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Deep learning algorithms for cyber security applications: A survey
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Botnet behaviour analysis: How would a data analytics‐based system with minimum a priori information perform?
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A deep learning approach for detecting malicious JavaScript code
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Machine learning in cybersecurity: A review
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A Hybrid Autoencoder and Density Estimation Model for Anomaly Detection
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Hybrid Intelligent Intrusion Detection Scheme
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Computer Supported Cooperative Work and Social Computing
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Semi-supervised machine learning approach for DDoS detection
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Cerberus, an Access Control Scheme for Enforcing Least Privilege in Patient Cohort Study Platforms
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Correlation Filters for Detection of Cellular Nuclei in Histopathology Images
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Malicious Domain Name Detection Based on Extreme Machine Learning
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The Analysis of Firewall Policy Through Machine Learning and Data Mining
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A machine learning based approach for phishing detection using hyperlinks information
inferredcites →https://doi.org/10.1016/j.asoc.2018.05.049openalex-snapshot
Semi-supervised learning based distributed attack detection framework for IoT
inferredcites →https://doi.org/10.1016/j.comnet.2018.05.018openalex-snapshot
USB side-channel attack on Tor
inferredcites →https://doi.org/10.1016/j.comnet.2018.07.025openalex-snapshot
An evaluation of the performance of Restricted Boltzmann Machines as a model for anomaly network intrusion detection
inferredcites →https://doi.org/10.1016/j.comnet.2018.07.028openalex-snapshot
A systematic evaluation of cybersecurity metrics for dynamic networks
inferredcites →https://doi.org/10.1016/j.comnet.2019.01.023openalex-snapshot
Internet of Things: A survey on machine learning-based intrusion detection approaches
inferredcites →https://doi.org/10.1016/j.compeleceng.2019.03.015openalex-snapshot
Identification of malicious code variants based on image visualization
inferredcites →https://doi.org/10.1016/j.cose.2017.10.011openalex-snapshot
Network intrusion detection system based on recursive feature addition and bigram technique
inferredcites →https://doi.org/10.1016/j.cose.2017.11.014openalex-snapshot
Intelligent agents defending for an IoT world: A review
inferredcites →https://doi.org/10.1016/j.cose.2019.04.018openalex-snapshot
A cost analysis of machine learning using dynamic runtime opcodes for malware detection
inferredcites →https://doi.org/10.1016/j.eswa.2017.09.053openalex-snapshot
Quantifying the resilience of machine learning classifiers used for cyber security
inferredcites →https://doi.org/10.1016/j.eswa.2018.05.031openalex-snapshot
Novel set of general descriptive features for enhanced detection of malicious emails using machine learning methods
inferredcites →https://doi.org/10.1016/j.eswa.2018.09.029openalex-snapshot
Machine learning based phishing detection from URLs
inferredcites →https://doi.org/10.1016/j.future.2018.06.055openalex-snapshot
Detection of advanced persistent threat using machine-learning correlation analysis
inferredcites →https://doi.org/10.1016/j.future.2019.01.022openalex-snapshot
A machine learning framework for investigating data breaches based on semantic analysis of adversary’s attack patterns in threat intelligence repositories
inferredcites →https://doi.org/10.1016/j.neucom.2012.11.050openalex-snapshot
Network anomaly detection with the restricted Boltzmann machine
inferredcites →https://doi.org/10.1016/j.neucom.2018.02.007openalex-snapshot
Data driven exploratory attacks on black box classifiers in adversarial domains
inferredcites →https://doi.org/10.1016/j.patcog.2016.11.003openalex-snapshot
A Survey on semi-supervised feature selection methods
inferredcites →https://doi.org/10.1016/j.robot.2017.10.006openalex-snapshot
Detection of Cyber-attacks to indoor real time localization systems for autonomous robots
