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Malware detection using machine learning

https://doi.org/10.1109/imcsit.2009.5352759

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-540-70542-0_6openalex-snapshot

Learning and Classification of Malware Behavior

inferredcites →https://doi.org/10.1007/bf00994018openalex-snapshot

Support-Vector Networks

inferredcites →https://doi.org/10.1007/s11416-008-0105-1openalex-snapshot

Profile hidden Markov models and metamorphic virus detection

inferredcites →https://doi.org/10.1017/cbo9780511801389openalex-snapshot

An Introduction to Support Vector Machines and Other Kernel-based Learning Methods

inferredcites →https://doi.org/10.1023/a:1007662407062openalex-snapshot

Large Margin Classification Using the Perceptron Algorithm

inferredcites →https://doi.org/10.1037/h0042519openalex-snapshot

The perceptron: A probabilistic model for information storage and organization in the brain.

inferredcites →https://doi.org/10.1093/bioinformatics/16.5.412openalex-snapshot

Assessing the accuracy of prediction algorithms for classification: an overview

inferredcites →https://doi.org/10.1093/bioinformatics/btm026openalex-snapshot

De novo SVM classification of precursor microRNAs from genomic pseudo hairpins using global and intrinsic folding measures

inferredcites →https://doi.org/10.1109/malware.2008.4690861openalex-snapshot

Using Markov chains to filter machine-morphed variants of malicious programs

inferredcites →https://doi.org/10.1109/pccc.2007.358933openalex-snapshot

SpyCon: Emulating User Activities to Detect Evasive Spyware

inferredcites →https://doi.org/10.1145/1029208.1029222openalex-snapshot

Visualizing windows executable viruses using self-organizing maps

inferredcites →https://doi.org/10.1145/1281192.1281308openalex-snapshot

IMDS

inferredcites →https://doi.org/10.1145/279943.279985openalex-snapshot

Large margin classification using the perceptron algorithm

inferredcites →https://doi.org/10.1198/jasa.2003.s269openalex-snapshot

Learning With Kernels: Support Vector Machines, Regularization, Optimization, and Beyond

inferredcites →https://doi.org/10.5220/0001863603170320openalex-snapshot

N-GRAMS-BASED FILE SIGNATURES FOR MALWARE DETECTION

inferredcites →https://doi.org/10.5555/1248547.1248643openalex-snapshot

Machine Learning for Computer Security

inferredcites →https://doi.org/10.5555/1248547.1248646openalex-snapshot

Learning to Detect and Classify Malicious Executables in the Wild

inferredcites →https://doi.org/10.7551/mitpress/4175.001.0001openalex-snapshot

Learning with Kernels

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Taxonomy on RapidMiner Using Machine Learning

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A Comparative Study Of Malware Detection Techniques Using Machine Learning Methods

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Malware Detection

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A Deep Learning–Based Malware and Intrusion Detection Framework

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Outgoing Data Filtration for Detecting Spyware on Personal Computers

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Feature Selection Using a Machine Learning to Classify a Malware

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Malware Detection in Executable Files Using Machine Learning

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Statistical Learning Applied to Malware Detection

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Context for API Calls in Malware vs Benign Programs

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Comparative Analysis of Various Machine Learning Algorithms for Detection of Malware and Benign

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Performance of Machine Learning Classifiers for Malware Detection Over Imbalanced Data

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Unveiling Powerful Machine Learning Strategies for Detecting Malware in Modern Digital Environment

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Anthology of ML Based Data Science Applications

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Design and Development of an Efficient Malware Detection Using ML

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Deep Learning Based Malware Analysis

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CLOP Ransomware Analysis Using Machine Learning Approach

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Malware Prediction Analysis Using AI Techniques with the Effective Preprocessing and Dimensionality Reduction

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Leveraging Classification and Detection of Malware: A Robust Machine Learning-Based Framework

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Malware Detection Using Machine Learning Techniques

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An Effective Model for Malware Detection

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Dronezilla: designing an accurate malware behavior retrieval system

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Building a practical and reliable classifier for malware detection

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A practical approach for clustering large data flows of malicious URLs

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Enhanced DNNs for malware classification with GAN-based adversarial training

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Malware recognition using novel convolutional neural network with residual connections

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Detection of malware in downloaded files using various machine learning models

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Detecting malware evolution using support vector machines

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Malware Detection: Issues and Challenges

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Comparative analysis of machine learning methods for detecting malicious files

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Detection of Malware Attacks using Artiﬁcial Neural Network

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Automated Malware Analysis in Internet of Things based Systems: A Deep Learning Approach

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Malicious Code Detection Using Machine Learning

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The Phenomenon of Cyber-Crime and Fraud Victimization in Online Shop

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Applying machine learning algorithms for PE-header-based malware detection on the Windows operating system

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Efficient Explanation and Evaluation Methodology Based on Hybrid Feature Dropout

