Compact feature hashing for machine learning based malware detection

Author:

Moon Damin,Lee JaeKoo,Yoon MyungKeunORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Networks and Communications,Hardware and Architecture,Information Systems,Software

Reference22 articles.

1. A close look at a daily dataset of malware samples;Ugarte-Pedrero;ACM Trans. Priv. Secur.,2019

2. VirusTotal, [Online]. Available: https://www.virustotal.com/en/statistics/.

3. Large-scale identification of malicious singleton files;Li,2017

4. Machine learning methods for malware detection;Kaspersky,2020

5. MutantX-S: Scalable malware clustering based on static features;Hu,2013

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1. Automated Malware Detection Based on a Machine Learning Algorithm;2023 IEEE Tenth International Conference on Communications and Networking (ComNet);2023-11-01

2. Securing IoT Devices Running PureOS from Ransomware Attacks: Leveraging Hybrid Machine Learning Techniques;Mathematics;2023-05-28

3. Hybrid Feature Hashing and Recurrent Neural Network based LSTM Architecture for Real Time Malware Analysis and Detection Techniques;2023 International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE);2023-01-27

4. Systematic Mapping of Machine Learning–Based Malware Detection Studies;2022 International Conference on Electrical, Computer and Energy Technologies (ICECET);2022-07-20

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