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Summary

DS-1263
Malware Training Sets
External Dataset
External Data Source
GitHub
Unknown
Unknown
55 (lowest rank is 55)

Category & Restrictions

Other
malware, cyber attack
Unrestricted
true

Description


Aim of the project is to provide an useful and classified dataset to researchers who want to investigate deeper in malware analysis by using Machine Learning techniques.

One of the most challenging tasks during Machine Learning processing is to define a great training (and possible dynamic) dataset. Assuming a well known learning algorithm and a periodic learning supervised process what you need is a classified dataset to best train your machine. Thousands of training datasets are available out there, but no great classified datasets for malware analyses exist. This dataset was created to share with the scientific community (and everybody interested on it) in order to give to everyone a base point to start with Machine Learning for Malware Analysis.

The collected dataset is composed by the following samples:

APT1 292 Samples
Crypto 2024 Samples
Locker 434 Samples
Zeus 2014 Samples

Additional Details

31.6MB
false
Unknown
zeus web server, external data source, cybercrime, malware analysis, malware training sets, malware, web server software, 1263, inferlink corporation, machine learning, exploit, locker