Web of science uf endnote android#

The Feasibility of Employing IEEE802.11p in Electronic-Based Congestion Pricing Zone: A Comparative Study with RFID 3 (2022): Malaysian Journal of Computer Science Malaysian Journal of Computer Science: Vol. GRANULAR NETWORK TRAFFIC CLASSIFICATION FOR STREAMING TRAFFIC USING INCREMENTAL LEARNING AND CLASSIFIER CHAIN 2 (2008): Malaysian Journal of Computer Science

Identifying False Alarm for Network Intrusion Detection System Using Hybrid Data Mining and Decision Tree

The experimental results also indicate a true positive rate as high as 99.94% and false positive of 0.06% for the knearest neighbour classifier. From the experiment, it is found that knearest neighbour provides the optimum results in terms of performance among the classifiers. Among various network traffic characteristics, three network features were selected: connection duration, TCP size and number of GET/POST parameters. The data sample is a collection of malwares gathered between August 2010 and October 2011 by the University of North Carolina.

Web of science uf endnote android#

The evaluation was validated using malware data samples from the Android Malware Genome Project. This study evaluates five machine learning classifiers, namely Naïve Bayes, k-nearest neighbour, decision tree, multi-layer perceptron, and support vector machine. Due to the proliferation of Android malwares, it is crucial to study the best classifiers that can detect these malwares effectively and accurately through selecting the most suitable network traffic features as well as comprehensive comparison with related works. Among the mobile operating systems, Android is the most popular due to its availability as an open source operating system.

They are employed for purposes beyond merely making phone calls. In recent years, mobile devices are ubiquitous.