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A Comparative Study of AI-Based Intrusion Detection Techniques in Critical Infrastructures
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/11538059_103openalex-snapshot
A Reinforcement Learning Approach for Host-Based Intrusion Detection Using Sequences of System Calls
inferredcites →https://doi.org/10.1007/3-540-46695-9_35openalex-snapshot
Q-Learning in Continuous State and Action Spaces
inferredcites →https://doi.org/10.1016/j.jpdc.2018.03.006openalex-snapshot
A scalable distributed machine learning approach for attack detection in edge computing environments
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.scs.2020.102080openalex-snapshot
Providing secure and reliable communication for next generation networks in smart cities
inferredcites →https://doi.org/10.1016/s0167-8655(00)00131-8openalex-snapshot
Two-phase clustering process for outliers detection
inferredcites →https://doi.org/10.1109/access.2017.2762418openalex-snapshot
A Deep Learning Approach for Intrusion Detection Using Recurrent Neural Networks
inferredcites →https://doi.org/10.1109/autest.2017.8080473openalex-snapshot
Testing automation for an intrusion detection system
inferredcites →https://doi.org/10.1109/iadcc.2009.4809235openalex-snapshot
An Enhanced Density Based Spatial Clustering of Applications with Noise
inferredcites →https://doi.org/10.1109/icc.2017.7997099openalex-snapshot
Hierarchical trust-based black-hole detection in WSN-based smart grid monitoring
inferredcites →https://doi.org/10.1109/iccci.2014.6921740openalex-snapshot
Performance evaluation of different intrusion detection system: An empirical approach
inferredcites →https://doi.org/10.1109/iwcmc.2016.7577152openalex-snapshot
An optimized weight-based clustering algorithm in wireless sensor networks
inferredcites →https://doi.org/10.1109/lsens.2017.2752719openalex-snapshot
Detection of Known and Unknown Intrusive Sensor Behavior in Critical Applications
inferredcites →https://doi.org/10.1109/mcom.2018.1700332openalex-snapshot
Deep Learning: The Frontier for Distributed Attack Detection in Fog-to-Things Computing
inferredcites →https://doi.org/10.1109/mwc.2010.5601957openalex-snapshot
Application of wireless sensor networks in critical infrastructure protection: challenges and design options [Security and Privacy in Emerging Wireless Networks
inferredcites →https://doi.org/10.1109/sahcn.2006.288409openalex-snapshot
A Trust Based Framework for Secure Data Aggregation in Wireless Sensor Networks
inferredcites →https://doi.org/10.1109/tii.2019.2922699openalex-snapshot
A Profitable and Energy-Efficient Cooperative Fog Solution for IoT Services
inferredcites →https://doi.org/10.1109/tsmc.2013.2294155openalex-snapshot
An MDP Model-Based Reinforcement Learning Approach for Production Station Ramp-Up Optimization: Q-Learning Analysis
inferredcites →https://doi.org/10.1109/tsmcc.2008.923876openalex-snapshot
Random-Forests-Based Network Intrusion Detection Systems
inferredcites →https://doi.org/10.1109/wimob.2005.1512887openalex-snapshot
Hierarchical dynamic source routing: passive forwarding node selection for wireless ad hoc networks
inferredcites →https://doi.org/10.1145/1654988.1655002openalex-snapshot
Active learning for network intrusion detection
inferredcites →https://doi.org/10.1145/3382770openalex-snapshot
Intelligent Control and Security of Fog Resources in Healthcare Systems via a Cognitive Fog Model
inferredcites →https://doi.org/10.1145/967900.967988openalex-snapshot
Unsupervised learning techniques for an intrusion detection system
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/10.23919/itu-wt.2018.8597682openalex-snapshot
DOUBLE SARSA BASED MACHINE LEARNING TO IMPROVE QUALITY OF VIDEO STREAMING OVER HTTP THROUGH WIRELESS NETWORKS
inferredcites →https://doi.org/10.24003/emitter.v2i1.16openalex-snapshot
Reinforced Intrusion Detection Using Pursuit Reinforcement Competitive Learning
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/10.5121/ijnsa.2012.4308openalex-snapshot
Multi Stage Filter Using Enhanced Adaboost for Network Intrusion Detection
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Cyber Security Intrusion Detection System Based on an Enhanced Gradient Boost Decision Trees with Cosine Kernel Support Vector Machine
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Defensive Machine Learning Methods and the Cyber Defence Chain
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A Tiny-BERT Transformer Model for Scalable and High-Performance Intrusion Detection
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Battling against cyberattacks: towards pre-standardization of countermeasures
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Denial of ARP spoofing in SDN and NFV enabled cloud-fog-edge platforms
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An Intelligent Tree-Based Intrusion Detection Model for Cyber Security
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Towards Model Generalization for Intrusion Detection: Unsupervised Machine Learning Techniques
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Deep learning-based network intrusion detection in smart healthcare enterprise systems
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TFCNet: Based on time-frequency domain and multi-channel analysis for Network security situation prediction
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Systematic survey of advanced metering infrastructure security: Vulnerabilities, attacks, countermeasures, and future vision
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A Survey on Blockchain for Information Systems Management and Security
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Attentional LSTM-ensemble architecture for intrusion detection in smart grids
inferred← citeshttps://doi.org/10.1080/1206212x.2023.2275084openalex-snapshot
MuDeLA: multi-level deep learning approach for intrusion detection systems
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Present and Future of Network Security Monitoring
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Reinforcement-Learning-Based Intrusion Detection in Communication Networks: A Review
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A Hybrid Masked MLP for Cyber Intrusion Detection in Sensor Network Domains
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Leveraging OpenStack-based Private Cloud for Intrusion Detection Using Deep Learning Techniques
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Transfer Learning-Driven Intrusion Detection for Internet of Vehicles (IoV)
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