196 citations · 517 across the 5 of their papers we have counts for
6 papers
Detection of App Collusion Potential Using Logic Programming
Jorge Blasco, Thomas M. Chen, Igor Muttik +1
Android is designed with a number of built-in security features such as app sandboxing and permission-based access controls. Android supports multiple communication methods for app…
A New Android Malware Detection Approach Using Bayesian Classification
Suleiman Y. Yerima, Sakir Sezer, Gavin McWilliams +1
Mobile malware has been growing in scale and complexity as smartphone usage continues to rise. Android has surpassed other mobile platforms as the most popular whilst also witnessi…
High Accuracy Android Malware Detection Using Ensemble Learning
Suleiman Y. Yerima, Sakir Sezer, Igor Muttik
With over 50 billion downloads and more than 1.3 million apps in the Google official market, Android has continued to gain popularity amongst smartphone users worldwide. At the sam…
Android Malware Detection Using Parallel Machine Learning Classifiers
Suleiman Y. Yerima, Sakir Sezer, Igor Muttik
Mobile malware has continued to grow at an alarming rate despite on-going efforts towards mitigating the problem. This has been particularly noticeable on Android due to its being…
Android Malware Detection: an Eigenspace Analysis Approach
Suleiman Y. Yerima, Sakir Sezer, Igor Muttik
The battle to mitigate Android malware has become more critical with the emergence of new strains incorporating increasingly sophisticated evasion techniques, in turn necessitating…
Towards Automated Android App Collusion Detection
Irina Mariuca Asavoae, Jorge Blasco, Thomas M. Chen +5
Android OS supports multiple communication methods between apps. This opens the possibility to carry out threats in a collaborative fashion, c.f. the Soundcomber example from 2011.…