Spam E-Mail Detection with Smart AI Translate
Hema Sri Potluri, Gopi Mani Kiran Gorantla, Venkata Bhargava Adithya Kothamasu, Arnab De · 2025
These days, email spam has grown to be a significant issue due to the rapid growth of internet users. By distributing malicious links through spam emails, people are taking use of them for phishing attacks, frauds and various other illegal and immoral acts, which can compromise both your system and ours. This paper includes a framework to embrace the growing threat from malicious and spam email. This includes a unique model of Spam and Ham classifier using machine learning algorithms and multilan guage content translation. The system proposed uses a mixture of feature extraction (using Count Vectorization) along with various classification algorithms (K- NN, Lo gistic Regression, SVM, Random Forest, Decision Tree, Naive Bayes). Each model is being evaluated based on their accuracy, precision, recall and F1 score. The further improvement comes in enhanced usability in multilingual contexts: the email content is translated into various languages through a specialized translation module to make it more accessible to a wider range of potential users. Results of our proposed system is efficient in analyzing the model accuracies and classify the email URLs accurately