Search Results - (( based classification system algorithm ) OR ( attack detection method algorithm ))

Immune Multiagent System for Network Intrusion Detection using Non-linear Classification Algorithm by Mohamed, M. E, Samir, B. B., Azween, Abdullah

“…In this work, we integrate artificial immune algorithm with non-linear classification of pattern recognition and machine learning methods to solve the problem of intrusion detection in network systems. …”
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

“…The algorithms involved were Genetic Algorithm, Differential Evolution Algorithm, Particle Swarm Optimization, Butterfly Optimization Algorithm, Teaching-Learning-Based Optimization Algorithm, Harmony Search Algorithm and Gravitational Search Algorithm. …”
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An analysis of intrusion detection classification using supervised machine learning algorithms on NSL-KDD dataset / Sarthak Rastogi ... [et al.] by Rastogi, Sarthak, Shrotriya, Archit, Singh, Mitul Kumar, Potukuchi, Raghu Vamsi

“…Anomaly based intrusion detection is a type of intrusion detection system that identifies anomalies. …”
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Security alert framework using dynamic tweet-based features for phishing detection on twitter by Liew, Seow Wooi

“…This model is then embedded into the detection algorithm together with the inclusion of dynamic tweet-based features which are not as part of the features used to train a classification model for phishing tweet detection. …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…Moreover, shortage of reliable methods on a new dataset for the intrusion detection system and anomaly detection in terms of classification is an issue. …”
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Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System by Ali, Mohammed Hasan, Mohamed Fadli, Zolkipli

“…As network attackers keep changing their methods of attack execution to evade the deployed intrusion-detection systems (IDS), machine learning (ML) algorithms have been introduced to boost the performance of the IDS. …”
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An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons by Ghanem, Waheed Ali H. M., Aman, Jantan, Ahmed Ghaleb, Sanaa Abduljabbar, Naseer, Abdullah B.

“…This study proposes a new binary classification model for intrusion detection, based on hybridization of Artificial Bee Colony algorithm (ABC) and Dragonfly algorithm (DA) for training an artificial neural network (ANN) in order to increase the classification accuracy rate for malicious and non-malicious traffic in networks. …”
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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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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level by Hasan Mahmoud Sha'ban Kanaker

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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Compression Header Analyzer Intrusion Detection System (CHA - IDS) for 6LoWPAN Communication Protocol by Napiah, Mohamad Nazrin, Idris, Mohd Yamani Idna, Ramli, Roziana, Ahmedy, Ismail

“…These features are then tested using six machine learning algorithms to find the best classification method that able to distinguish between an attack and non-attack and then from the best classification method, we devise a rule to be implemented in Tmote Sky. …”
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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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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

“…However, these algorithms often fall short in consistently detecting and classifying network intrusions, particularly when distinctions between classes are subtle or when facing evolving attack patterns. …”
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Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques by Farhan, Farhan Abdel-Fattah Ahmad

“…In the past decades, machine learning methods have been successfully used in several intrusion detection methods because of their ability to discover and detect novel attacks. …”
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Image authentication using Zernike moment watermarking by Shojanazeri, Hamid

“…The adding or replacing a portion of the image is regarded as malicious attacks and rejected by this algorithm. Using two different watermarks lead to a good classification of incidental and malicious modifications and locating the tampered areas. …”
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File integrity monitor scheduling based on file security level classification by Abdullah, Zul Hilmi, Udzir, Nur Izura, Mahmod, Ramlan, Samsudin, Khairulmizam

“…System files are common targets by the attackers. …”
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Metaheuristic based ids using multi-objective wrapper feature selection and neural network classification by Ghanem, W.A.H.M, El-Ebiary, Y.A.B., Abdulnab, M., Tubishat, M., Alduais, N.A.M., Nasser, A.B., Abdullah, N., Al-wesabi, O.A.

“…This article proposes a cyber-intrusion detecting system classification with MLP trained by a hybrid metaheuristic algorithm and feature selection based on multi-objective wrapper method. …”
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Transformer-Based Model for Malicious URL Classification by Do N.Q., Selamat A., Lim K.C., Krejcar O., Ghani N.A.M.

Cyber attacks analysis and mitigation with machine learning techniques in ICS SCADA systems by Mubarak, Sinil, Habaebi, Mohamed Hadi, Abdul Rahman, Farah Diyana, Khan, Sheroz, Islam, Md Rafiqul

“…The advancement in technology for connectivity in communication protocols has resulted the system to be more vulnerable to cyber-attacks. The classifications of various attacks along with the intrusions detection methods have been highlighted. …”
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