TY - JOUR
T1 - WillRo
T2 - A Deep Learning App for Potential Phishing Threat Detection
AU - Sotelo, Willy
AU - Roque, Alvaro
AU - Wong-Durand, Sandra
AU - Castaneda, Pedro
AU - Onate-Andino, Alejandra
N1 - Publisher Copyright:
© (c) by the authors
PY - 2025/12/8
Y1 - 2025/12/8
N2 - This article presents an application called WillRo App, designed to detect potential phishing by analyzing website screenshots in real time. The system integrated Robotic Process Automation (RPA) to capture screenshots, and the YOLOv5 deep learning model in order to classify phishing and no-phishing content. The results demonstrated a precision of 85.80%, a recall of 93.00%, a [email protected] of 66.60%, and a [email protected] -0.95 of 32.70%. These values showed a reliable detection performance, making WillRo a possible model for phishing detection. Future work should focus on improving the model with additional features to increase its accuracy.
AB - This article presents an application called WillRo App, designed to detect potential phishing by analyzing website screenshots in real time. The system integrated Robotic Process Automation (RPA) to capture screenshots, and the YOLOv5 deep learning model in order to classify phishing and no-phishing content. The results demonstrated a precision of 85.80%, a recall of 93.00%, a [email protected] of 66.60%, and a [email protected] -0.95 of 32.70%. These values showed a reliable detection performance, making WillRo a possible model for phishing detection. Future work should focus on improving the model with additional features to increase its accuracy.
KW - deep learning
KW - malicious content
KW - phishing detection
KW - Robotic Process Automation (RPA)
UR - https://www.scopus.com/pages/publications/105026864829
U2 - 10.48084/etasr.14161
DO - 10.48084/etasr.14161
M3 - Artículo
AN - SCOPUS:105026864829
SN - 2241-4487
VL - 15
SP - 30591
EP - 30598
JO - Engineering, Technology and Applied Science Research
JF - Engineering, Technology and Applied Science Research
IS - 6
ER -