Search Results - (( based classification using algorithm ) OR ( attack detection using algorithm ))

Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

“…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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Immune Multiagent System for Network Intrusion Detection using Non-linear Classification Algorithm by Mohamed, M. E, Samir, B. B., Azween, Abdullah

“…The algorithm tested use KDD Cup dataset and the result shows a significant improvement in detection accuracy and reducing the false alerts …”
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Hybrid Classification Algorithm For Denial Of Service Attack Detection Using Rough Set Theory And Artificial Immune by Fatin Norsyafawati, Mohd Sabri

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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A New Mobile Botnet Classification based on Permission and API Calls by Yusof, M, Saudi, MM, Ridzuan, F

“…This new classification can be used as the input for mobile botnet detection for future work, especially for financial matters.…”

An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

“…The experiment was executed by using k-fold cross validation techniques for predicting the classification algorithm performance. …”
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A new mobile botnet classification based on permission and API calls by Yusof M., Madihah Mohd Saudi, Farida Hazwani Mohd Ridzuan

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

“…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. …”
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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.

“…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. …”
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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

“…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. …”
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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

“…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. …”
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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

“…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. …”
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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

“…The IDS with machine learning method improves the detection accuracy of the security attacks. To this end, this paper studies the classification analysis of intrusion detection using various supervised learning algorithms such as SVM, Naive Bayes, KNN, Random Forest, Logistic Regression and Decision tree on the NSL-KDD dataset. …”
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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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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level by Hasan Mahmoud Sha'ban Kanaker

Crytojacking Classification based on Machine Learning Algorithm by Mansor W.N.A.B.W., Ahmad A., Zainudin W.S., Kama M.N., Madihah Mohd Saudi

Hybrid intelligent approach for network intrusion detection by Al-Mohammed, Wael Hasan Ali

“…Clustering is the last step of processing before classification has been performed, using k-means algorithm. …”
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SVM for network anomaly detection using ACO feature subset by Mehmood, T., Rais, H.B.M.

“…This paper proposes a detection model, ant system with support vector machine, which uses ant system, a variation of ant colony optimization, to filter out the redundant and irrelevant features for support vector machine classification algorithm. …”
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Android Mobile Malware Surveillance Exploitation via Call Logs: Proof of Concept by Madihah Mohd Saudi, Farida Hazwani Mohd Ridzuan, Nurlida Basir, Sakinah Ali Pitchay, Nabila N.F., Ahmad I.N.

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

“…In fact a data clustering method is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on our proposed algorithm; which is Enhanced Binary Particle swarm Optimization (EBPSO), (ii) To mine data using various data chunks (windows) and overcome a failure of single clustering. …”
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