MalDy: Portable, data-driven malware detection using natural language processing and machine learning techniques on behavioral analysis reports-Reference-Cited by-同舟云学术

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MalDy: Portable, data-driven malware detection using natural language processing and machine learning techniques on behavioral analysis reports

Published:2019-04 Issue: Volume:28 Page:S77-S87
ISSN:1742-2876
Container-title:Digital Investigation
language:en
Short-container-title:Digital Investigation

Author:

Karbab ElMouatez Billah,Debbabi Mourad

Publisher

Elsevier BV

Subject

Law,Medical Laboratory Technology,Computer Science Applications

Reference40 articles.

1. N-gram-based detection of new malicious code;Abou-Assaleh,2004

2. DynaLog: an automated dynamic analysis framework for characterizing Android applications;Alzaylaee;CoRR,2016

3. UNVEIL: a large-scale, automated approach to detecting ransomware;Amin,2016

4. Android Emulator - https://tinyurl.com/zlngucb, 2016.

5. Android SDK - https://tinyurl.com/hn8qo9o, 2016.

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2. DawnGNN: Documentation augmented windows malware detection using graph neural network;Computers & Security;2024-05

3. Clustering android ransomware families using fuzzy hashing similarities;Journal of Intelligent & Fuzzy Systems;2024-04-02

4. A systematic literature review on Windows malware detection: Techniques, research issues, and future directions;Journal of Systems and Software;2024-03

5. DFRWS EU 10-year review and future directions in Digital Forensic Research;Forensic Science International: Digital Investigation;2024-03

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