A Deep Learning Model with Hierarchical LSTMs and Supervised Attention for Anti-Phishing [article]

Minh Nguyen, Toan Nguyen, Thien Huu Nguyen
2018 arXiv   pre-print
Anti-phishing aims to detect phishing content/documents in a pool of textual data. This is an important problem in cybersecurity that can help to guard users from fraudulent information. Natural language processing (NLP) offers a natural solution for this problem as it is capable of analyzing the textual content to perform intelligent recognition. In this work, we investigate state-of-the-art techniques for text categorization in NLP to address the problem of anti-phishing for emails (i.e,
more » ... cting if an email is phishing or not). These techniques are based on deep learning models that have attracted much attention from the community recently. In particular, we present a framework with hierarchical long short-term memory networks (H-LSTMs) and attention mechanisms to model the emails simultaneously at the word and the sentence level. Our expectation is to produce an effective model for anti-phishing and demonstrate the effectiveness of deep learning for problems in cybersecurity.
arXiv:1805.01554v1 fatcat:d25stxadzfbmfjkvw234gim4ia