Search Results - (( attack detection service algorithm ) OR ( based optimization method algorithm ))
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A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network
Published 2023“…As a result, legitimate users are barred from utilizing the service from the MPLS network. This thesis proposes a hybrid ML-based intrusion detection system (ML-IDS) and ML-based intelligent routing algorithm (ML-RA) for MPLS network. …”
text::Thesis -
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Optimized Decision Forest for Website Phishing Detection
Published 2021“…Nonetheless, given the dynamism of phishing efforts, there is a constant requirement for novel and efficient website phishing detection solutions. In this study, an optimized decision forest (ODF) method for detecting website phishing is proposed ODF involves the use of a genetic algorithm (GA) for the selection of optimal diverse individual trees in a forest to generate an efficient sub-forest. …”
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An Enhanced Mechanism To Detect Drdos Attacks On Dns Using Adaptive Thresholding Technique
Published 2023“…By exploiting DNS flaws, cyber attackers conduct a Distributed Reflection Denial of Service (DRDoS) attack. …”
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4
Early detection and mitigation of DDoS attacks in software defined networks
Published 2018“…To detect and mitigate this attack at its early stages, an entropy-based DDoS attack detection and mitigation algorithm was proposed. …”
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Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm
Published 2021“…Proposed real-time training dataset for SVM algorithm achieved highest detection rate of 99.13% while decision tree and Naïve Bayes has 93.28% & 86.41% of attack detection rate, respectively. …”
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Cloud co-residency denial of service threat detection inspired by artificial immune system
Published 2024Subjects:journal::journal article -
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Cooperative multi agents for intelligent intrusion detection and prevention systems / Shahaboddin Shamshirband
Published 2014“…Owing to the distributed nature of modern attacks (e.g. denial-of-service), it is extremely challenging to detect such malicious behaviour using traditional intrusion detection systems. …”
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Ethereum blockchain-based three factor authentication and multi-contract access control for secure smart home environment in 5G networks
Published 2025“…The Adaptive Neuro-Fuzzy Inference System (ANFIS) is used for role-based access control and judge contracts. To improve secure service providing, we perform the detection of malicious and vulnerable users using Improved Cuckoo Optimization and Support Vector Machine (ICO-SVM) and Gated Recurrent Unit and Residual Neural Network (GRU-ResNNet) algorithm in ROS-EB which reduces the vulnerability in the smart home. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…It leads to network disturbances, interruption of communication and significant damage to services. Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…It leads to network disturbances, interruption of communication and significant damage to services. Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…It leads to network disturbances, interruption of communication and significant damage to services. Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…It leads to network disturbances, interruption of communication and significant damage to services. Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2023“…It leads to network disturbances, interruption of communication and significant damage to services. Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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Hybrid Classification Algorithm For Denial Of Service Attack Detection Using Rough Set Theory And Artificial Immune
Published 2024thesis::master thesis -
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Mitigating Slow Hypertext Transfer Protocol Distributed Denial of Service Attacks in Software Defined Networks
Published 2021“…This paper provides the scholarly community with an approach to boosting service availability in web servers under slow Hypertext Transfer Protocol (HTTP) DDoS attacks through attack detection using Genetic Algorithm and Support Vector Machine which facilitates attack mitigation in a Software-Defined Networking (SDN) environment simulated in GNS3. …”
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Cloud Co-Residency Denial of Service Threat Detection Inspired by Artificial Immune System
Published 2024“…The experiment was conducted in a controlled environment and conducted using custom generated co-residency denial of service attacks for testing the capability of the proposed model in detecting novel co-residency attacks. …”
Proceedings Paper -
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An Intelligence Technique For Denial Of Service (Dos) Attack Detection
Published 2017“…Therefore, this paper concern about Denial of Service (DoS) attack, detection using Neural Network. …”
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An intelligence technique for denial of service (DoS) attack detection
Published 2018“…Therefore, this paper concern about Denial of Service (DoS) attack, detection using Neural Network. …”
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Cloud co-residency denial of service threat detection inspired by artificial immune system
Published 2018“…The experiment was conducted in a controlled environment and conducted using custom generated co-residency denial of service attacks for testing the capability of the proposed model in detecting novel co-residency attacks. …”
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Proceeding Paper -
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Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system
Published 2022“…In future, the HW-DBN algorithm can be proposed as an integrated deep Learning for the classification performance of attack detection models.…”
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