Abstract: Automated classification of applications (“apps”) for mobile devices is provided. In some embodiments, automated classification of apps for mobile devices includes receiving an application (“app”); performing an analysis of the app using a classification engine; and determining an app category for the app based on the analysis performed using the classification engine.

Abstract: Automated classification of applications (“apps”) for mobile devices is provided. In some embodiments, automated classification of apps for mobile devices includes receiving an application (“app”); performing an analysis of the app using a classification engine; and determining an app category for the app based on the analysis performed using the classification engine.

Abstract: Quantifying the risks of applications (“apps”) for mobile devices is disclosed. In some embodiments, quantifying the risks of apps for mobile devices includes receiving an application for a mobile device; performing an automated analysis of the application based on a risk profile; and generating a risk score based on the automated analysis of the application based on the risk profile.

Abstract: Techniques for in-line filtering of insecure or unwanted mobile components or communications (e.g., insecure or unwanted behaviors associated with applications for mobile devices (“apps”), updates for apps, communications to/from apps, operating system components/updates for mobile devices, etc.) for mobile devices are disclosed. In some embodiments, in-line filtering of apps for mobile devices includes intercepting a request for downloading an application to a mobile device; and modifying a response to the request for downloading the application to the mobile device. In some embodiments, the response includes a notification that the application cannot be downloaded due to an application risk policy violation.

Abstract: Techniques for off-device anti-malware protection for mobile devices are disclosed. In some embodiments, off-device anti-malware protection for mobile devices includes receiving a software inventory for a mobile device, in which the software inventory identifies a plurality of applications installed on the mobile device; and determining whether one or more of the plurality of applications identified in the software inventory are associated with malware based on a policy. In some embodiments, the off-device anti-malware protection for mobile devices further includes enforcing the policy on the mobile device. In some embodiments, the off-device anti-malware protection for mobile devices is provided as a cloud service.

Abstract: Application malware filtering for advertising networks is disclosed. For example, techniques for providing a system and process for detecting malicious ad content (e.g., or other undesirable ad content) distributed by advertising (ad) networks are disclosed. In some embodiments, application (“app”) malware filtering for advertising networks includes receiving ad content; processing the ad content; and automatically determining whether the ad content is associated with a malicious app.

Abstract: Quantifying the risks of applications (“apps”) for mobile devices is disclosed. In some embodiments, quantifying the risks of apps for mobile devices includes receiving an application for a mobile device; performing an automated analysis of the application based on a risk profile; and generating a risk score based on the automated analysis of the application based on the risk profile.

Abstract: Techniques for in-line filtering of insecure or unwanted mobile components or communications (e.g., insecure or unwanted behaviors associated with applications for mobile devices (“apps”), updates for apps, communications to/from apps, operating system components/updates for mobile devices, etc.) for mobile devices are disclosed. In some embodiments, in-line filtering of apps for mobile devices includes intercepting a request for downloading an application to a mobile device; and modifying a response to the request for downloading the application to the mobile device. In some embodiments, the response includes a notification that the application cannot be downloaded due to an application risk policy violation.

Abstract: Automated classification of applications (“apps”) for mobile devices is provided. In some embodiments, automated classification of apps for mobile devices includes receiving an application (“app”); performing an analysis of the app using a classification engine; and determining an app category for the app based on the analysis performed using the classification engine.

Abstract: Application malware filtering for advertising networks is disclosed. For example, techniques for providing a system and process for detecting malicious ad content (e.g., or other undesirable ad content) distributed by advertising (ad) networks are disclosed. In some embodiments, application (“app”) malware filtering for advertising networks includes receiving ad content; processing the ad content; and automatically determining whether the ad content is associated with a malicious app.

Abstract: Techniques for off-device anti-malware protection for mobile devices are disclosed. In some embodiments, off-device anti-malware protection for mobile devices includes receiving a software inventory for a mobile device, in which the software inventory identifies a plurality of applications installed on the mobile device; and determining whether one or more of the plurality of applications identified in the software inventory are associated with malware based on a policy. In some embodiments, the off-device anti-malware protection for mobile devices further includes enforcing the policy on the mobile device. In some embodiments, the off-device anti-malware protection for mobile devices is provided as a cloud service.

Abstract: Quantifying the risks of applications (“apps”) for mobile devices is disclosed. In some embodiments, quantifying the risks of apps for mobile devices includes receiving an application for a mobile device; performing an automated analysis of the application based on a risk profile; and generating a risk score based on the automated analysis of the application based on the risk profile.

Abstract: Techniques for in-line filtering of insecure or unwanted mobile components or communications (e.g., insecure or unwanted behaviors associated with applications for mobile devices (“apps”), updates for apps, communications to/from apps, operating system components/updates for mobile devices, etc.) for mobile devices are disclosed. In some embodiments, in-line filtering of apps for mobile devices includes intercepting a request for downloading an application to a mobile device; and modifying a response to the request for downloading the application to the mobile device. In some embodiments, the response includes a notification that the application cannot be downloaded due to an application risk policy violation.

Abstract: Quantifying the risks of applications (“apps”) for mobile devices is disclosed. In some embodiments, quantifying the risks of apps for mobile devices includes receiving an application for a mobile device; performing an automated analysis of the application based on a risk profile; and generating a risk score based on the automated analysis of the application based on the risk profile.

Abstract: Quantifying the risks of applications (“apps”) for mobile devices is disclosed. In some embodiments, quantifying the risks of apps for mobile devices includes receiving an application for a mobile device; performing an automated analysis of the application based on a risk profile; and generating a risk score based on the automated analysis of the application based on the risk profile.

Abstract: Techniques for in-line filtering of insecure or unwanted mobile components or communications (e.g., insecure or unwanted behaviors associated with applications for mobile devices (“apps”), updates for apps, communications to/from apps, operating system components/updates for mobile devices, etc.) for mobile devices are disclosed. In some embodiments, in-line filtering of apps for mobile devices includes intercepting a request for downloading an application to a mobile device; and modifying a response to the request for downloading the application to the mobile device. In some embodiments, the response includes a notification that the application cannot be downloaded due to an application risk policy violation.

Abstract: Techniques for off-device anti-malware protection for mobile devices are disclosed. In some embodiments, off-device anti-malware protection for mobile devices includes receiving a software inventory for a mobile device, in which the software inventory identifies a plurality of applications installed on the mobile device; and determining whether one or more of the plurality of applications identified in the software inventory are associated with malware based on a policy. In some embodiments, the off-device anti-malware protection for mobile devices further includes enforcing the policy on the mobile device. In some embodiments, the off-device anti-malware protection for mobile devices is provided as a cloud service.

Abstract: Quantifying the risks of applications (“apps”) for mobile devices is disclosed. In some embodiments, quantifying the risks of apps for mobile devices includes receiving an application for a mobile device; performing an automated analysis of the application based on a risk profile; and generating a risk score based on the automated analysis of the application based on the risk profile.