Publication Type : Conference Paper
Publisher : Proceedings of the 1st Anti-Phishing Shared Task Pilot at 4th ACM IWSPA co-located with 8th ACM Conference on Data and Application Security and Privacy
Source : Proceedings of the 1st Anti-Phishing Shared Task Pilot at 4th ACM IWSPA co-located with 8th ACM Conference on Data and Application Security and Privacy (CODASPY 2018), Tempe, Arizona, USA (2018)
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking
Department : Electronics and Communication
Year : 2018
Abstract : Email communication, has now become an inevitable communication tool in our daily life. Especially for finance sector, communication through email plays an important role in their businesses. So, it is very important to classify emails based on their behavior. Email phishing one of most dangerous Internet phenomenon that cause various problems to business class mainly to finance sector. This type of emails steals our valuable information without our permission, more over we won't be aware of such an act even if it has been occurred. In this paper, we reveal about how to distinguish phishing emails from legitimate mails. Dataset had two types of email texts one with header and other without header. We used Keras Word Embedding and Convolutional Neural Network to build our model.
Cite this Research Publication : H. M, Unnithan, N., Ravi, V., and Dr. Soman K. P., “Deep Learning Based Phishing E-mail Detection CEN-Deepspam”, in Proceedings of the 1st Anti-Phishing Shared Task Pilot at 4th ACM IWSPA co-located with 8th ACM Conference on Data and Application Security and Privacy (CODASPY 2018), Tempe, Arizona, USA, 2018.