stealthML: Data-driven Malware for Stealthy Data Exfiltration-Reference-Cited by-同舟云学术

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stealthML: Data-driven Malware for Stealthy Data Exfiltration

Published:2023-07-31 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Cyber Security and Resilience (CSR)
language:
Short-container-title:

Author:

Chung Keywhan¹,Cao Phuong²,Kalbarczyk Zbigniew T.¹,Iyer Ravishankar K.¹

Affiliation:

1. University of Illinois at Urbana-Champaign,Coordinated Science Laboratory

2. National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign

Funder

National Science Foundation (NSF)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10224900/10224823/10224946.pdf?arnumber=10224946

Reference18 articles.

1. Stoecklin. Deeplocker-Concealing Targeted Attacks with AI Locksmithing;kirat;BlackHat USA,2018

2. Double-Extortion Ransomware: A Technical Analysis of Maze Ransomware;kerns;Proc of the Future Technologies Conference,2021

3. Kill Chain;Analysis of the 2013 Target Data Breach,2014

4. Actions Taken by Equifax and Federal Agencies in Response to the 2017 Breach;marinos;Technical report New York NY USA,2018

5. The AI-Based Cyber Threat Landscape

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