Abstract: Disclosed herein are methods and systems for evaluating web browser behavior to report on human versus non-human activity, based on varying analyses of detectable properties. By passively detecting the code of a webpage engaged by a browsing user, the present invention evaluates the browsing user's activity in order to predict the type of user with a degree of confidence. The predictions are formed by acquiring information on how a user loads, navigates, and interacts with a webpage and comparing that information with known and unknown properties in various control groups. If the prediction yields a high likelihood of automated activity, additional active detection may be performed. Reports are compiled by analysis servers and made available to the operators of webpages. By compiling performance metrics and informing operators of fraudulent versus normal activity, the invention combats malicious automated traffic directed at any aspect of a given webpage.

Abstract: Disclosed herein are methods and systems for new analytic pathways for collecting information regarding video playback by human (and automated) users. This is achieved in part by placing certain elements (Vixels) within the code of a video file prior to it being uploaded by a user who shares the video. Whenever and wherever the video is played, whether it is streamed once, downloaded and played several times thereafter, or played for a mass audience, the analytic pathway is triggered each and every time the video file is played because the elements triggering the collection of analytics exist in the video file itself. By embedding Vixels into video files at or before upload, the analytics mechanisms are triggered by the embedded Vixel regardless of how, where, when, and by whom the video is played back, forming the framework for a simpler and more accurate analytics network.

Abstract: A computer-implemented method and system for the validation of a true browsing user on a website is disclosed. The invention allows for the collection of data regarding the evolving threat landscape created by online attackers. The system and method fingerprint user behavior to detect differences between a local user, a remote/foreign user, and an automated script. The system then covertly transmits that information back to a financial institution client without giving online attackers the opportunity to notice such transmittal. Certain embodiments of the invention also correspond with the browsing user to validate their identity. The claimed system and method proactively reveal attackers and attack ploys, additionally enabling institutions and security consultants to adapt to attacks in an automated fashion.

Abstract: A method for determining if a web browser is being operated by a human or a non-human agent, based on analysis of certain aspects of how a user interacts with a webpage. By placing a code snippet into the code of a webpage prior to a given user accessing that webpage, one is able to evaluate the user's actions in order to predict the type of user. The predictions are made by acquiring information on how the user loads, navigates, and interacts with the webpage and comparing that information with statistics taken from a control group. Performance metrics from all webpages containing similar code elements are compiled by analysis servers and made available to the operator of a webpage through a variety of reporting mediums. By compiling such performance metrics, the method helps combat and prevent malicious automated traffic directed at advertisements and other aspects of a given webpage.