Abstract: The embodiments include methods and systems for detecting advertising fraud in a computing device by monitoring information received in a receiver component of the computing device, monitoring information received in a render component of the computing device, comparing the information received in the receiver component to the information received in the render component to generate comparison results, using the comparison results to determine whether there are discrepancies between the received information and the rendered information, and performing fraud prevention operations in response to determine that there are discrepancies between the received information and the rendered information. The fraud prevention operations may include dropping a connection to cease receiving the information in the receiver component, sending negative or position feedback to the service provider or a security server, and performing other similar operations.

Abstract: Methods, systems and devices for identifying, classifying, modeling, and responding to mobile device behaviors may include using lightweight processes to monitor and analyze various conditions and device behaviors to detect an instance of a non-benign behavior, increasing a level of security or scrutiny to identify other instances of non-benign behavior, and notifying select computing devices of the increased security risk so that they may also increase their security/scrutiny levels. For example, a computing device may be configured to perform a first type of analysis operations (e.g., lightweight analysis operations) to determine whether there is an increased security risk, and perform a second type of analysis operations (e.g., robust analysis operations) in response to determining that there is an increased security risk to determine whether there are additional security risks that are different from the security risk detected via the performance of the first type of analysis operations.