Search Results - (( wave optimization method algorithm ) OR ( attack detection sensor algorithm ))
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Detecting sybil attacks in clustered wireless sensor networks based on energy trust system (ETS)
Published 2017“…Then, a trust algorithm is applied based on the energy of each sensor node. …”
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Presentation attack detection for face recognition on smartphones: a comprehensive review
Published 2017“…Face Presentation Attack Detection through the sensor level technique involved in using additional hardware or sensor to protect recognition system from spoofing while feature level techniques are purely software-based algorithms and analysis. …”
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Cooperative multi agents for intelligent intrusion detection and prevention systems / Shahaboddin Shamshirband
Published 2014“…This thesis evaluates the proposed solution using flooding attacks in wireless sensor networks (i.e. a type of DDoS attack). …”
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Thesis -
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
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A study on advanced statistical analysis for network anomaly detection
Published 2005“…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
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Monograph -
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Energy-efficient intrusion detection in wireless sensor network
Published 2012“…Attacks can occur from any direction and any node in WSNs, so one crucial security challenge is to detect networks' intrusion. …”
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Conference or Workshop Item -
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ETERS: A comprehensive energy aware trust-based efficient routing scheme for adversarial WSNs
Published 2021“…However, a trust-based attack detection algorithm (TADA) assesses the reliability of SNs to detect internal attacks. …”
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Inversion Of Surface Wave Phase Velocity Using New Genetic Algorithm Technique For Geotechnical Site Investigation
Published 2011“…Therefore the use of genetic algorithm (GA) optimization technique which is one of nonlinear optimization methods is an appropriate choice to solve surface wave inversion problem having high nonlinearity and multimodality. …”
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Cyber attacks analysis and mitigation with machine learning techniques in ICS SCADA systems
Published 2019“…Mitigation techniques such as honeypot simulation which helps in vulnerability assessment, along with machine learning algorithms, suitable for intrusion detection and prevention of cyber-attacks in SCADA systems has been detailed.…”
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Optimizing the efficiency of Oscillating Water Column (OWC) wave energy converter using genetic algorithm
Published 2015“…This paper, describes a method to maximize the pneumatic system efficiency using optimization technique based on Genetic algorithm. …”
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Secure and Energy-Efficient Data Aggregation Method Based on an Access Control Model
Published 2019“…The secure node authentication algorithm prevents attacks from accessing the network. …”
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Machine learning-based anomaly detection in NFV: a comprehensive survey
Published 2023“…It proposes the utilization of anomaly detection techniques as a means to mitigate the potential risks of cyber attacks. …”
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Low computational complexity for optimizing energy efficiency in mm-wave hybrid precoding system for 5G
Published 2021“…We propose effective alternating minimization algorithms based on the zero gradient method to establish fully-connected structures (FCSs) and partially-connected structures (PCSs). …”
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Low computational complexity for optimizing energy efficiency in mm-wave hybrid precoding system for 5G
Published 2021“…We propose effective alternating minimization algorithms based on the zero gradient method to establish fully-connected structures (FCSs) and partially-connected structures (PCSs). …”
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Modelling of intelligent intrusion detection system: making a case for snort
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Proceeding Paper -
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks
Published 2023“…The RNN, CNN, LSTM, and CNN-BiLSTM are implemented and tested to determine the most effective model against DDoS attacks that can accurately detect and distinguish DDoS from legitimate traffic. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks
Published 2023“…The RNN, CNN, LSTM, and CNN-BiLSTM are implemented and tested to determine the most effective model against DDoS attacks that can accurately detect and distinguish DDoS from legitimate traffic. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks
Published 2023“…The RNN, CNN, LSTM, and CNN-BiLSTM are implemented and tested to determine the most effective model against DDoS attacks that can accurately detect and distinguish DDoS from legitimate traffic. …”
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