A Smartphone Malware Detection Framework Based on Artificial Immunology

With the sharp increase in the number of smartphones, the Android platform pose to becoming a market leader that makes the need for malware analysis on this platform an urgent issue. The current Artificial Immune-Based malware detection systems research focus on traditional computers that uses information from OS or network, but the smartphone software behavior has its own structure and semantics. Current research cannot detect malware in smartphone exactly and efficiently. To address these problems, in this paper, we capitalize on earlier approaches for dynamic analysis of application behavior as a means for detecting malware in the smartphone. An Artificial Immune-Based Smartphone Malware Detection Framework is brought forwards and a prototype system is implemented, the experiment result show that the system can obtain higher detection rate and decrease the false positive rate.