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Swarm Optimization and Machine Learning Applied to PE Malware Detection towards Cyber Threat Intelligence

https://doi.org/10.3390/electronics12020342

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What this work says

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

inferredcites →https://doi.org/10.1007/978-0-387-30164-8_192openalex-snapshot

Curse of Dimensionality

inferredcites →https://doi.org/10.1007/978-3-319-19578-0_34openalex-snapshot

A Real-Time PE-Malware Detection System Based on CHI-Square Test and PE-File Features

inferredcites →https://doi.org/10.1007/978-3-540-74565-5_5openalex-snapshot

Applying Machine Learning Techniques for Detection of Malicious Code in Network Traffic

inferredcites →https://doi.org/10.1007/978-981-13-3582-2_9openalex-snapshot

Novel Wrapper-Based Feature Selection for Efficient Clinical Decision Support System

inferredcites →https://doi.org/10.1007/978-981-15-4992-2_12openalex-snapshot

PE File-Based Malware Detection Using Machine Learning

inferredcites →https://doi.org/10.1007/s00521-016-2473-7openalex-snapshot

Modified cuckoo search algorithm with rough sets for feature selection

inferredcites →https://doi.org/10.1007/s11416-008-0082-4openalex-snapshot

An intelligent PE-malware detection system based on association mining

inferredcites →https://doi.org/10.1007/s11416-016-0274-2openalex-snapshot

Structural analysis of binary executable headers for malware detection optimization

inferredcites →https://doi.org/10.1016/j.advengsoft.2013.12.007openalex-snapshot

Grey Wolf Optimizer

inferredcites →https://doi.org/10.1016/j.engappai.2014.03.007openalex-snapshot

An unsupervised feature selection algorithm based on ant colony optimization

inferredcites →https://doi.org/10.1016/j.eswa.2006.04.010openalex-snapshot

A hybrid approach for feature subset selection using neural networks and ant colony optimization

inferredcites →https://doi.org/10.1016/j.jksuci.2017.01.003openalex-snapshot

A learning model to detect maliciousness of portable executable using integrated feature set

inferredcites →https://doi.org/10.1016/j.neucom.2015.06.083openalex-snapshot

Binary grey wolf optimization approaches for feature selection

inferredcites →https://doi.org/10.1016/s1361-3723(14)70531-7openalex-snapshot

Using feature generation from API calls for malware detection

inferredcites →https://doi.org/10.1051/matecconf/201823203003openalex-snapshot

A Comparative Study of Cuckoo Algorithm and Ant Colony Algorithm in Optimal Path Problems

inferredcites →https://doi.org/10.1109/access.2019.2906757openalex-snapshot

Binary Optimization Using Hybrid Grey Wolf Optimization for Feature Selection

inferredcites →https://doi.org/10.1109/cec.2002.1004474openalex-snapshot

Ant colony optimization for FOP shop scheduling: a case study on different pheromone representations

inferredcites →https://doi.org/10.1109/csa.2008.28openalex-snapshot

PE File Header Analysis-Based Packed PE File Detection Technique (PHAD)

inferredcites →https://doi.org/10.1109/icec.1996.542672openalex-snapshot

Solving symmetric and asymmetric TSPs by ant colonies

inferredcites →https://doi.org/10.1109/isi.2008.4565046openalex-snapshot

Unknown malcode detection via text categorization and the imbalance problem

inferredcites →https://doi.org/10.1109/malware.2010.5665799openalex-snapshot

Header information in malware families and impact on automated classifiers

inferredcites →https://doi.org/10.1109/ncm.2009.385openalex-snapshot

Detecting Unknown Malicious Executables Using Portable Executable Headers

inferredcites →https://doi.org/10.1109/osscom.2016.7863676openalex-snapshot

The malware detection challenge of accuracy

inferredcites →https://doi.org/10.1109/secpri.2001.924286openalex-snapshot

Data mining methods for detection of new malicious executables

inferredcites →https://doi.org/10.1109/tsmcc.2009.2037978openalex-snapshot

CIMDS: Adapting Postprocessing Techniques of Associative Classification for Malware Detection

inferredcites →https://doi.org/10.1145/1014052.1014105openalex-snapshot

Learning to detect malicious executables in the wild

inferredcites →https://doi.org/10.1145/3128572.3140442openalex-snapshot

Learning the PE Header, Malware Detection with Minimal Domain Knowledge

inferredcites →https://doi.org/10.1186/s40537-020-00327-4openalex-snapshot

Selecting critical features for data classification based on machine learning methods

inferredcites →https://doi.org/10.1504/ijmmno.2010.035430openalex-snapshot

Engineering optimisation by cuckoo search

inferredcites →https://doi.org/10.25073/jaec.201712.64openalex-snapshot

Malware Detection Based on Multiple PE Headers Identification and Optimization for Specific Types of Files

inferredcites →https://doi.org/10.32604/iasc.2021.016933openalex-snapshot

A Learning-based Static Malware Detection System with Integrated Feature

inferredcites →https://doi.org/10.3390/electronics10040485openalex-snapshot

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

inferredcites →https://doi.org/10.4018/ijisp.2017070103openalex-snapshot

Malware Detection by Static Checking and Dynamic Analysis of Executables

inferredcites →https://doi.org/10.4018/ijisp.2020070106openalex-snapshot

Feature Reduction and Optimization of Malware Detection System Using Ant Colony Optimization and Rough Sets

inferredcites →https://doi.org/10.5281/zenodo.1075109openalex-snapshot

Ant Colony Optimization For Feature Subset Selection

inferredcites →https://doi.org/10.5815/ijcnis.2019.09.02openalex-snapshot

An Improved Method for Packed Malware Detection using PE Header and Section Table Information

inferredcites →https://doi.org/10.5815/ijitcs.2017.04.08openalex-snapshot

Feature Selection based on Hybrid Binary Cuckoo Search and Rough Set Theory in Classification for Nominal Datasets