inferredcites →https://doi.org/10.1017/atsip.2013.8openalex-snapshot
Depth video coding based on intra mode inheritance from texture
inferredcites →https://doi.org/10.1038/nature16961openalex-snapshot
Mastering the game of Go with deep neural networks and tree search
inferredcites →https://doi.org/10.1080/08839514.2019.1582861openalex-snapshot
A New Hybrid Machine Learning for Cybersecurity Threat Detection Based on Adaptive Boosting
inferredcites →https://doi.org/10.1080/19393555.2018.1456577openalex-snapshot
Deep belief network based detection and categorization of malicious URLs
inferredcites →https://doi.org/10.1109/access.2019.2892066openalex-snapshot
Phishing Website Detection Based on Multidimensional Features Driven by Deep Learning
inferredcites →https://doi.org/10.1109/access.2019.2895334openalex-snapshot
Deep Learning Approach for Intelligent Intrusion Detection System
inferredcites →https://doi.org/10.1109/access.2019.2906934openalex-snapshot
Robust Intelligent Malware Detection Using Deep Learning
inferredcites →https://doi.org/10.1109/access.2019.2912210openalex-snapshot
AC-Net: Assessing the Consistency of Description and Permission in Android Apps
inferredcites →https://doi.org/10.1109/access.2019.2913705openalex-snapshot
Phishing Email Detection Using Improved RCNN Model With Multilevel Vectors and Attention Mechanism
inferredcites →https://doi.org/10.1109/access.2019.2914311openalex-snapshot
Predicting the Impact of Android Malicious Samples via Machine Learning
inferredcites →https://doi.org/10.1109/cbd.2014.41openalex-snapshot
An Intrusion Detection Model Based on Deep Belief Networks
inferredcites →https://doi.org/10.1109/compsac.2016.151openalex-snapshot
Malware Detection with Deep Neural Network Using Process Behavior
inferredcites →https://doi.org/10.1109/compsac.2018.10315openalex-snapshot
Lightweight Classification of IoT Malware Based on Image Recognition
inferredcites →https://doi.org/10.1109/comst.2015.2494502openalex-snapshot
A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection
inferredcites →https://doi.org/10.1109/comst.2018.2800740openalex-snapshot
Detecting and Preventing Cyber Insider Threats: A Survey
inferredcites →https://doi.org/10.1109/comst.2018.2844341openalex-snapshot
Deep Learning for IoT Big Data and Streaming Analytics: A Survey
inferredcites →https://doi.org/10.1109/comst.2018.2847722openalex-snapshot
A Detailed Investigation and Analysis of Using Machine Learning Techniques for Intrusion Detection
inferredcites →https://doi.org/10.1109/comst.2018.2871866openalex-snapshot
Survey of Attack Projection, Prediction, and Forecasting in Cyber Security
inferredcites →https://doi.org/10.1109/etfa.2016.7733515openalex-snapshot
Accelerated deep neural networks for enhanced Intrusion Detection System
inferredcites →https://doi.org/10.1109/icmla.2016.0040openalex-snapshot
Toward an Online Anomaly Intrusion Detection System Based on Deep Learning
inferredcites →https://doi.org/10.1109/icrtit.2014.6996133openalex-snapshot
An impact analysis: Real time DDoS attack detection and mitigation using machine learning
inferredcites →https://doi.org/10.1109/jisic.2014.19openalex-snapshot
Identifying Top Sellers In Underground Economy Using Deep Learning-Based Sentiment Analysis
inferredcites →https://doi.org/10.1109/malware.2015.7413680openalex-snapshot
Deep neural network based malware detection using two dimensional binary program features
inferredcites →https://doi.org/10.1109/mc.2019.2913138openalex-snapshot
Security of Cyberphysical Systems: Chaining Induction and Deduction
inferredcites →https://doi.org/10.1109/mdat.2019.2899334openalex-snapshot
Context-Aware Intelligence in Resource-Constrained IoT Nodes: Opportunities and Challenges
inferredcites →https://doi.org/10.1109/mnet.2018.1700349openalex-snapshot
Deep Learning Based Inference of Private Information Using Embedded Sensors in Smart Devices
inferredcites →https://doi.org/10.1109/tasl.2011.2109382openalex-snapshot
Acoustic Modeling Using Deep Belief Networks
inferredcites →https://doi.org/10.1109/tcyb.2019.2940940openalex-snapshot
Data-Driven Cyber Security in Perspective—Intelligent Traffic Analysis
inferredcites →https://doi.org/10.1109/tpwrs.2018.2818746openalex-snapshot
Can Attackers With Limited Information Exploit Historical Data to Mount Successful False Data Injection Attacks on Power Systems?
