Authentic Learning of Machine Learning to Ransomware Detection and Prevention-Reference-Cited by-同舟云学术

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Authentic Learning of Machine Learning to Ransomware Detection and Prevention

Published:2022-06 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)
language:
Short-container-title:

Author:

Faruk Md Jobair Hossain¹,Masum Mohammad²,Shahriar Hossain³,Qian Kai⁴,Lo Dan⁴

Affiliation:

1. Kennesaw State University,Department of Software Engineering and Game Development,USA

2. School of Data Science, Kennesaw State University,USA

3. Kennesaw State University,Department of Information Technology,USA

4. Kennesaw State University,Department Computer Science,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9842455/9842394/09842537.pdf?arnumber=9842537

Reference6 articles.

1. Malware Detection and Prevention using Artificial Intelligence Techniques

2. Ransomware Classification and Detection With Machine Learning Algorithms

3. Bayesian Hyperparameter Optimization for Deep Neural Network-Based Network Intrusion Detection

4. Authentic learning of mobile security with case studies

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Authentic Learning on DevOps Security with Labware: Git Hooks To Facilitate Automated Security Static Analysis;2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC);2024-07-02

2. ARdetector: android ransomware detection framework;The Journal of Supercomputing;2023-11-08

3. A Recent Systematic Review of Ransomware Attack detection in machine learning techniques;2023 4th International Conference on Artificial Intelligence and Data Sciences (AiDAS);2023-09-06

4. Case Study-Based Approach of Quantum Machine Learning in Cybersecurity: Quantum Support Vector Machine for Malware Classification and Protection;2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC);2023-06

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