Publication Type : Journal Article
Publisher : arXiv preprint arXiv:1810.03977 .
Source : arXiv preprint arXiv:1810.03977 (2018)
Url : https://arxiv.org/abs/1810.03977
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking
Department : Electronics and Communication
Year : 2018
Abstract : Hackers and spammers are employing innovative and novel techniques to deceive novice and even knowledgeable internet users. Image spam is one of such technique where the spammer varies and changes some portion of the image such that it is indistinguishable from the original image fooling the users. This paper proposes a deep learning based approach for image spam detection using the convolutional neural networks which uses a dataset with 810 natural images and 928 spam images for classification achieving an accuracy of 91.7% outperforming the existing image processing and machine learning techniques
Cite this Research Publication : A. Dinesh Kumar, R, V., and Dr. Soman K. P., “Deepimagespam: Deep learning based image spam detection”, arXiv preprint arXiv:1810.03977, 2018.