This research paper presents MLDroid—a web-based framework—which helps to detect
malware from Android devices. Due to increase in the popularity of Android devices …

Machine learning advances have been extensively explored for implementing large-scale
malware detection. When reported in the literature, performance evaluation of machine …

With the exponential growth in Android apps, Android based devices are becoming victims
of target attackers in the “silent battle” of cybernetics. To protect Android based devices from …

As a result of the rapid advancement of mobile and internet technology, a plethora of new
mobile security risks has recently emerged. Many techniques have been developed to …

Implementation of malware detection using Artificial Intelligence (AI) has emerged as a
significant research theme to combat evolving various types of malwares. Researchers …

Stacked Generalization has been assessed and evaluated in the field of Phishing URLs
detection. This field has become egregious area of information security. Recently, different …

With more than three million applications already in the Android marketplace, various
malware detection systems based on machine learning have been proposed to prevent …

In the area of sentiment analysis and classification, the performance of the classification
tasks can be varied based on the usage of text vectorization and feature extraction methods …

In the field of information security, phishing URLs detection and prevention has recently
become egregious. For detecting, phishing attacks several anti-phishing systems have …

N-gram techniques usually used in Natural Language Processing (NLP). Those techniques
along with stacked generalization has been experimented and assessed in the field of …