inferredcites →https://doi.org/10.1109/tsg.2018.2859339openalex-snapshot
Distributed Framework for Detecting PMU Data Manipulation Attacks With Deep Autoencoders
inferredcites →https://doi.org/10.1109/tst.2016.7399288openalex-snapshot
Droiddetector: android malware characterization and detection using deep learning
inferredcites →https://doi.org/10.1109/wifs.2016.7823921openalex-snapshot
Single-image splicing localization through autoencoder-based anomaly detection
inferredcites →https://doi.org/10.1109/wiw.2016.040openalex-snapshot
Deep4MalDroid: A Deep Learning Framework for Android Malware Detection Based on Linux Kernel System Call Graphs
inferredcites →https://doi.org/10.1126/science.1127647openalex-snapshot
Reducing the Dimensionality of Data with Neural Networks
inferredcites →https://doi.org/10.1145/2975591openalex-snapshot
Detection of Rogue Certificates from Trusted Certificate Authorities Using Deep Neural Networks
inferredcites →https://doi.org/10.1145/3029806.3029823openalex-snapshot
Deep Android Malware Detection
inferredcites →https://doi.org/10.1145/3052973.3053009openalex-snapshot
Practical Black-Box Attacks against Machine Learning
inferredcites →https://doi.org/10.1155/2017/4975343openalex-snapshot
A DDoS Attack Detection Method Based on Hybrid Heterogeneous Multiclassifier Ensemble Learning
inferredcites →https://doi.org/10.1155/2018/4678746openalex-snapshot
Web Phishing Detection Using a Deep Learning Framework
inferredcites →https://doi.org/10.1155/2018/4943509openalex-snapshot
TR-IDS: Anomaly-Based Intrusion Detection through Text-Convolutional Neural Network and Random Forest
inferredcites →https://doi.org/10.1155/2018/5749481openalex-snapshot
Android Malware Characterization Using Metadata and Machine Learning Techniques
inferredcites →https://doi.org/10.1155/2018/6383145openalex-snapshot
Role of Machine Learning and Data Mining in Internet Security: Standing State with Future Directions
inferredcites →https://doi.org/10.1155/2018/6728020openalex-snapshot
Robust Fully Distributed Minibatch Gradient Descent with Privacy Preservation
inferredcites →https://doi.org/10.1155/2018/7247095openalex-snapshot
Detecting Malware with an Ensemble Method Based on Deep Neural Network
inferredcites →https://doi.org/10.1155/2019/2674684openalex-snapshot
A Feature Extraction Method of Hybrid Gram for Malicious Behavior Based on Machine Learning
inferredcites →https://doi.org/10.1155/2019/4656480openalex-snapshot
Optimizing Computer Worm Detection Using Ensembles
inferredcites →https://doi.org/10.1155/2019/8485365openalex-snapshot
Malware Detection on Byte Streams of PDF Files Using Convolutional Neural Networks
inferredcites →https://doi.org/10.1186/2190-8532-1-1openalex-snapshot
Detecting unknown malicious code by applying classification techniques on OpCode patterns
inferredcites →https://doi.org/10.12753/2066-026x-19-099openalex-snapshot
CURRENT TECHNOLOGIES AND TRENDS IN CYBERSECURITY AND THE IMPACT OF ARTIFICIAL INTELLIGENCE
inferredcites →https://doi.org/10.1371/journal.pone.0155781openalex-snapshot
Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security
inferredcites →https://doi.org/10.14257/ijsia.2015.9.5.21openalex-snapshot
A Hybrid Malicious Code Detection Method based on Deep Learning
inferredcites →https://doi.org/10.18844/ijire.v8i1.6445openalex-snapshot
Semi supervised machine learning approach for DDOS detection
inferredcites →https://doi.org/10.2352/issn.2470-1173.2017.7.mwsf-330openalex-snapshot
Autoencoder with recurrent neural networks for video forgery detection
inferredcites →https://doi.org/10.26483/ijarcs.v8i3.3146openalex-snapshot
Network Intrusion Anomaly Detection Using Radial Basis Function Networks
inferredcites →https://doi.org/10.26483/ijarcs.v8i9.4781openalex-snapshot
ANDROID MALWARE DETECTION USING HAML
inferredcites →https://doi.org/10.3233/jifs-169429openalex-snapshot
Evaluating deep learning approaches to characterize and classify malicious URL’s
inferredcites →https://doi.org/10.3390/fi10010001openalex-snapshot
A New Lightweight Watchdog-Based Algorithm for Detecting Sybil Nodes in Mobile WSNs
