Comparative Analysis of LSTM, One-Class SVM, and PCA to Monitor Real-Time Malware Threats Using System Call Sequences and Virtual Machine Introspection-Reference-Cited by-同舟云学术

Comparative Analysis of LSTM, One-Class SVM, and PCA to Monitor Real-Time Malware Threats Using System Call Sequences and Virtual Machine Introspection

Published:2021 Issue: Volume: Page:113-127
ISSN:1876-1100
Container-title:Lecture Notes in Electrical Engineering
language:
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Author:

Soni Jayesh,Peddoju Suresh K.,Prabakar Nagarajan,Upadhyay Himanshu

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-33-4909-4_9

Reference38 articles.

1. Peddoju SK, Upadhyay H, Lagos L (2020) File integrity monitoring tools: issues, challenges, and solutions. Concurr Comput Pract Exper e5825. https://doi.org/https://doi.org/10.1002/cpe.5825

2. Suresh Kumar P, Ramachandram S (2019) Fuzzy-based integration of security and trust in distributed computing. In: Soft computing for problem solving. Advances in intelligent systems and computing, vol 816. Springer, Singapore

3. Ligh MH, Case A, Levy J, Walters A (2014) The art of memory forensics

4. Xen Project (2013) available at https://www.xenproject.org/

5. Hizver J, Chiueh T (2014) Real-time deep virtual machine introspection and its applications.ACM SIGPLAN Notices 49(7)

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