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Publication Type : Conference Paper
Publisher : 2020 6th Conference on Data Science and Machine Learning Applications (CDMA)
Source : 2020 6th Conference on Data Science and Machine Learning Applications (CDMA) (2020)
Keywords : convolutional neural nets, Convolutional neural network, Cost-sensitive learning, Cyber security, DCNN models, Deep convolutional neural network, Deep learning, deep learning approaches, Feature extraction, image classification, Image spam, image spam classification, learning (artificial intelligence), Machine learning, pre-trained ImageNet architectures, spam emails, Symantec monthly threat report, text analysis, text-based spam filters, Texture features, Transfer learning, transfer learning-based pre-trained CNN models, unsolicited e-mail
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking
Department : Center for Computational Engineering and Networking (CEN), Electronics and Communication
Year : 2020
Abstract : With the tremendous growth of the internet, cyberspace is facing several threats from the attackers. Threats like spam emails account for 55% of total emails according to the Symantec monthly threat report. Over time, the attackers moved on to image spam to evade the text-based spam filters. To deal with this, the researchers have several machine learning and deep learning approaches that use various features like metadata, color, shape, texture features. But the Deep Convolutional Neural Network (DCNN) and transfer learning-based pre-trained CNN models are not explored much for Image spam classification. Therefore, in this work, 2 DCNN models along with few pre-trained ImageNet architectures like VGG19, Xception are trained on 3 different datasets. The effect of employing a Cost-sensitive learning approach to handle data imbalance is also studied. Some of the proposed models in this work achieves an accuracy up to 99% with zero false positive rate in best case.
Cite this Research Publication : S. Srinivasan, Ravi, V., V, S., Krichen, M., Ben Noureddine, D., Anivilla, S., and Dr. Soman K. P., “Deep Convolutional Neural Network Based Image Spam Classification”, in 2020 6th Conference on Data Science and Machine Learning Applications (CDMA), 2020.