Mobile applications create their own security and privacy models through permission based models. Applications, if they require to access any sensitive data in mobile devices that they are downloaded on, in order to do the needed system call for this access, they have to define only required permissions. However, some applications may request extra permissions which they do not need and may use these permissions for suspicious database access they do later. In this study, the aim is to determine those extra requested permissions and to use this on the security and privacy model. According to the study, through the determined methodology, risk values of applications are determined in the light of pre-determined levels within datasets. It is an approach that uses static analysis and code analysis together. According to this approach, the permissions that the applications request and use are determined separately and the applications that request extra permissions are discovered. Then, via the produced formula, suspicion value of every application is determined and applications are classified as malicious or benignant according to this value. This approach was applied on existing datasets; the results were compared and accuracy level was determined. For Android operating system, it is aimed to determine the malicious applications via this newly developed method and to create a safer Android atmosphere for users.