, N. Baygin, and M. Karakose, “A blockchain-based approach to smart cargo transportation using UHF RFID,” Expert Syst. Appl., vol. 188, pp. 116030 (2022).
[8] B. Bekci, Z. Akhtar, and H. K. Ekenel, “Cross-dataset face manipulation detection,” in Proc. 28th Signal Process. Commun. Appl. Conf. (SIU) (2020).
[9] A. Biswas, D. Bhattacharya, and A. K. Kakelli, “DeepFake detection using 3D-Xception net with discrete Fourier transformation,” J. Inf. Syst. Telecommun., vol. 3, no. 35, pp. 161–168 (2021).
[10] N. Bonettini, E. D. Cannas, S. Mandelli, L. Bondi, P. Bestagini, and S. Tubaro, “Video face manipulation detection through ensemble of CNNs,” in Proc. 25th Int. Conf. Pattern Recognit. (ICPR) (2020).
[11] P. Sagar, V. Ghanimi, H. M. A. Ghanimi, L. A. J. Prabhu, L. Raja, P. Dadheech, and S. Sengan, “Secure multi-party computation in deep learning: Enhancing privacy in distributed neural networks,” J. Discrete Math. Sci. Cryptogr., vol. 27, no. 2-A, pp. 249–259 (2024), doi: 10.47974/JDMSC-1879.
[12] R. J. Krishna, T. Gopalakrishnan, M. Divyapushpalakshmi, K. Amarendra, P. Dadheech, and S. Sengan, “Security and privacy concerns in social networks mathematically modified metaheuristic-based approach,” J. Discrete Math. Sci. Cryptogr., vol. 27, no. 2-A, pp. 371–382 (2024), doi: 10.47974/JDMSC-1892.
[13] P. Pareek, S. Yadav, and S. S. Choudhary, “Addressing applications and security issues in the Internet of Things (IoT): A comprehensive review,” J. Discrete Math. Sci. Cryptogr., vol. 27, no. 7, pp. 1977–1989 (2024), doi: 10.47974/JDMSC-2073.
[14] A. K. Saini, M. L. Saini, D. K. Srivastava, S. Singh, P. Vats, and T. K. Tak, “Secure communication framework using lattice-based encryption and image steganography,” J. Discrete Math. Sci. Cryptogr., vol. 28, no. 5-B, pp. 1855–1864 (2025), doi: 10.47974/JDMSC-2418.
[15] B. L. V. S. Aditya and S. N. Mohanty, “Design of an efficient model for fake profile detection on social media using advanced feature engineering and deep learning techniques,” J. Inf. Optim. Sci., vol. 46, no. 6, pp. 1803–1810 (2025), doi: 10.47974/JIOS-2009.
[16] S. D. Bahinipati and B. K. Pattanayak, “A novel blockchain enabled smart contract for smart city e-governance ecosystem,” J. Inf. Optim. Sci., vol. 46, no. 6, pp. 1831–1840 (2025), doi: 10.47974/JIOS-2012.
[17] Z. S. Alsham, E. Bahçekapılı, and A. Ayaz, “Trends in IoT applications in smart campuses: A topic modeling approach,” COLLNET J. Scientometrics Inf. Manage., vol. 19, no. 1, pp. 21–40 (2025), doi: 10.47974/CJSIM-2024-017.
[18] W. Sripanya, W. Rungrottheera, and P. Hyunsin, “Fourier series analysis and computation based on function characteristics,” J. Interdiscip. Math., vol. 28, no. 6, pp. 2109–2120 (2025), doi: 10.47974/JIM-2352.




