References
[1]. Ortega O B, Segura J R. Protocolo básico de ciberseguridad para pymes[J]. Interfases, 2022 (016): 168-186.
[2]. Wang C, Chen Y. TCURL: Exploring hybrid transformer and convolutional neural network on phishing URL detection[J]. Knowledge-Based Systems, 2022, 258: 109955.
[3]. Sharif M H U, Mohammed M A. A literature review of financial losses statistics for cyber security and future trend[J]. World Journal of Advanced Research and Reviews, 2022, 15(1): 138-156.
[4]. Gupta B B, Arachchilage N A G, Psannis K E. Defending against phishing attacks: taxonomy of methods, current issues and future directions[J]. Telecommunication Systems, 2018, 67: 247-267.
[5]. Lakshmi V. Beginning Security with Microsoft Technologies[J]. Beginning Security with Microsoft Technologies, 2019.
[6]. Day G. Security in the Digital World: For the home user, parent, consumer and home office[M]. IT Governance Ltd, 2017.
[7]. Dong R, Zhang Y, Zhao J. How green are the streets within the sixth ring road of Beijing? An analysis based on tencent street view pictures and the green view index[J]. International journal of environmental research and public health, 2018, 15(7): 1367.
[8]. Wang L, Guo S, Huang W, et al. Places205-vggnet models for scene recognition[J]. arXiv preprint arXiv:1508.01667, 2015.
[9]. Vecile S, Lacroix K, Grolinger K, et al. Malicious and Benign URL Dataset Generation Using Character-Level LSTM Models[C]//2022 IEEE Conference on Dependable and Secure Computing (DSC). IEEE, 2022: 1-8.
[10]. Ren F, Jiang Z, Liu J. A bi-directional LSTM model with attention for malicious URL detection[C]//2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). IEEE, 2019, 1: 300-305.
[11]. Bozkir A S, Dalgic F C, Aydos M. GramBeddings: A New Neural Network for URL Based Identification of Phishing Web Pages Through N-gram Embeddings[J]. Computers & Security, 2023, 124: 102964.
[12]. Alshingiti Z, Alaqel R, Al-Muhtadi J, et al. A Deep Learning-Based Phishing Detection System Using CNN, LSTM, and LSTM-CNN[J]. Electronics, 2023, 12(1): 232.
[13]. Simonyan K, Zisserman A. Very deep convolutional networks for large-scale image recognition[J]. arXiv preprint arXiv:1409.1556, 2014.
[14]. Li J, Wang D, Zhao C, et al. MUI-VB: Malicious URL Identification Model Combining VGG and Bi-LSTM[C]//Proceedings of the 2022 3rd International Conference on Control, Robotics and Intelligent System. 2022: 141-148.
[15]. Korkmaz M, Kocyigit E, Sahingoz O K, et al. Phishing web page detection using N-gram features extracted from URLs[C]//2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA). IEEE, 2021: 1-6.
[16]. Jolliffe I T, Cadima J. Principal component analysis: a review and recent developments[J]. Philosophical transactions of the royal society A: Mathematical, Physical and Engineering Sciences, 2016, 374(2065): 20150202.
[17]. Maas A L, Hannun A Y, Ng A Y. Rectifier nonlinearities improve neural network acoustic models[C]//Proc. icml. 2013, 30(1): 3.
[18]. Url T. Gesamtwirtschaftliche Auswirkungen der Exportgarantien in Österreich[J]. WIFO Studies, 2016.
[19]. Johnson C, Khadka B, Basnet R B, et al. Towards Detecting and Classifying Malicious URLs Using Deep Learning[J]. J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl., 2020, 11(4): 31-48.
Cite this article
Liu,Q. (2023). Detection of malicious websites across multiple classes using n-gram features and VGG based on URL analysis. Applied and Computational Engineering,18,66-72.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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References
[1]. Ortega O B, Segura J R. Protocolo básico de ciberseguridad para pymes[J]. Interfases, 2022 (016): 168-186.
[2]. Wang C, Chen Y. TCURL: Exploring hybrid transformer and convolutional neural network on phishing URL detection[J]. Knowledge-Based Systems, 2022, 258: 109955.
[3]. Sharif M H U, Mohammed M A. A literature review of financial losses statistics for cyber security and future trend[J]. World Journal of Advanced Research and Reviews, 2022, 15(1): 138-156.
[4]. Gupta B B, Arachchilage N A G, Psannis K E. Defending against phishing attacks: taxonomy of methods, current issues and future directions[J]. Telecommunication Systems, 2018, 67: 247-267.
[5]. Lakshmi V. Beginning Security with Microsoft Technologies[J]. Beginning Security with Microsoft Technologies, 2019.
[6]. Day G. Security in the Digital World: For the home user, parent, consumer and home office[M]. IT Governance Ltd, 2017.
[7]. Dong R, Zhang Y, Zhao J. How green are the streets within the sixth ring road of Beijing? An analysis based on tencent street view pictures and the green view index[J]. International journal of environmental research and public health, 2018, 15(7): 1367.
[8]. Wang L, Guo S, Huang W, et al. Places205-vggnet models for scene recognition[J]. arXiv preprint arXiv:1508.01667, 2015.
[9]. Vecile S, Lacroix K, Grolinger K, et al. Malicious and Benign URL Dataset Generation Using Character-Level LSTM Models[C]//2022 IEEE Conference on Dependable and Secure Computing (DSC). IEEE, 2022: 1-8.
[10]. Ren F, Jiang Z, Liu J. A bi-directional LSTM model with attention for malicious URL detection[C]//2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). IEEE, 2019, 1: 300-305.
[11]. Bozkir A S, Dalgic F C, Aydos M. GramBeddings: A New Neural Network for URL Based Identification of Phishing Web Pages Through N-gram Embeddings[J]. Computers & Security, 2023, 124: 102964.
[12]. Alshingiti Z, Alaqel R, Al-Muhtadi J, et al. A Deep Learning-Based Phishing Detection System Using CNN, LSTM, and LSTM-CNN[J]. Electronics, 2023, 12(1): 232.
[13]. Simonyan K, Zisserman A. Very deep convolutional networks for large-scale image recognition[J]. arXiv preprint arXiv:1409.1556, 2014.
[14]. Li J, Wang D, Zhao C, et al. MUI-VB: Malicious URL Identification Model Combining VGG and Bi-LSTM[C]//Proceedings of the 2022 3rd International Conference on Control, Robotics and Intelligent System. 2022: 141-148.
[15]. Korkmaz M, Kocyigit E, Sahingoz O K, et al. Phishing web page detection using N-gram features extracted from URLs[C]//2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA). IEEE, 2021: 1-6.
[16]. Jolliffe I T, Cadima J. Principal component analysis: a review and recent developments[J]. Philosophical transactions of the royal society A: Mathematical, Physical and Engineering Sciences, 2016, 374(2065): 20150202.
[17]. Maas A L, Hannun A Y, Ng A Y. Rectifier nonlinearities improve neural network acoustic models[C]//Proc. icml. 2013, 30(1): 3.
[18]. Url T. Gesamtwirtschaftliche Auswirkungen der Exportgarantien in Österreich[J]. WIFO Studies, 2016.
[19]. Johnson C, Khadka B, Basnet R B, et al. Towards Detecting and Classifying Malicious URLs Using Deep Learning[J]. J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl., 2020, 11(4): 31-48.