Amazon Technologies, Inc.

Sevag Demirjian

Blair Livingstone Hotchkies

Mark Evans Brighton

Forrest MacKenzie Vines

Samuel Charles Goodwin

John Lindsay Bates

Colin James Hawkett

Michael James McInerny

Jui Te Tseng

Nathan David Scott

Mohan Das Katragadda

Network resources are subject to automated downloading of information by automated-agents that cause business- or user-specific data to be compiled en masse. In order to control resources and information available to automated-agents, markup documents or elements of markup documents are obfuscated such that a client must reconfigure the obfuscated information in order to display the requested content contained in the document. The obfuscation is applied such that the content will render and display to a human user in the same manner as if the element was untransformed; however, the markup will appear syntactically different to an automated-agent. Thus, in response to a user request, a server can transform elements of a structured document and provide the transformed document to the client for reconfiguring and rendering.

Randomize markup to disturb scrapers

Service providers may operate one or more services configured to detect requests generated by automated agents. A CAPTCHA may be transmitted in response to requests generated by automated agents. The CAPTCHAs may be included in a modal pop-up box configured to be displayed by a client application displaying a webpage to a customer of the service provider. Furthermore, the CAPTCHAs included in the modal pop-up box may be rendered inactive and caused not to be displayed by client application executing the webpage. Submitted solutions to CAPTCHAs may be presented with a cookie that enables access to resources of the service provider without restriction. Cookies may be tracked and their use may be used to detect automated agent activity.

Token based automated agent detection

Web Bot detection methods and systems are provided that receive a request, in connection with a network session. The methods and systems determine whether the request is associated with potential Bot activity, and based thereon assign a Bot confidence designation. The Bot confidence designation indicates a likelihood that the request represents an agent-based request. The methods and systems analyze a session trait of the network session relative to predetermined session traits indicative of human-based requests, and assign a human confidence designation based on the analysis. The human confidence designation indicates a likelihood that the request represents a human-based request. The request is then classified to represent an agent-based request or human-based request based on the Bot and human confidence designations.

Web Bot detection and human differentiation

Current CAPTCHA tests are designed to be difficult for a bot and simple for a human-user to answer; however, as artificial intelligence improves, bots are more capable of using techniques such as optical character recognition to resolve current CAPTCHAs in similar manners as human-users. By providing a CAPTCHA challenge from a library or set of challenges that are designed in a manner that causes or likely causes a human-user to trivially get the answer to the challenge wrong, helps to confirm that a user is a human-user, as a bot would answer the challenge correctly.

Turing test via failure

Online retailers may operate one or more services configured to detect requests generated by automated agents. A CAPTCHA may be transmitted in response to requests generated by automated agents. The CAPTCHAs may be included in a modal pop-up box configured to be displayed by a client application displaying a webpage to a customer of the online retailer. Automated agents receiving the CAPTCHAs may not be blocked or otherwise restricted from the resources requested and therefore may not be configured to interact with the CAPTCHAs contained in the modal pop-up box.

Non-blocking automated agent detection

Embodiments of methods, systems and storage media associated with mitigating the effects of client-side (customer) bot-like activity caused by code injected into an e-commerce web page in the customer's browser after it is received from the e-commerce server system. Rather than entirely block a selected account or device (IP address) of a legitimate customer, a more politic process to mitigate the effects of bot-like scripts is implemented by embedding a 'protective script' into a web page before it is downloaded to a client device. The protective script intercepts attempts to inject new code into the page, and it may prevent the injection entirely, or modify the injected code to mitigate its impact, for example, by slowing down its operation. This process leaves the customer free to continue normal activities on the site without any adverse impact or penalty.

Client-side protective script to mitigate server loading

Online retailers may operate one or more services configured to detect requests generated by automated agents. A CAPTCHA may be transmitted in response to requests generated by automated agents. The CAPTCHAs may be included in a modal pop-up box configured to be displayed by a client application displaying a webpage to a customer of the online retailer. Furthermore, the CAPTCHAs included in the modal pop-up box may be rendered inactive and caused not to be displayed by client application executing the webpage. Rendering the CAPTCHAs inactive may provide an additional signal which may be sued to update one or more automated agent detection models.

Inactive non-blocking automated agent detection

Current CAPTCHA tests are designed to be difficult for a bot and simple for a human-user to answer; however, as artificial intelligence improves, bots are more capable of using techniques such as optical character recognition to resolve current CAPTCHAs in similar manners as human-users. By maintaining a library of security tests and/or questions based on products purchased by the human-user, and using those questions as a CAPTCHA challenge in order to determine if the user is a human-user on how the user responds, CAPTCHA challenges may be directed toward determining a human-user based on responses exhibiting humanity.

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Seattle, WA, United States of America

Sevag Demirjian