English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Android Operating System is gettingpopular withmajority of users of the entire genre. Ever increasing mobile malware is a major threat to Android OS. Hence it is essential to add an extra security layer to android smart phone. Various malware detection techniques use Mutual Information or Information Gain for feature selection. Mutual Information calculates relevance of a feature and the class variable. Feature selection or ranking is crucial step before applying any machine learning classification algorithm on the preprocessed data. The proposed system uses improved mutual information feature selection (IMIFS) method to maximize relevance and minimize redundancy in the selected features. This improves the accuracy of the classification model. The proposed system will use features from manifest.xml as well as application code for malware detection. Bayesian Classification is used to develop classifier model to detect malicious applications before installation on the device.

An Innovative Technique to Detect Malicious Applications in Android