PhishGuard Ai

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  PhishGuard Ai

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Inspiration

What it does

How we built it

Challenges we ran into

Accomplishments that we're proud of

What we learned

What's next for PhishGuard Ai

A Phishing Email Detection model is a cybersecurity system designed to automatically identify malicious emails that attempt to steal sensitive information such as passwords, banking credentials, or personal data. Phishing emails usually impersonate trusted organizations like banks, payment services, or social media platforms and trick users into clicking malicious links or providing confidential information. The goal of this model is to analyze the content of an email and classify it as either legitimate (safe) or phishing (malicious).

The system works using machine learning techniques. First, a dataset containing email messages and their labels (0 for safe, 1 for phishing) is collected. The email text is then cleaned through preprocessing steps such as converting text to lowercase, removing punctuation, and eliminating unnecessary words. After preprocessing, the text is transformed into numerical features using a technique called TF-IDF (Term Frequency–Inverse Document Frequency), which helps the model understand the importance of words within emails.

Built With

• csv
• data
• machine-learning
• numpy
• panda
• python
• scikit-learn