Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Deep fake detection using cascaded deep sparse auto-encoder for effective feature selection Subject The topic of the resource Deep fake detection; Deep learning; Deep sparse auto encoder; Dnn; Face2face; Faceforensics++; Faceswap; Temporal convolutional neural network Description An account of the resource In the recent research era, artificial intelligence techniques have been used for computer vision, big data analysis, and detection systems. The development of these advanced technologies has also increased security and privacy issues. One kind of this issue is Deepfakes which is the combined word of deep learning and fake. DeepFake refers to the formation of a fake image or video using artificial intelligence approaches which are created for political abuse, fake data transfer, and pornography. This paper has developed a Deepfake detection method by examining the computer vision features of the digital content. The computer vision features based on the frame change are extracted using a proposed deep learning model called the Cascaded Deep Sparse Auto Encoder (CDSAE) trained by temporal CNN. The detection process is performed using a Deep Neural Network (DNN) to classify the deep fake image/video from the real image/video. The proposed model is implemented using Face2Face, FaceSwap, and DFDC datasets which have secured an improved detection rate when compared to the traditional deep fake detection approaches. 2022. Balasubramanian et al. Creator An entity primarily responsible for making the resource Balasubramanian S.B.; Kannan R.J.; Prabu P.; Venkatachalam K.; TrojovskP. Source A related resource from which the described resource is derived PeerJ Computer Science, Vol-8 Publisher An entity responsible for making the resource available PeerJ Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.7717/peerj-cs.1040" target="_blank" rel="noreferrer noopener">https://doi.org/10.7717/peerj-cs.1040</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134509137&amp;doi=10.7717%2Fpeerj-cs.1040&amp;partnerID=40&amp;md5=2778015b0bf532431ca59ed8b77b1464" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134509137&amp;doi=10.7717%2fpeerj-cs.1040&amp;partnerID=40&amp;md5=2778015b0bf532431ca59ed8b77b1464</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access; Green Open Access Relation A related resource ISSN: 23765992 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Balasubramanian S.B., Department of Information Technology, Lebanese French University, Erbil, Iraq; Kannan R.J., School of Computer Science and Engineering, VIT Chennai, Tamilnadu, Chennai, India; Prabu P., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Venkatachalam K., Department of Applied Cybernetics, University of Hradec Krov Hradec Kralove, Czech Republic; TrojovskP., Department of Mathematics, University of Hradec Krov Hradec Kralove, Czech Republic