Search Results - (( based optimization method algorithm ) OR ( attack detection clustering algorithm ))

Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…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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An improved hybrid learning approach for better anomaly detection by Mohamed Yassin, Warusia

“…Nonetheless, current anomaly detection techniques are unable to detect all types of attacks accurately and correctly. …”
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ETERS: A comprehensive energy aware trust-based efficient routing scheme for adversarial WSNs by Khan, T., Singh, K., Hasan, M.H., Ahmad, K., Reddy, G.T., Mohan, S., Ahmadian, A.

“…However, a trust-based attack detection algorithm (TADA) assesses the reliability of SNs to detect internal attacks. …”
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Anomaly-based intrusion detection through K-means clustering and naives Bayes classification by Mohamed Yassin, Warusia, Udzir, Nur Izura, Muda, Zaiton, Sulaiman, Md. Nasir

“…Anomaly-based intrusion detection methods, which employ machine learning algorithms, are able to identify unforeseen attacks. …”
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Anomaly-based intrusion detection through K-Means clustering and Naives Bayes classification by Yassin, Warusia, Udzir, Nur Izura, Muda, Zaiton, Sulaiman, Md Nasir

“…Intrusion detection systems (IDSs) effectively balance extra security appliance by identifying intrusive activities on a computer system, and their enhancement is emerging at an unexpected rate.Anomaly-based intrusion detection methods, which employ machine learning algorithms, are able to identify unforeseen attacks. …”
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Detecting sybil attacks in clustered wireless sensor networks based on energy trust system (ETS) by Alsaedi, Noor, Hashim, Fazirulhisyam, Sali, Aduwati, Rokhani, Fakhrul Zaman

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KM-NEU: an efficient hybrid approach for intrusion detection system by Lisehroodi, Mazyar Mohammadi, Muda, Zaiton, Yassin, Warusia, Udzir, Nur Izura

“…The anomaly-based Intrusion Detection Systems (IDS) are able to detect unknown attacks. …”
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Global and local clustering soft assignment for intrusion detection system: a comparative study by Mohd Rizal Kadis, Azizi Abdullah

“…The ability of IDS to detect new sophisticated attacks compared to traditional method such as firewall is important to secure the network. …”
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Anomaly-based intrusion detection using fuzzy rough clustering by Chimphlee, Witcha, Abdullah, Abdul Hanan, Sap, M. N. M, Srinoy, Surat, Chimphlee, Siriporn

“…It is an important issue for the security of network to detect new intrusion attack and also to increase the detection rates and reduce false positive rates in Intrusion Detection System (IDS). …”
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A keypoint based copy-move forgery detection and localization in digital images / Somayeh Sadeghi by Somayeh, Sadeghi

“…Furthermore, the detection rate of the algorithm is improved by utilizing the proposed clustering procedure. …”
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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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Hybrid of fuzzy clustering neural network over NSL dataset for intrusion detection system by Ahmad Zainaddin, Dahlia Asyiqin, Mohd Hanapi, Zurina

“…In recent years, data mining approach for intrusion detection have been advised and used. The approach such as Genetic Algorithms , Support Vector Machines, Neural Networks as well as clustering has resulted in high accuracy and good detection rates but with moderate false alarm on novel attacks. …”
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A hybrid framework based on neural network MLP and means clustering for intrusion detection system by Lisehroodi, Mazyar Mohammadi, Muda, Zaiton, Yassin, Warusia

“…Concerning the robustness of K-means method and MLP algorithms benefits, this research is the part of an effort to develop a hybrid information detection system (IDS) which is able to detect high percentage of novel attacks while keep the false alarm at low rate.This paper provides the conceptual view and a general framework of the proposed system.…”
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Hybrid intelligent approach for network intrusion detection by Al-Mohammed, Wael Hasan Ali

“…Hence, there must be substantial improvement in network intrusion detection techniques and systems. 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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RFID-enabled supply chain detection using clustering algorithms by Azahar, T.F., Mahinderjit-Singh, M., Hassan, R.

“…We will apply various clustering algorithms to analyzed and determine every attribute in the dataset structure pattern. …”
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A hybrid framework based on neural network MLP and K-means clustering for intrusion detection system by Lisehroodi, Mazyar Mohammadi, Muda, Zaiton, Yassin, Warusia

“…Concerning the robustness of K-means method and MLP algorithms benefits, this research is the part of an effort to develop a hybrid information detection system (IDS) which is able to detect high percentage of novel attacks while keep the false alarm at low rate. …”
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ChoCD : Usable and secure graphical password authentication scheme by Radhi Rafiee Bin Afandi

A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works by Gorment N.Z., Selamat A., Krejcar O.

“…Barium compounds; Cybersecurity; Data mining; Decision trees; Evolutionary algorithms; K-means clustering; Learning algorithms; Malware; Network security; Sodium compounds; Support vector machines; 'current; Comparatives studies; Cyber security; K-means; Machine learning algorithms; Malware attacks; Malware detection; Metaheuristic; Recent researches; Systematic literature review; Nearest neighbor search…”

Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

“…Detecting cyber-security attacks is still a challenging task. …”
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Text spam messages classification using Artificial Immune System (AIS) algorithms by Nurul Fadhilah Sulaiman