Deployable Machine Learning for Security Defense: Second International Workshop, MLHat 2021
- Length: 168 pages
- Edition: 1
- Language: English
- Publisher: Springer
- Publication Date: 2021-09-25
- ISBN-10: 3030878384
- ISBN-13: 9783030878382
- Sales Rank: #0 (See Top 100 Books)
This book constitutes selected and extended papers from the Second International Workshop on Deployable Machine Learning for Security Defense, MLHat 2021, held in August 2021. Due to the COVID-19 pandemic the conference was held online.
The 6 full papers were thoroughly reviewed and selected from 7 qualified submissions. The papers are organized in topical sections on machine learning for security, and malware attack and defense.
Cover Front Matter Machine Learning for Security STAN: Synthetic Network Traffic Generation with Generative Neural Models Machine Learning for Fraud Detection in E-Commerce: A Research Agenda Few-Sample Named Entity Recognition for Security Vulnerability Reports by Fine-Tuning Pre-trained Language Models Malware Attack and Defense DexRay: A Simple, yet Effective Deep Learning Approach to Android Malware Detection Based on Image Representation of Bytecode Attacks on Visualization-Based Malware Detection: Balancing Effectiveness and Executability A Survey on Common Threats in npm and PyPi Registries Back Matter
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