FutureComputing4AI/KiloGrams
KiloGram algorithm for finding the top-k most frequent n-grams for large values of n quickly with fixed memory.
This tool helps cybersecurity researchers and data scientists efficiently extract the most frequent N-grams from large collections of files, like malware samples or software executables. You input paths to folders containing your files (e.g., 'goodware' and 'malware'), and it outputs a dataset in a format like libsvm, ready for machine learning analysis. It's designed for those building machine learning models for file classification, particularly in cybersecurity.
No commits in the last 6 months.
Use this if you need to generate features for machine learning models by identifying the most common very large N-grams from extensive file datasets, especially for malware analysis or binary classification tasks.
Not ideal if you require a user-friendly application with a graphical interface or if you need ongoing support and warranty for production systems.
Stars
9
Forks
4
Language
Java
License
Apache-2.0
Category
Last pushed
Oct 08, 2025
Commits (30d)
0
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