Search Results - (( based detection packet algorithm ) OR ( based optimization based algorithm ))

Privacy optimization and intrusion detection in modbus/tcp network-based scada in water distribution systems by Franco, Daniel Jose Da Graca Peceguina

“…Another problematic aspect is related to the intrusion detection solutions that are based on machine learning cluster algorithms to learn systems’ specifications and extract general state-based rules for attacks identification. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

“…Second, an Optimized time sliding window packet marker (OTSWTCM) algorithm. …”
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A novel selection of optimal statistical features in the DWPT domain for discrimination of ictal and seizure-free electroencephalography signals by Ong, Pauline, Zainuddin, Zarita, Kee, Huong Lai

“…Properly determining the discriminative features which characterize the inherent behaviors of electroencephalography (EEG) signals remains a great challenge for epileptic seizure detection. In this present study, a novel feature selection scheme based on the discrete wavelet packet decomposition and cuckoo search algorithm (CSA) was proposed. …”
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Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection by Ghanem, Waheed Ali Hussein Mohammed

“…Those problems lend themselves to the realm of optimization. Considering the wide success of swarm intelligence methods in optimization problems, the main objective of this thesis is to contribute to the improvement of intrusion detection technology through the application of swarm-based optimization techniques to the basic problems of selecting optimal packet features, and optimal training of neural networks on classifying those features into normal and attack instances. …”
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A novel selection of optimal statistical features in the DWPT domain for discrimination of ictal and seizure‑free electroencephalography signals by Ong, Pauline, Zainuddin, Zarita, Kee, Huong Lai

“…Properly determining the discriminative fea-tures which characterize the inherent behaviors of electro-encephalography (EEG) signals remains a great challenge for epileptic seizure detection. In this present study, a novel feature selection scheme based on the discrete wavelet packet decomposition and cuckoo search algorithm (CSA) was proposed. …”
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Efficient gear fault feature selection based on moth‑flame optimisation in discrete wavelet packet analysis domain by Ong, Pauline, Tieh, Tony Hieng Cai, Lai, Kee Huong, Lee, Woon Kiow, Ismon, Maznan

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Detection of black hole nodes in mobile ad hoc network using hybrid trustworthiness and energy consumption techniques by Mustafa, Ahmed Sudad

“…In this thesis, a hybrid detection algorithm mechanism has been proposed which combines two detection algorithms based on nodes’ trustworthiness and energy consumption in a parallel manner in order to detect the black hole nodes. …”
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Design and implementation of smart wireless campus network based on lora and wi-fi by Leong, Rong Chuan

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Performance optimization method in OFDM based on majorization and minimization technique by Al-Saadi, Alaa Abdullah, Latip, Rohaya, Muhammed, Abdullah

“…Phase Noise is considered a remarkable problem which causes significant degradation in detecting packet- based Orthogonal Frequency Division Multiplexing (OFDM) signals. …”
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Route optimization security in mobile IPv6 wireless networks: a test-bed experience by Mehdizadeh, Abbas, Khatun, Sabira, Mohd Ali, Borhanuddin, Raja Abdullah, Raja Syamsul Azmir, Kurup, Gopakumar

“…This algorithm is able to detect and prevent the attacker from modifying the data with using an encryption algorithm by cost of little bit increase but tolerable delay. …”
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New synchronization protocol for distributed system with TCP extension by Bayat, Peyman

“…The resulting algorithm does not involve variability in the hardware type nor is it based on specific distributed application software or databases. …”
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Security enhancement of route optimization in mobile IPv6 networks by Mehdizadeh, Abbas, Khatun, Sabira, Mohd Ali, Borhanuddin, Raja Abdullah, Raja Syamsul Azmir, Kurup, Gopakumar

“…This algorithm is able to detect and prevent the attacker from modifying the data with using an encryption algorithm by cost of little bit increase but tolerable delay. …”
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Real-time anomaly detection using clustering in big data technologies / Riyaz Ahamed Ariyaluran Habeeb by Riyaz Ahamed , Ariyaluran Habeeb

“…Based on the outcome of the analysis, this research proposed a novel framework namely real-time anomaly detection based on big data technologies (RTADBDT), along with supporting implementation algorithms. …”
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An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition by Al-Qammaz, Abdullah Yousef Awwad

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A reliable time base routing framework with seamless networking operation for SDN / Nauman Khan by Nauman , Khan

“…This thesis presents a preventive maintenance time-based routing framework (PMTRF) to optimize the recovery of data plane failures in SDN-based networks during maintenance, such as multiple links or switch failures. …”
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Performance enhancement of DCCP TCP - like over long delay link networks by Awang Nor, Shahrudin, Hassan, Suhaidi, Ghazali, Osman, M. Kadhum, Mohammed, Omar, Mohd Hasbullah

“…Instead of halving the current congestion window when congestion events are detected, the reduction of current congestion window drop has been shown to improve the DCCP TCP-like throughput with minimal drop packet percentage.…”
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Network instrusion prevention system ( NIPS) based on network intrusion detection system (NIDS) and ID3 algorithm decision tree classifier by Syurahbil, A

“…Network security has gained significant attention in research and industrial communities.Due to the increasing threat of the network intrusion,firewalls have become important elements of the security policy.Firewall performance highly depends toward number of rules,because the large more rules the consequence makes downhill performance progressively.Firewall can be allow or deny access network packets incoming and outgoing into Local Area Network(LAN),but firewall can not detect intrusion.To distinguishing an intrusion network packet or normal is very difficult and takes a lot of time.An analyst must review all the network traffics previously.In this study,a new way to make the rules that can determine network packet is intrusion or normal automatically.These rules implemented into firewall as prevention,which if there is a network packet that match these rules then network packet will be dropped.This is called Network Intrusion Prevention System(NIPS).These rules are generated based on Network Intrusion Detection System(NIDS)and Iterative Dichotomiser 3 (ID3)Algorithm Decision Tree Classifier,which as data training is intrusion network packet and normal network packets from previous network traffics.The experiment is successful,which can generate the rules then implemented into a firewall and drop the intrusion network packet automatically.Moreover,this way can minimize number of rules in firewall.…”
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Wormhole attack detection mechanism in mobile ad hoc network using neighborhood information and path tracing algorithm by Enshaei, Mehdi

“…In this study, a new defence mechanism is proposed based on modification of the packet forwarding process, using Neighborhood Information (NI) and PT algorithm, and known as NIPT algorithm. …”
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Anomaly behavior detection using flexible packet filtering and support vector machine algorithms by Abdul Wahid, Mohammed N.

“…FPF of SVM have merged the analyzed results of flexible packet filtering with support vector machine algorithm to get better classification of the captured network traffics and to detect anomalies. …”
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Industrial datasets with ICS testbed and attack detection using machine learning techniques by Mubarak, Sinil, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Balla, Asaad, Tahir, Mohammad, Elsheikh, Elfatih A A, Suliman, F M

“…The Machine learning (ML) techniques are deployed for cyber-attack detection of datasets from the cyber kit. The performance metrics such as accuracy, precision, recall, F1 score are evaluated and cross validated for different ML algorithms for anomaly detection. …”
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