TY  - JOUR
AU  - Ch Yamini1
AU  - G Jamuna Rani
AU  - Vadlamudi Chandana Sri
AU  - P Nithin Reddy
AU  - R Durga Mallikarjun
PY  - 2025
DA  - 2025/06/27
TI  - Machine learning Ensemble Methods for Detection of Phishing in Website
JO  - Global Journal of Engineering Innovations and Interdisciplinary Research
VL  - 5
IS  - 4
AB  - In this research article, we propose to use a learning method with combinations such as the competitive
random forest algorithm and the cloud gradient boosting and algorithm to efficiently and accurately
identify customers who follow phishing websites. Phishing is one of the biggest cybercrimes in today's
digital world. The attackers attempt to Obtain victims’ credentials, account information, and other
sensitive information by impersonating existing and generally trusted individuals or organizations are
visible and similar to phishing websites. On real websites. Online commerce has also grown to increase
the number of phishing scams. Network Security is the most difficult task to achieve, and development.
Automated systems are in place for phishing website detection. Need machine learning is one of the best
solutions for this situation because it can provide the correct classification system as well as check the
status of phishing strategies.
SN  - 3066-1226
UR  - https://dx.doi.org/10.33425/3066-1226.1133
DO  - 10.33425/3066-1226.1133