Advanced malware and their impact on virtualization: A case study on hybrid feature extraction using deep memory introspection

Author:

Bhatt Mohit1,Gaur Avantika1,Badoni Saksham1,Mishra Preeti1

Affiliation:

1. Doon University, India

Funder

SERB DST

Publisher

ACM

Reference14 articles.

1. Tight Arms Race: Overview of Current Malware Threats and Trends in Their Detection

2. Huseyn Huseynov , Kenichi Kourai , Tarek Saadawi , and Obinna Igbe . 2020 . Virtual Machine Introspection for Anomaly-Based Keylogger Detection. In 2020 IEEE 21st International Conference on High Performance Switching and Routing (HPSR). 1–6. https://doi.org/10 .1109/HPSR48589.2020.9098980 10.1109/HPSR48589.2020.9098980 Huseyn Huseynov, Kenichi Kourai, Tarek Saadawi, and Obinna Igbe. 2020. Virtual Machine Introspection for Anomaly-Based Keylogger Detection. In 2020 IEEE 21st International Conference on High Performance Switching and Routing (HPSR). 1–6. https://doi.org/10.1109/HPSR48589.2020.9098980

3. Divya Kapil and Preeti Mishra . 2021. Virtual Machine Introspection in Virtualization: A Security Perspective . Association for Computing Machinery , New York, NY, USA , 117–124. https://doi.org/10.1145/3474124.3474140 10.1145/3474124.3474140 Divya Kapil and Preeti Mishra. 2021. Virtual Machine Introspection in Virtualization: A Security Perspective. Association for Computing Machinery, New York, NY, USA, 117–124. https://doi.org/10.1145/3474124.3474140

4. Scalability, fidelity and stealth in the DRAKVUF dynamic malware analysis system

5. VMShield: Memory Introspection-Based Malware Detection to Secure Cloud-Based Services Against Stealthy Attacks

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1. DeepHyperv: A deep neural network based virtual memory analysis for malware detection at hypervisor-layer;2023 International Conference on Advances in Intelligent Computing and Applications (AICAPS);2023-02-01

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