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Journal of Computer and Communications

Journal of Computer and Communications

Journal of Computer and Communications

ISSN Print: 2327-5219
ISSN Online: 2327-5227
www.scirp.org/journal/jcc
E-mail: jcc@scirp.org
"Malware Images Classification Using Convolutional Neural Network"
written by Espoir K. Kabanga, Chang Hoon Kim,
published by Journal of Computer and Communications, Vol.6 No.1, 2018
has been cited by the following article(s):
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[2] Efficient malware classification by binary sequences with one-dimensional convolutional neural networks
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[17] Machine Learning Classification of Obfuscation using Image Visualization.
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[18] Malware Classification Approaches Using Machine Learning Techniques: A Review
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[19] Malicious Code Variant Identification Based on Multiscale Feature Fusion CNNs
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[20] Image classification for EGG incubator using transfer learning of VGG16 and VGG19
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[22] RETRACTED ARTICLE: A Survey on Malware Detection and Classification
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[23] Recent innovations and comparison of deep learning techniques in malware classification: a review
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[24] Towards Detecting Evasive Malware in the Age of Smart Adversaries
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[25] Malware Classification Using Attention-Based Transductive Learning Network
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[26] Classifying Malware Images with Convolutional Neural Network Models
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[27] Malware Classification Using CNN-XGBoost Model
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[28] A survey on practical adversarial examples for malware classifiers
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[29] Image-based Malware Family Detection: An Assessment between Feature Extraction and Classification Techniques.
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[30] Malware Classification Framework using Convolutional Neural Network
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[31] A survey on malware detection and classification
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[32] An Experimental Study to Evaluate the Performance of Machine Learning Alogrithms in Ransomware Detection
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[33] Generalization Performance Comparison of Machine Learners for the Detection of Computer Worms Using Behavioral Features
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[34] An improved two-hidden-layer extreme learning machine for malware hunting
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[35] Customized Convolutional Neural Networks with K-Nearest Neighbor Classification System for Malware Categorization
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[36] A Comprehensive Tutorial and Survey of Applications of Deep Learning for Cyber Security
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[37] The Image Game: Exploit Kit Detection Based on Recursive Convolutional Neural Networks
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[38] An enhanced stacked LSTM method with no random initialization for malware threat hunting in safety and time-critical systems
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[39] Study on the Different Types of Neural Networks to Improve the Classification of Ransomwares.
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[56] Experiential Learning: Case Study-Based Portable Hands-on Regression Labware for Cyber Fraud Prediction
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[57] Short Paper: Creating Adversarial Malware Examples using Code Insertion.
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[58] Malware Classification with Markov Transition Field Encoded Images
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[60] Evaluation and Design of Robust Neural Network Defenses
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[64] Malware Classification Using Customized Convolutional Neural Networks by Leaky RELU Activated Function
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