Anti malware solution using Machine Learning
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This document discusses building a machine learning-based anti-malware solution using a classification model to identify whether a given binary is legitimate or malicious. It involves extracting features from binaries using PE parameters, selecting relevant independent variables, choosing a classification ML model, and using a Python script to extract parameters and predict outputs. A demo is available on YouTube and the Python scripts and datasets are on the author's GitHub account.
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Anti malware solution using Machine Learning
- 2. Anti-Malware using ML Enough of Machine Learning techniques…. Let’s Start Machine Learning in Cyber Security ! We will build a Machine Learning based Anti-malware solution by using classification model. Aim would be to identify whether a given binary is legitimate or malicious. Our dataset consists of n number of entries of executables(exe) and its properties. These exe will be malware executable as well as legitimate windows exe files.
- 3. Malwares
- 4. Anti-Malware using ML Traditional AV or anti malware solution works on signatures. Polymorphic malware bypass these traditional detection solutions. Malware detection is a classification problem. Machine learning learns the dataset and then based on its learning, It predicts : malware/not malware. Supply more and more latest dataset to improve machine learning model performance.
- 5. Anti-Malware using ML 1st Step – Feature extraction from binaries (PE Parameters) using pefile. 2nd Step – Feature selection to identify independent variables which will be relevant. 3rd Step – Selection of Classification machine learning model. 4th Step – Just run a .py file which will extract the parameters from exe file and predict the output.
- 6. Anti-Malware using ML Let’s Begin Machine Learning! Demo is available on Youtube:- https://www.youtube.com/watch?v=Kf9VD1os_pY&index=58&list=PL2iM- fIRjbTBFazzQ5uEzeASpmP8o40y1
- 7. Anti-Malware using ML - Conclusion All the python scripts and datasets for each part are available at my github account:- https://github.com/akky2892 THANK YOU !!