Search Results - (( java application customization algorithm ) OR ( security classification problems algorithm ))

ChoCD : Usable and secure graphical password authentication scheme by Radhi Rafiee Bin Afandi

Security alert framework using dynamic tweet-based features for phishing detection on twitter by Liew, Seow Wooi

“…This framework is divided into three phases which are classification model of phishing detection, detection algorithm of phishing tweet detection and security alert mechanism of phishing tweet detection. …”
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Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions by Gorment N.Z., Selamat A., Cheng L.K., Krejcar O.

“…The research investigates malware and machine learning in the context of cybersecurity, including malware detection taxonomy and machine learning algorithm classification into numerous categories. …”

Maldroid- attribute selection analysis for malware classification by Rahiwan Nazar, Romli, Mohamad Fadli, Zolkipli, Mohd Zamri, Osman

“…Hence, the objective of this paper is to find the most effective and efficient attribute selection and classification algorithm in malware detection. Moreover, in order to get the best combination between attribute selection and classification algorithm, eight attributes selection and seven categories machine learning algorithm are applied in this study. …”
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An enhanced classification framework for intrusions detection system using intelligent exoplanet atmospheric retrieval algorithm by Slamet, ., Izzeldin Ibrahim, Mohamed Abdelaziz

“…Regardless of the methods implemented by this system, eliminating false alerts is still a huge problem. To describe data traffic passing through the network, a database of the network security layer (NSL) knowledge discovery in database (KDD) dataset is used. …”
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A novel framework for identifying twitter spam data using machine learning algorithms by Maziku, Susana Boniphace, Abdul Rahiman, Amir Rizaan, Muhammed, Abdullah, Abdullah @ Selimun, Mohd Taufik

“…Previous studies have approached spam detection as a classification problem, high dimension, time-consuming problem, which requires new methods to address the problems. …”
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Diagnosis security problems in cloud computing for business cloud by Shakir M., Abubakar A.B., Yousoff Y.B., Sagher A.M., Alkayali H.

“…This paper aims to examine the security problems and to identify the characteristics of such security problems, in addition this study will examine the important issues in security cloud computing and will determine the frames to improve security systems for cloud computing. …”

Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection by Ghanem, Waheed Ali Hussein Mohammed

“…Those problems lend themselves to the realm of optimization. …”
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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.

“…However, the problem of improving the accuracy and efficiency of classification models remains open and yet to be resolved. …”
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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

Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques by AHMAD, IFTIKHAR

“…Based on the selected features, the classification is performed. The Support Vector Machine (SVM) and Multilayer Perceptron (MLP) are used for classification purpose due to their proven ability in classification. …”
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An enhanced classification framework for intrusions detection system using intelligent exoplanet atmospheric retrieval by Slamet, Slamet, Izzeldin, Ibrahim Mohamed Abdelaziz

“…Regardless of the methods implemented by this system, eliminating false alerts is still a huge problem. To describe data traffic passing through the network, a database of the network security layer (NSL) knowledge discovery in database (KDD) dataset is used. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

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An efficient anomaly intrusion detection method with evolutionary neural network by Sarvari, Samira

“…Several directions can be taken to extend this work such as a combination of an IDS with the IPS system to be capable of dropping or blocking network connections that are determined too risky, extend the model for multi-class classification problems and using hybrid IDS (combining anomaly and signature-based detection systems) to respond to wider ranges of intrusions and increase the level of security of a network.…”
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Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques by Iftikhar , Ahmad, Azween, Abdullah

“…Based on the selected features, the classification is performed. The Support Vector Machine (SVM) and Multilayer Perceptron (MLP) are used for classification purpose due to their proven ability in classification. …”
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SVM for network anomaly detection using ACO feature subset by Mehmood, T., Rais, H.B.M.

“…But irrelevant and redundant features are the obstacle for classification algorithm to build an efficient detection model. …”
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Revolutionizing Perimeter Intrusion Detection: A Machine Learning-Driven Approach with Curated Dataset Generation for Enhanced Security by Pitafi, S., Anwar, T., Dewa Made Widia, I., Yimwadsana, B.

“…After collecting the data from above mentioned sensors we applied machine learning algorithms DBSCAN to cluster the data points and K-NN classification to classify those clusters in one-dimensional data, but the results were not much satisfying. …”
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Review of the machine learning methods in the classification of phishing attack by Jupin, John Arthur, Sutikno, Tole, Mohd Arfian, Ismail, Mohd Saberi, Mohamad, Shahreen, Kasim, Deris, Stiawan

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Spam classification based on supervised learning using grasshopper optimization algorithm and artificial neural network by Mumtazimah, Mohamad, Engku Fadzli Hasan, Syed Abdullah, Ghaleb, S.A.A., Ghanem, W.A.H.M.

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Optimalisation of a job scheduler in the grid environment by using fuzzy C-mean by Lorpunmanee, Siriluck, Abdullah, Abdul Razak

“…Grid computing is the principle in utilizing and sharing large-scale resources to solve complex scientific problems. Under this principle, Grid environment has problems in flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions, and resources. …”
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