4.2 Article

Op2Vec: An Opcode Embedding Technique and Dataset Design for End-to-End Detection of Android Malware

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Computer Science, Artificial Intelligence

Deep learning-aided runtime opcode-based Windows malware detection

Enes Sinan Parildi et al.

Summary: This paper presents an alternative method for malware detection using assembly opcode sequences obtained during runtime, extracting deeper behavioral features through natural language processing and deep learning techniques. This method proves effective against novel malware and code obfuscation, achieving high MCC scores of 0.95 on more balanced datasets.

NEURAL COMPUTING & APPLICATIONS (2021)

Article Computer Science, Artificial Intelligence

Learning to detect Android malware via opcode sequences

Abdurrahman Pektas et al.

NEUROCOMPUTING (2020)

Article Computer Science, Hardware & Architecture

Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection

Ambra Demontis et al.

IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING (2019)

Article Computer Science, Artificial Intelligence

Training neural networks on high-dimensional data using random projection

Piotr Iwo Wojcik et al.

PATTERN ANALYSIS AND APPLICATIONS (2019)

Article Computer Science, Artificial Intelligence

Effective android malware detection with a hybrid model based on deep autoencoder and convolutional neural network

Wei Wang et al.

JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING (2019)

Article Computer Science, Theory & Methods

A Multimodal Deep Learning Method for Android Malware Detection Using Various Features

TaeGuen Kim et al.

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY (2019)

Article Computer Science, Artificial Intelligence

Similarity encoding for learning with dirty categorical variables

Patricio Cerda et al.

MACHINE LEARNING (2018)

Article Computer Science, Information Systems

AMAL: High-fidelity, behavior-based automated malware analysis and classification

Aziz Mohaisen et al.

COMPUTERS & SECURITY (2015)

Article Computer Science, Information Systems

Exfiltrating data from Android devices

Quang Do et al.

COMPUTERS & SECURITY (2015)

Review Computer Science, Artificial Intelligence

Deep learning in neural networks: An overview

Juergen Schmidhuber

NEURAL NETWORKS (2015)

Proceedings Paper Computer Science, Information Systems

Drebin: Effective and Explainable Detection of Android Malware in Your Pocket

Daniel Arp et al.

21ST ANNUAL NETWORK AND DISTRIBUTED SYSTEM SECURITY SYMPOSIUM (NDSS 2014) (2014)