Advanced BERT and CNN-Based Computational Model for Phishing Detection in Enterprise Systems  

作　　者：Brij B.Gupta Akshat Gaurav Varsha Arya Razaz Waheeb Attar Shavi Bansal Ahmed Alhomoud Kwok Tai Chui 

机构地区：[1]Department of Computer Science and Information Engineering,Asia University,Taichung,413,Taiwan [2]Symbiosis Centre for Information Technology(SCIT),Symbiosis International University,Pune,411057,India [3]Center for Interdisciplinary Research,University of Petroleum and Energy Studies(UPES),Dehradun,248007,India [4]University Centre for Research and Development(UCRD),Chandigarh University,Chandigarh,140413,India [5]Computer Engineering,Ronin Institute,Montclair,NJ 07043,USA [6]Department of Business Administration,Asia University,Taichung,413,Taiwan [7]Department of Electrical and Computer Engineering,Lebanese American University,Beirut,1102,Lebanon [8]College of Business Administration,Management Department,Princess Nourah bint Abdulrahman University,Riyadh,11671,Saudi Arabia [9]Department of Research and Innovation,Insights2Techinfo,Jaipur,302001,India [10]Department of Computer Sciences,Faculty of Computing and Information Technology,Northern Border University,Rafha,91911,Saudi Arabia [11]Department of Electronic Engineering and Computer Science,Hong Kong Metropolitan University(HKMU),Hong Kong,518031,China

出　　处：《Computer Modeling in Engineering & Sciences》2024年第12期2165-2183,共19页工程与科学中的计算机建模（英文）

基　　金：supported by a grant from Hong Kong Metropolitan University (RD/2023/2.3);supported Princess Nourah bint Abdulrah-man University Researchers Supporting Project number (PNURSP2024R 343);Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia;the Deanship of Scientific Research at Northern Border University,Arar,Kingdom of Saudi Arabia for funding this research work through the project number“NBU-FFR-2024-1092-09”.

摘　　要：Phishing attacks present a serious threat to enterprise systems,requiring advanced detection techniques to protect sensitive data.This study introduces a phishing email detection framework that combines Bidirectional Encoder Representations from Transformers(BERT)for feature extraction and CNN for classification,specifically designed for enterprise information systems.BERT’s linguistic capabilities are used to extract key features from email content,which are then processed by a convolutional neural network(CNN)model optimized for phishing detection.Achieving an accuracy of 97.5%,our proposed model demonstrates strong proficiency in identifying phishing emails.This approach represents a significant advancement in applying deep learning to cybersecurity,setting a new benchmark for email security by effectively addressing the increasing complexity of phishing attacks.

关 键 词：PHISHING BERT convolutional neural networks email security deep learning 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]