Abstract: Disclosed herein are systems and methods for categorizing an application on a computing device including gathering a set of attributes of an application. The set of attributes of the application includes at least one of: a number of files in an application package of the application; a number of executable files in the application package; numbers and types of permissions being requested; a number of classes in the executable files in the application package; and a number of methods in the executable files in the application package. sending the gathered set of attributes to a trained classification model. The application is classified, using the classification model, based on the gathered set of attributes by generating one or more probabilities of the application belonging to respective one or more categories of applications. A category of the application is determined based on the generated one or more probabilities.

Abstract: Disclosed herein are systems and methods for categorizing an application on a computing device including gathering a set of attributes of an application. The set of attributes of the application includes at least one of: a number of files in an application package of the application; a number of executable files in the application package; numbers and types of permissions being requested; a number of classes in the executable files in the application package; and a number of methods in the executable files in the application package. sending the gathered set of attributes to a trained classification model. The application is classified, using the classification model, based on the gathered set of attributes by generating one or more probabilities of the application belonging to respective one or more categories of applications. A category of the application is determined based on the generated one or more probabilities.

Abstract: Disclosed herein are systems and methods for categorizing an application on a computing device. In one aspect, an exemplary method comprises, obtaining results of a classification of an application from a security server, when the results of the classification satisfy rules of relevance, designating the results of the classification as relevant and determining a category of the application based on the designation of the results as relevant, and when the results of the classification do not satisfy the rules of relevance, performing at least one of: terminating the categorization of the application, and updating the classification of the application based on a set of attributes of the application.

Abstract: Disclosed herein are systems and methods for categorizing an application on a computing device. In one aspect, an exemplary method comprises, obtaining results of a classification of an application from a security server, when the results of the classification satisfy rules of relevance, designating the results of the classification as relevant and determining a category of the application based on the designation of the results as relevant, and when the results of the classification do not satisfy the rules of relevance, performing at least one of: terminating the categorization of the application, and updating the classification of the application based on a set of attributes of the application.

Abstract: Disclosed are system, method and computer program product for detecting malicious files on mobile devices. An example method includes: analyzing a file to identify classes and methods contained in said classes; identifying a bytecode array for each identified method; determining instructions contained in each method by identifying a corresponding operation code from the bytecode array of each method; dividing the determined instructions for each method into a plurality of groups based on similarity of functionality among said instructions; forming a vector for each method on the basis of the results of the division of the instructions into the plurality of groups; comparing the formed vectors with a plurality of vectors of known malicious files to determine a degree of similarity between the compared vectors; and determining whether the analyzed file is malicious or clean based on the degree of similarity between the compared vectors.

Abstract: Disclosed are system, method and computer program product for detecting malicious files on mobile devices. An example method includes: analyzing a file to identify classes and methods contained in said classes; identifying a bytecode array for each identified method; determining instructions contained in each method by identifying a corresponding operation code from the bytecode array of each method; dividing the determined instructions for each method into a plurality of groups based on similarity of functionality among said instructions; forming a vector for each method on the basis of the results of the division of the instructions into the plurality of groups; comparing the formed vectors with a plurality of vectors of known malicious files to determine a degree of similarity between the compared vectors; and determining whether the analyzed file is malicious or clean based on the degree of similarity between the compared vectors.