Webb5 aug. 2024 · In order to download the ready-to-use phishing detection Python environment, you will need to create an ActiveState Platform account. Just use your GitHub credentials or your email address to register. Signing up is easy and it unlocks the ActiveState Platform’s many benefits for you! WebbIn this study, our innovations and contributions are as follows: (1) This paper proposes a malicious URL detection model based on a DCNN. The dynamic convolution algorithm adds a new folding layer to the original multilayer convolution structure. It replaces the pooling layer with the k-max-pooling layer.
phishing-detection · GitHub Topics · GitHub
WebbPhishing Website Detection by Machine Learning Techniques. 1. Objective: A phishing website is a common social engineering method that mimics trustful uniform resource locators (URLs) and webpages. The objective of this project is to train machine learning models and deep neural nets on the dataset created to predict phishing websites. WebbPhishers use the websites which are visually and semantically similar to those real websites. So, we develop this website to come to know user whether the URL is phishing … ching yeh pork
A Malicious URL Detection Model Based on Convolutional Neural …
WebbThis empirical study built four phishing detection models using four different DL algorithms: DNN, CNN, LSTM, and GRU. The general architecture of a typical DL-based … Webb1 sep. 2024 · We compare three deep learning networks, i.e., CNN-LSTM, single CNN and single LSTM, with our method (self-attention CNN) in phishing detection. CNN-LSTM is … Webb20 sep. 2024 · Phishers try to deceive their victims by social engineering or creating mock-up websites to steal information such as account ID, username, password from … ching yeh lin