HackBU_2023

Annual hackathon event hosted by Binghamton's HackBU

Members:

• Anthony Zhang (azhan134@binghamton.edu)
• Jeffrey Huang (jhuan262@binghamton.edu)
• Julian Ortiz (jortiz53@binghamton.edu)
• Klejben Hysenbelli (khysenb1@binghamton.edu)

Hack:

Utilizes machine learning to determine the safety of a website given its URL. Combining pre-existing databases labeling websites as 'good' or 'bad' with Beautiful Soup (an HTML parser in python), we determined metrics to check the safety of a website. These metrics are moved to a csv file, and the data is used to train our algorithm by finding correlations and weighing metrics.

Metrics:

• url
• url_length
• https (https or http)
• number of outgoing links
• number of safe outgoing links
• number of non-safe outgoing links
• length of content (total number of chars)
• status (whether site is currently up or down)
• tld (domain name)
• sentiment analysis (positive or negative)
• bad_words (if url contains key words that are "bad")
• label (whether the site is malicious or not)

Built With

• csv
• pandas
• python
• sklearn