Machine Learning Detection of Ransomware by Lightweight Mini-filters-Reference-Cited by-同舟云学术

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Machine Learning Detection of Ransomware by Lightweight Mini-filters

Published:2023-02-03 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 6th Eurasian Conference on Educational Innovation (ECEI)
language:
Short-container-title:

Author:

Chiu Chen-Yu¹,Wu Min-Hao²,Huang Jian-Hung³,Chen Jian-Xin³,Wang Hao-Jyun³

Affiliation:

1. School of Art & Design, Guangzhou Panyu Polytechnic,Guangdong,China

2. School of Information Engineering, Guangzhou Panyu Polytechnic,Guangdong,China

3. National Central University,Department of Computer Science & Information Engineering,Taoyuan,Taiwan

Funder

Ministry of Science and Technology, Taiwan, R.O.C.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10105301/10105250/10105315.pdf?arnumber=10105315

Reference17 articles.

1. Behind closed doors: measurement and analysis of CryptoLocker ransoms in Bitcoin

2. Design of Quantification Model for Prevent of Cryptolocker

3. Connection-monitor & connection-breaker: A novel approach for prevention and detection of high survivable ransomwares

4. A Continuum of Internet-Based Crime: How the Effectiveness of Cybersecurity Policies Varies across Cybercrime Types;jardine;Research Handbook on Digital Transformations,2015

Cited by 1 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. Method for Detecting Steganographic Changes in Images Using Machine Learning;2023 13th International Conference on Dependable Systems, Services and Technologies (DESSERT);2023-10-13

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