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Malware Detection in Files and URL’s using Machine Learning

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Combined kNN Classification and Hierarchical Similarity Hash for Fast Malware Detection

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Applications in Security and Evasions in Machine Learning: A Survey

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Malicious PowerShell Detection Using Attention against Adversarial Attacks

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A Closer Look at Machine Learning Effectiveness in Android Malware Detection

inferred← citeshttps://doi.org/10.3390/s20102893openalex-snapshot

Attention-Based Automated Feature Extraction for Malware Analysis

inferred← citeshttps://doi.org/10.3390/s22041335openalex-snapshot

Static Analysis of Information Systems for IoT Cyber Security: A Survey of Machine Learning Approaches

inferred← citeshttps://doi.org/10.3390/s23020946openalex-snapshot

Evaluation of Machine Learning Algorithms for Malware Detection

inferred← citeshttps://doi.org/10.3390/sym14112304openalex-snapshot

Malware Analysis and Detection Using Machine Learning Algorithms

inferred← citeshttps://doi.org/10.35940/ijeat.d8025.049420openalex-snapshot

Malware Detection using ANN Malviz.AI

inferred← citeshttps://doi.org/10.35940/ijitee.l7889.1091220openalex-snapshot

Deep Droid: Deep Learning for Android Malware Detection

inferred← citeshttps://doi.org/10.3934/mbe.2021300openalex-snapshot

Malware detection based on semi-supervised learning with malware visualization

inferred← citeshttps://doi.org/10.4018/978-1-5225-9611-0.ch001openalex-snapshot

Review on Intelligent Algorithms for Cyber Security

inferred← citeshttps://doi.org/10.4018/978-1-7998-4900-1.ch006openalex-snapshot

Deep Learning-Based Malware Detection and Classification

inferred← citeshttps://doi.org/10.4018/978-1-7998-7789-9.ch001openalex-snapshot

Machine Learning for Malware Analysis

inferred← citeshttps://doi.org/10.4018/979-8-3693-7758-1.ch008openalex-snapshot

Integrating Machine Learning Techniques for Comprehensive Malware Classification

inferred← citeshttps://doi.org/10.4108/eetiot.6774openalex-snapshot

A Probabilistic Descent Ensemble for Malware Prediction Using Deep Learning

inferred← citeshttps://doi.org/10.4236/jcc.2018.61016openalex-snapshot

Malware Images Classification Using Convolutional Neural Network

inferred← citeshttps://doi.org/10.48175/ijarsct-31469openalex-snapshot

AI-Based Cyber Threat Detection System: An Integrated Approach Using Machine Learning for Network, Email, and Malware Security

inferred← citeshttps://doi.org/10.48550/arxiv.1911.09586openalex-snapshot

The Performance of Machine and Deep Learning Classifiers in Detecting Zero-Day Vulnerabilities

inferred← citeshttps://doi.org/10.5120/ijca2019918355openalex-snapshot

An Analysis of Malware Classification Technique by using Machine Learning

inferred← citeshttps://doi.org/10.54554/jtec.2023.15.03.004openalex-snapshot

A Deep Learning Model for Malware Multi-Class Classification based on Colored Malware Images

inferred← citeshttps://doi.org/10.54692/ijeci.2024.0801185openalex-snapshot

A Comprehensive Study for Malware Detection through Machine Learning in Executable Files

inferred← citeshttps://doi.org/10.54939/1859-1043.j.mst.90.2023.134-139openalex-snapshot

Hướng tiếp cận phát hiện mã độc dựa trên phân tích tĩnh kết hợp thuật toán học máy

inferred← citeshttps://doi.org/10.55524/ijircst.2024.12.1.7openalex-snapshot

Analysis of Cyber Security Threats Using Machine Learning Techniques

inferred← citeshttps://doi.org/10.5815/ijcnis.2023.02.04openalex-snapshot

Detecting Remote Access Network Attacks Using Supervised Machine Learning Methods

inferred← citeshttps://doi.org/10.5815/ijieeb.2023.02.03openalex-snapshot

Malware Multi-Class Classification based on Malware Visualization using a Convolutional Neural Network Model

inferred← citeshttps://doi.org/10.58837/chula.the.2017.1374openalex-snapshot

การคดแยกไวรสคอมพวเตอรจากรหสฐานสอง

inferred← citeshttps://doi.org/10.71097/ijsat.v16.i1.1428openalex-snapshot

A COMPREHENSIVE REVIEW ON MALWARE DETECTION TECHNIQUES

inferred← citeshttps://doi.org/10.71097/ijsat.v16.i2.6747openalex-snapshot

Malware Detection System Using Machine Learning

inferred← citeshttps://doi.org/10.9781/ijimai.2017.03.013openalex-snapshot

N-grams Based Supervised Machine Learning Model for Mobile Agent Platform Protection against Unknown Malicious Mobile Agents

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.