inferredcites →https://doi.org/10.3390/fi10080076openalex-snapshot
SCADA System Testbed for Cybersecurity Research Using Machine Learning Approach
inferredcites →https://doi.org/10.3390/s17010001openalex-snapshot
A Unified Framework for Street-View Panorama Stitching
inferredcites →https://doi.org/10.36001/phmconf.2015.v7i1.2655openalex-snapshot
On Accurate and Reliable Anomaly Detection for Gas Turbine Combustors: A Deep Learning Approach
inferredcites →https://doi.org/10.3837/tiis.2018.10.024openalex-snapshot
Feature Selection Algorithms in Intrusion Detection System: A Survey
inferredcites →https://doi.org/10.3837/tiis.2018.10.027openalex-snapshot
Using weighted Support Vector Machine to address the imbalanced classes problem of Intrusion Detection System
inferredcites →https://doi.org/10.4108/eai.3-12-2015.2262516openalex-snapshot
A Deep Learning Approach for Network Intrusion Detection System
inferredcites →https://doi.org/10.5555/1756006.1953039openalex-snapshot
Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Multimodal Data Fusion Defense Strategy for Campus Network Security: Research on Kolmogorov Arnold Networks Combined With B‐Spline Function
inferred← citeshttps://doi.org/10.1007/978-3-031-06791-4_16openalex-snapshot
Deep Learning Network Intrusion Detection Based on Network Traffic
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GRAPHSEC – Advancing the Application of AI/ML to Network Security Through Graph Neural Networks
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Enhancing cloud native security: a knowledge graph approach for securing container runtimes
inferred← citeshttps://doi.org/10.1007/s10791-025-09593-3openalex-snapshot
Multi modal data fusion defense strategy for campus network security: research on Kolmogorov Arnold Networks combined with B-spline function
inferred← citeshttps://doi.org/10.1016/j.eswa.2023.120965openalex-snapshot
TSGS: Two-stage security game solution based on deep reinforcement learning for Internet of Things
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Deep neural networks in the cloud: Review, applications, challenges and research directions
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A Computer Network Security Intrusion Detection Algorithm Based on Deep Learning
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Strategic Cyber Defense via Reinforcement Learning-Guided Combinatorial Auctions
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Research on Cyber Security Situation Awareness System Based on Knowledge Graph
inferred← citeshttps://doi.org/10.1109/punecon67554.2025.11378536openalex-snapshot
An Optimized ADASYN-OSS Data Balancing Approach with Wrapper-Based Feature Selection for Phishing Detection
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Deep Learning Neural Networks in the Cloud
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A Comprehensive Review of Large Language Models in Cyber Security.
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Research on the Impact of Combining Big Data and Deep Learning Technology on Network Security Information Security Protection
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Detecting and Mitigating Adversarial Attacks: Model Comparison Between Tree-Based and Deep Learning-Based Intrusion Detection Systems
inferred← citeshttps://doi.org/10.3233/jcs-230145openalex-snapshot
Evaluating the stealth of reinforcement learning-based cyber attacks against unknown scenarios using knowledge transfer techniques
inferred← citeshttps://doi.org/10.3233/jifs-213430openalex-snapshot
RETRACTED: Oversampling by genetic algorithm and k-nearest neighbors for network intrusion problem
inferred← citeshttps://doi.org/10.3390/math10060999openalex-snapshot
A Modified Grey Wolf Optimization Algorithm for an Intrusion Detection System
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Unified Cybersecurity Data Analytical Model for Smart Learning Operations
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Deep Learning in Cybersecurity: Applications, Challenges, and Future Prospects
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