This paper presents a web intrusion detection system that addresses security threats with the increasing use of web applications in almost all domains.
A web intrusion detection system that addresses security threats with the increasing use of web applications in almost all domains, as well as the increase ...
Our web intrusion detection system uses a Distil-BERT, RNN, and LSTM model to identify attacks with body, URL, and User-data.
This project proposes to train the BERT masked language model (MLM) for advanced phishing detection, through a process known as Finetuning.
Jul 19, 2023 · In this study, we employ a Transformer called Bidirectional Encoder Representations (BERT) and several machine learning techniques (CNN, SVM, Random Forest, ...
In summary, this is the first study in the literature which shows that BERT can be successfully utilised for web attack detection with high accuracy.
Jul 31, 2024 · Bert Network Packet Flow Header Payload is a machine learning model designed for detecting intrusions in computer networks.
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How to use BERT model for prediction?
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Feb 8, 2024 · BERT has been utilized in various fields, from detecting log anomalies to identifying malicious web requests. A noteworthy study by Alkhatib et ...
Oct 26, 2024 · In 202215, Seyyar et al. integrated the pre-trained BERT model with machine learning methods, achieving positive results in injection attack ...
Reference [24] adopts the Transformer-based BERT model to learn word features for URL semantic analysis, and uses a CNN model to classify suspicious URLs.