Search Results - attack detection ((using algorithm) OR (((mining algorithm) OR (learning algorithm))))

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…”

Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions by Gorment N.Z., Selamat A., Cheng L.K., Krejcar O.

“…Furthermore, the taxonomy was used to evaluate the most recent machine learning algorithm and analysis. …”

Improving intrusion detection using genetic algorithm by Hashemi, V. Moraveji, Muda, Zaiton, Yassin, Warusia

“…To overcome this problem, a genetic algorithm approach is proposed. Genetic Algorithm (GA) is most frequently employed as a robust technology based on machine learning for designing IDS. …”
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A simultaneous spam and phishing attack detection framework for short message service based on text mining approach by Mohd Foozy, Cik Feresa

“…Additionally, the proposed framework also can detect the attack simultaneously using text mining approaches.…”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…Experiments demonstrate and prove that the proposed EBPSO method produces better accuracy mining data and selecting subset of relevant features comparing other algorithms. …”
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Intrusion detection system for the internet of things based on blockchain and multi-agent systems by Liang, Chao, Shanmugam, Bharanidharan, Azam, Sami, Karim, Asif, Islam, Ashraful, Zamani, Mazdak, Kavianpour, Sanaz, Idris, Norbik Bashah

“…The results demonstrate the efficiency of deep learning algorithms when detecting attacks from the transport layer. …”
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A Cryptojacking Detection System With Product Moment Correlation Coefficient (Pmcc) Heatmap Intelligent by Kong, Jun Hao

“…Because the number of cryptojacking attacks is on the rise, this project use machine learning to detect cryptojacking. …”
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An efficient attack detection for Intrusion Detection System (IDS) in internet of medical things smart environment with deep learning algorithm by Abdulkareem, Fatimah Saleem, Mohd Sani, Nor Fazlida

“…To achieve this, we measured the performance of three deep learning algorithms for normal and abnormal detection of IDS, and a comparison was made to select the best performance of the deep learning algorithm for detection in IDS, such as RNN, DBN and CNN. …”
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An improved hybrid learning approach for better anomaly detection by Mohamed Yassin, Warusia

“…In recent years, data mining approach for intrusion detection have been proposed and used such as neural networks, clustering, genetic algorithms, decision trees, and support vector machines. …”
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Phishing attack detection using machine learning method by Jupin, John Arthur

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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

“…Most of the currently existing intrusion detection systems (IDS) use machine learning algorithms to detect network intrusion. …”
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Malware Classification and Detection using Variations of Machine Learning Algorithm Models by Andi Maslan, Andi Maslan, Abdul Hamid, Abdul Hamid

“…The purpose of the study is to detect, classify malware attacks using a variety of ML Algorithm models such as SVM, KNN and Neural Network and testing detection performance. …”
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Cooperative multi agents for intelligent intrusion detection and prevention systems / Shahaboddin Shamshirband by Shamshirband, Shahaboddin

“…We investigate the detection capability based on the fuzzy Q-learning (FQL) algorithm and evaluate it using distribute denial of service attacks (DDoS). …”
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Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm by Jama, Abdirisaq M., Khalifa, Othman Omran, Subramaniam, Nantha Kumar

“…IP-PBX face challenges in detecting and mitigating malicious traffic. In this research, Support Vector Machine (SVM) machine learning detection & prevention algorithm were developed to detect this type of attacks Two other techniques were benchmarked decision tree and Naïve Bayes. …”
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Machine learning algorithms in context of intrusion detection by Mehmood, T., Rais, H.B.Md.

“…These machine learning algorithms develop a detection model in a training phase. …”
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An evaluation on KNN-SVM algorithm for detection and prediction of DDoS attack by Yusof, Ahmad Riza’ain, Udzir, Nur Izura, Selamat, Ali

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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

“…Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. The present study proposes an efficient DDoS attack detection model. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A.

“…Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. The present study proposes an efficient DDoS attack detection model. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Ahmed Dheyab, Saad, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

“…Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. The present study proposes an efficient DDoS attack detection model. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

“…Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. The present study proposes an efficient DDoS attack detection model. …”
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