@inproceedings{59f8dba87da748c4a06fb534fcb92105,
title = "Detection of Deep-Morphed Deepfake Images to Make Robust Automatic Facial Recognition Systems",
abstract = "Face Morphing has emerged as a pervasive attack of Facial Recognition Systems. The rapid growth of Generative Adversarial Networks takes it to a complete new level. Deepfake or deep neural network based face morphing, a.k.a deep-morph attack, presents a significant threat to Facial Recognition System. In this paper, we propose a novel Convolutional Neural Network based detection method of deep morphed deepfake images which is suitable for IoT environments in smart cities. A high accuracy of 94.83\% has been achieved for the DeepfakeTIMIT HQ dataset. This lightweight and fast network is a natural choice for IoT environments.",
keywords = "Convolutional Neural Network, Deep Learning, Deep-fake, Deep-Morph, Facial recognition System, Smart City",
author = "Alakananda Mitra and Mohanty, \{Saraju P.\} and Peter Corcoran and Elias Kougianos",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 19th Orissa Information Technology Society International Conference on Information Technology, OCIT 2021 ; Conference date: 16-12-2021 Through 18-12-2021",
year = "2021",
doi = "10.1109/OCIT53463.2021.00039",
language = "English",
series = "Proceedings - 2021 19th OITS International Conference on Information Technology, OCIT 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "149--154",
booktitle = "Proceedings - 2021 19th OITS International Conference on Information Technology, OCIT 2021",
}