What points at this work

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

inferred← citeshttps://doi.org/10.2139/ssrn.4684455openalex-extracted

inferred← citeshttps://doi.org/10.1002/cpe.70732openalex-snapshot

PE Malware Detection via Optimized Static Features and Ensemble Learning

inferred← citeshttps://doi.org/10.1007/978-3-032-06703-6_46openalex-snapshot

Malware Detection for Cyber Security

inferred← citeshttps://doi.org/10.1007/978-3-032-27669-8_9openalex-snapshot

Hybrid SVM-RF Model to Enhance Intrusion Detection in Electronic-Vehicle Networks

inferred← citeshttps://doi.org/10.1007/978-981-99-8612-5_24openalex-snapshot

Enhancing Cyber Threat Intelligence and Security Automation: A Comprehensive Approach for Effective Protection

inferred← citeshttps://doi.org/10.1007/978-981-99-9718-3_1openalex-snapshot

From Evolution to Intelligence: Exploring the Synergy of Optimization and Machine Learning

inferred← citeshttps://doi.org/10.1016/j.cose.2024.103754openalex-snapshot

Agriculture 4.0 and beyond: Evaluating cyber threat intelligence sources and techniques in smart farming ecosystems

inferred← citeshttps://doi.org/10.1016/j.eswa.2026.134586openalex-snapshot

Cross-environment AI-based malware detection: A systematic review of Android applications, IoT ecosystems, and windows PE executables

inferred← citeshttps://doi.org/10.1038/s41598-025-26058-1openalex-snapshot

Nature-inspired swarm optimization paradigms for securing semantic web frameworks against DDoS attacks: a computational approach

inferred← citeshttps://doi.org/10.1038/s41598-025-31444-wopenalex-snapshot

A hierarchical deep learning framework with doubly regularized loss for robust malware detection and family categorization

inferred← citeshttps://doi.org/10.1038/s41598-025-85248-zopenalex-snapshot

An optimized LSTM-based deep learning model for anomaly network intrusion detection

inferred← citeshttps://doi.org/10.1109/assic60049.2024.10507929openalex-snapshot

An Effective Feed Forward Neural Network Model for Detection of Malware

inferred← citeshttps://doi.org/10.1109/cbdcom68404.2025.00026openalex-snapshot

Image Representation Based Malware Detection Using Transfer Learning

inferred← citeshttps://doi.org/10.1109/gcat59970.2023.10353495openalex-snapshot

Detection of Malware Using Machine Learning techniques on Random Forest, Decision Tree, KNeighbour, AdaBoost, SGD, ExtraTrees and GaussianNB Classifier

inferred← citeshttps://doi.org/10.1109/iccit68739.2025.11490307openalex-snapshot

Advanced Malware Detection Through Function Call Graph Analysis with Graph2Vec Embeddings and Graph Attention Networks

inferred← citeshttps://doi.org/10.1109/icsintesa68165.2025.11413710openalex-snapshot

Malware Classification Using Transfer Learning on Image Representations

inferred← citeshttps://doi.org/10.1109/spw67851.2025.00034openalex-snapshot

Reliable KMDF Instruction Set Generation for User Queries Based on Endogenous Generative LLMs

inferred← citeshttps://doi.org/10.15622/ia.23.3.2openalex-snapshot

Methodology for Collecting Data on the Activity of Malware for Windows OS Based on MITRE ATT&CK

inferred← citeshttps://doi.org/10.2139/ssrn.5143870openalex-snapshot

Cyber Threat Intelligence Sharing: Challenges and Opportunities

inferred← citeshttps://doi.org/10.28948/ngumuh.1811827openalex-snapshot

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Deep Learning Approach for Malware Classification and Threat Intelligence in Hospital Management

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Robust Malicious Executable Detection Using Host-Based Machine Learning Classifier

inferred← citeshttps://doi.org/10.32722/multinetics.v9i1.5578openalex-snapshot

Hyperparameter Tuning Menggunakan GridsearchCV pada Random Forest untuk Deteksi Malware

inferred← citeshttps://doi.org/10.3390/app13064060openalex-snapshot

An Efficient Boosting-Based Windows Malware Family Classification System Using Multi-Features Fusion

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A Novel Malware Detection Model in the Software Supply Chain Based on LSTM and SVMs

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Enhancing Cyber-Threat Intelligence in the Arab World: Leveraging IoC and MISP Integration

inferred← citeshttps://doi.org/10.3390/electronics14214196openalex-snapshot

Generation of a Multi-Class IoT Malware Dataset for Cybersecurity

inferred← citeshttps://doi.org/10.3390/fi16050168openalex-snapshot

Evaluating Realistic Adversarial Attacks against Machine Learning Models for Windows PE Malware Detection

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Intrusion Detection in Vehicle Controller Area Network (CAN) Bus Using Machine Learning: A Comparative Performance Study

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AOAFS: A Malware Detection System Using an Improved Arithmetic Optimization Algorithm

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A HYBRID DNN-DKN MODEL WITH MAPREDUCE FRAMEWORK FOR DETECTING MALICIOUS THREATS IN LARGE EXECUTABLE FILES

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