Ensemble-Based Classification Using Neural Networks and Machine Learning Models for Windows PE Malware Detection

Artificial Intelligence in the Cyber Domain: Offense and Defense

(2020) Thanh Cong Truong et al.   Symmetry-Basel

End-to-end malware detection for android IoT devices using deep learning

(2020) Zhongru Ren et al.   Ad Hoc Networks

DeepDetectNet vs RLAttackNet: An adversarial method to improve deep learning-based static malware detection model

(2020) Yong Fang et al.   PLoS One

Investigation of Dual-Flow Deep Learning Models LSTM-FCN and GRU-FCN Efficiency against Single-Flow CNN Models for the Host-Based Intrusion and Malware Detection Task on Univariate Times Series Data

(2020) Dainius Čeponis et al.   Applied Sciences-Basel

Malicious JavaScript Detection Based on Bidirectional LSTM Model

(2020) Xuyan Song et al.   Applied Sciences-Basel

Ensemble Malware Classification System Using Deep Neural Networks

(2020) Barath Narayanan Narayanan et al.   Electronics

AMalNet: A deep learning framework based on graph convolutional networks for malware detection

(2020) Xinjun Pei et al.   COMPUTERS & SECURITY

VisDroid: Android malware classification based on local and global image features, bag of visual words and machine learning techniques

(2020) Khaled Bakour et al.   NEURAL COMPUTING & APPLICATIONS

Hybrid Malware Classification Method Using Segmentation-Based Fractal Texture Analysis and Deep Convolution Neural Network Features

(2020) Maryam Nisa et al.   Applied Sciences-Basel

Improving malware detection using big data and ensemble learning

(2020) Deepak Gupta et al.   COMPUTERS & ELECTRICAL ENGINEERING

JOWMDroid: Android Malware Detection Based on Feature Weighting with Joint Optimization of Weight-Mapping and Classifier Parameters

(2020) Lingru Cai et al.   COMPUTERS & SECURITY

Malware-Detection Method with a Convolutional Recurrent Neural Network Using Opcode Sequences

(2020) Seungho Jeon et al.   INFORMATION SCIENCES

Cybersecurity Risks in a Pandemic

(2020) Christina Meilee Williams et al.   JOURNAL OF MEDICAL INTERNET RESEARCH

A Method for Windows Malware Detection Based on Deep Learning

(2020) Xiang Huang et al.   Journal of Signal Processing Systems for Signal Image and Video Technology

SLAM: A Malware Detection Method Based on Sliding Local Attention Mechanism

(2020) Jun Chen et al.   Security and Communication Networks

Ensemble machine learning approaches for webshell detection in Internet of things environments

(2020) Binbin Yong et al.   Transactions on Emerging Telecommunications Technologies

Utilising Deep Learning Techniques for Effective Zero-Day Attack Detection

(2020) Hanan Hindy et al.   Electronics

Recurrent neural network for detecting malware

(2020) Sudan Jha et al.   COMPUTERS & SECURITY

DeepAMD: Detection and identification of Android malware using high-efficient Deep Artificial Neural Network

(2020) Syed Ibrahim Imtiaz et al.   Future Generation Computer Systems-The International Journal of eScience

An Android mutation malware detection based on deep learning using visualization of importance from codes

(2019) Yao-Saint Yen et al.   MICROELECTRONICS RELIABILITY

Machine-Learning based analysis and classification of Android malware signatures

(2019) Ignacio Martín et al.   Future Generation Computer Systems-The International Journal of eScience

Ransomware Detection System for Android Applications

(2019) Samah Alsoghyer et al.   Electronics

A critique of pure learning and what artificial neural networks can learn from animal brains

(2019) Anthony M. Zador   Nature Communications

An improved two-hidden-layer extreme learning machine for malware hunting

(2019) Amir Namavar Jahromi et al.   COMPUTERS & SECURITY

DL-Droid: Deep learning based android malware detection using real devices

(2019) Mohammed K. Alzaylaee et al.   COMPUTERS & SECURITY

Detecting Android malicious apps and categorizing benign apps with ensemble of classifiers

(2018) Wei Wang et al.   Future Generation Computer Systems-The International Journal of eScience

Detecting Malware with an Ensemble Method Based on Deep Neural Network

(2018) Jinpei Yan et al.   Security and Communication Networks

Ensemble learning: A survey

(2018) Omer Sagi et al.   Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery

A Novel Dynamic Android Malware Detection System With Ensemble Learning

(2018) Pengbin Feng et al.   IEEE Access

A state-of-the-art survey of malware detection approaches using data mining techniques

(2018) Alireza Souri et al.   Human-centric Computing and Information Sciences

Survey of machine learning techniques for malware analysis

(2018) Daniele Ucci et al.   COMPUTERS & SECURITY

Malware detection based on deep learning algorithm

(2017) Ding Yuxin et al.   NEURAL COMPUTING & APPLICATIONS

A survey on automated dynamic malware-analysis techniques and tools

(2012) Manuel Egele et al.   ACM COMPUTING SURVEYS