基于猫雀优化LSTM分类器的网络钓鱼检测模型

IF 1.1 4区计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

International Journal of Sensor Networks Pub Date : 2023-01-01 DOI:10.1504/ijsnet.2023.133249

Mohd Shoaib, Mohammad Sarosh Umar

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Phishing detection model using feline finch optimisation-based LSTM classifier

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

International Journal of Sensor Networks COMPUTER SCIENCE, INFORMATION SYSTEMS-TELECOMMUNICATIONS

CiteScore

2.40

自引率

27.30%

发文量

期刊介绍： IJSNet proposes and fosters discussion on and dissemination of issues related to research and applications of distributed and wireless/wired sensor and actuator networks. Sensor networks is an interdisciplinary field including many fields such as wireless networks and communications, protocols, distributed algorithms, signal processing, embedded systems, and information management. Topics covered include: -Energy efficiency, energy efficient protocols- Applications- Location techniques, routing, medium access control- Coverage, connectivity, longevity, scheduling, synchronisation- Network resource management, network protocols, lightweight protocols- Fault tolerance/diagnostics- Foundations- Data storage, query processing, system architectures, operating systems- In-network processing and aggregation- Learning of models from data- Mobility- Performance analysis- Sensor tasking and control- Security, privacy, data integrity- Modelling of systems/physical environments, simulation tools/environments.