Search Results - (( java optimization search 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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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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Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions
Published 2022“…Metaheuristic algorithms have been used successfully for solving different optimization problems. …”
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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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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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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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A random search based effective algorithm for pairwise test data generation
Published 2011“…This paper proposes an effective random search based pairwise test data generation algorithm named R2Way to optimize the number of test cases. …”
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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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An efficient detection of Sinkhole attacks using machine learning: impact on energy and security
Published 2025“…In the realm of Wireless Sensor Networks (WSNs), the detection and mitigation of sinkhole attacks remain pivotal for ensuring network integrity and efficiency. …”
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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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Modelling of intelligent intrusion detection system: making a case for snort
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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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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