Search Results - (( network detection clustering algorithm ) OR ( java application optimization algorithm ))

A reinforcement learning-based energy-efficient spectrum-aware clustering algorithm for cognitive radio wireless sensor network by Mustapha, Ibrahim

“…In this thesis, a Reinforcement Learning (RL) based clustering algorithm is proposed to address energy and Primary Users (PUs) detection challenges in CR-WSN. …”
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An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks by Mustapha, Ibrahim, Mohd Ali, Borhanuddin, A. Rasid, Mohd Fadlee, Sali, Aduwati, Mohamad, Hafizal

“…We first model the network energy consumption and then determine the optimal number of clusters for the network. …”
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An Improved LEACH Algorithm Based On Fuzzy C-Means Algorithm And Distributed Cluster Head Selection Mechanism. by Hassan, Ali Abdul Hussian, Othman, Mohd Fairuz Iskandar, Md Shah, Wahidah, Husien, Ali Mohamed, Hassan, Hayder Abdul Hussien

“…The comparison of therecommended algorithm with LEACH algorithm is conducted, in relations to energy consumption and network lifetime. …”
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Development Of Human Skin Detection Algorithm Using Multilayer Perceptron Neural Network And Clustering Method by Al-Mohair, Hani Kaid Saif

“…Human skin detection is an important preprocessing step in many applications involving images such as face detection, gesture tracking, and nudity detection. …”
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Unsupervised Anomaly Detection with Unlabeled Data Using Clustering by Chimphlee, Witcha, Abdullah, Abdul Hanan, Md. Sap, Mohd. Noor

“…We present a clustering-based intrusion detection algorithm, unsupervised anomaly detection, which trains on unlabeled data in order to detect new intrusions. …”
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Cluster head selection using fuzzy logic and chaotic based genetic algorithm in wireless sensor network by Karimi, Abbas, Abedini, S. M., Zarafshan, Faraneh, Syed Mohamed, Syed Abdul Rahman Al-Haddad

“…As energy is a challenging issue in these networks, clustering models are used to overcome this problem. …”
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Improving K-Means Clustering Algorithm Using Discretization Technique in Network Intrusion Detection System (S/O: 13141) by Mohamad Tahir, Hatim, Ghazali, Osman, Katuk, Norliza, Zakaria, Nur Haryani, Omar, Mohd Hasbullah

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Combined generative adversarial network and fuzzy C-means clustering for multi-class voice disorder detection with an imbalanced dataset by Chui, K.T., Lytras, M.D., Vasant, P.

“…In this paper, a conditional generative adversarial network (CGAN) and improved fuzzy c-means clustering (IFCM) algorithm called CGAN-IFCM is proposed for the multi-class voice disorder detection of three common types of voice disorders. …”
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Text spam messages classification using Artificial Immune System (AIS) algorithms by Nurul Fadhilah Sulaiman

Integrating genetic algorithms and fuzzy c-means for anomaly detection by Chimphlee, Witcha, Abdullah, Abdul Hanan, Sap, Noor Md., Chimphlee, Siriporn, Srinoy, Surat

“…Clustering-based intrusion detection algorithm which trains on unlabeled data in order to detect new intrusions. …”
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Pairwise clusters optimization and cluster most significant feature methods for anomaly-based network intrusion detection system (POC2MSF) / Gervais Hatungimana by Hatungimana, Gervais

“…Most of researches in IDS which use k-centroids-based clustering methods like K-means, K-medoids, Fuzzy, Hierarchical and agglomerative algorithms to baseline network traffic suffer from high false positive rate compared to signature-based IDS, simply because the nature of these algorithms risk to force some network traffic into wrong profiles depending on K number of clusters needed. …”
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Hybrid intelligent approach for network intrusion detection by Al-Mohammed, Wael Hasan Ali

“…Due to the prevailing limitations of finding novel attacks, high false detection, and accuracy in previous intrusion detection approaches, this study has proposed a hybrid intelligent approach for network intrusion detection based on k-means clustering algorithm and support vector machine classification algorithm. …”
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A clustering-based method for outlier detection under concept drift by Tahir, Mahjabeen, Abdullah, Azizol, Udzir, Nur Izura, Kasmiran, Khairul Azhar

“…The proposed approach CADSD (Cluster-based Anomaly Detection with Streaming Data), operates in real-time without pre-training. …”
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Improving K-Means Clustering using discretization technique in Network Intrusion Detection System by Tahir, H.M., Said, A.M., Osman, N.H., Zakaria, N.H., Sabri, P.N.M., Katuk, N.

“…Network Intrusion Detection Systems (NIDSs) have always been designed to enhance and improve the network security issue by detecting, identifying, assessing and reporting any unauthorized and illegal network connections and activities. …”
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Data redundancy reduction scheme for data aggregation in wireless sensor network by Adawy, Mohammad Ibrahim

“…This research proposes Data Redundancy Reduction Scheme (DRRS) which includes three algorithms namely, Metadata Classification (MC), Selection Active Nodes (SAN) and Anomaly Detection (AD) algorithms that works before data aggregation, when multiple composite events simultaneously occur in the different locations within the cluster. …”
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A multi-view clustering algorithm for attributed weighted multi-edge directed networks by Khameneh, Azadeh Zahedi, Kilicman, Adem, Mahad, Zahari

“…Graph clustering acts as a critical topic for solving decision situations in networks. …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…Based on the above components and circumstances, many studies have been performed on data clustering problems. Despite attempts to solve the data clustering issues, there are also many variants of modified algorithms in traditional information clustering that attempt to solve issues such as clustering algorithms based on condensation. …”
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ChoCD : Usable and secure graphical password authentication scheme by Radhi Rafiee Bin Afandi

Energy-Aware Routing Hole Detection Algorithm in the Hierarchical Wireless Sensor Network by Najm Us, Sama, Kartinah, Zen, Atiq Ur, Rahman, Aziz Ud, Din

“…In this paper a novel energy efficient routing hole detection (EEHD) algorithm is presented, on the detection of routing hole, the periodic re-clustering is performed to avoid the long detour path. …”
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Reducing false alarm using hybrid Intrusion Detection based on X-Means clustering and Random Forest classification by Juma, Sundus, Muda, Zaiton, Yassin, Warusia

“…In recent times, Intrusion Detection systems (IDSs) incarnate the high network security. …”
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