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Intelligent Malware Detection Using File-to-file Relations and Enhancing its Security against Adversarial Attacks

机译：智能恶意软件检测使用文件到文件关系并提高其对抗对抗攻击的安全性

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作者
Chen, Lingwei.;
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作者单位

West Virginia University.;

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授予单位 West Virginia University.;
学科
学位 Ph.D.
年度 2019
页码 138 p.
总页数 138
原文格式 PDF
正文语种 eng
中图分类 AAI27805956;
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1. Robust Android Malware Detection System Against Adversarial Attacks Using Q-Learning [J] . Rathore Hemant, Sahay Sanjay K., Nikam Piyush, Information systems frontiers . 2021,第4期

机译：强大的Android恶意软件检测系统反对使用Q-Learning的对抗攻击
2. Robust Malware Detection Models: Learning from Adversarial Attacks and Defenses [J] . Rathore Hemant, Samavedhi Adithya, Sahay Sanjay K., Digital investigation . 2021,第Suppla期

机译：鲁棒恶意软件检测模型：从对抗性攻击和防御中学习
3. Towards Adversarial Malware Detection: Lessons Learned from PDF-based Attacks [J] . Maiorca Davide, Biggio Battista, Giacinto Giorgio ACM Computing Surveys . 2020,第4期

机译：朝向侵犯恶意软件检测：从基于PDF的攻击中汲取的经验教训
4. Analyzing File-to-File Relation Network in Malware Detection [C] . Lingwei Chen, William Hardy, Yanfang Ye, . 2015

机译：在恶意软件检测中分析文件间关系网络
5. On Concept Drift, Deployability, and Adversarial Selection in Machine Learning-Based Malware Detection. [D] . Singh, Anshuman. 2012

机译：基于机器学习的恶意软件检测中的概念漂移，可部署性和对抗选择。
6. DeepDetectNet vs RLAttackNet: An adversarial method to improve deep learning-based static malware detection model [O] . Yong Fang, Yuetian Zeng, Beibei Li, 2020

机译：DeepDetectNet VS RLATTACKNET：一种改进基于深度学习的静态恶意软件检测模型的对手方法
7. Robust Android Malware Detection System Against Adversarial Attacks Using Q-Learning [O] . Hemant Rathore, Sanjay K. Sahay, Piyush Nikam, 2020

机译：强大的Android恶意软件检测系统使用Q-Learning对抗对抗攻击

Intelligent Malware Detection Using File-to-file Relations and Enhancing its Security against Adversarial Attacks

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