Hello, I'm
Brian Wilcox.

I lead cross functional teams that use AI to solve the formerly impossible.

Leveraging over a decade of experience, I've both founded companies and worked for the Fortune 100. As a results oriented product leader, I am proud that each and every day, over half a billion people use products I've helped to build.

Today, I primarily focus on building products that use AI to solve the formerly impossible, with a specialization in adversarial spaces such as information security, and anti-fraud.

I have experience in several industries: technology start-ups, finance, enterprise software, public safety, online food ordering, consumer software (mobile, web), and security. I help to identify and advance commercial opportunities for AI at the intersection of security and usability, and where anti-fraud can fuel healthy growth. History of cultivating human-in-the-loop learning systems, and intelligent feedback loops.

Sole inventor of two patents in the deep learning and security spaces:

Enhanced techniques for generating and deploying dynamic false user accounts (US10601868B2)

Technologies described herein facilitate generating and deploying dynamic false user accounts. Embodiments disclosed herein obtain a false tenant model that is usable to dynamically populate a false user account with messages and/or data files. Rather than containing only a static set of documents, a “dynamic” false user account is continually populated with fresh documents. This results in dynamic false user accounts appearing practically indistinguishable from real user accounts that are continually populated with new real email messages and/or new real hosted files as they are used by account owners to perform legitimate business activities. The realistic nature of the dynamic false user accounts described herein significantly reduces the ability of malicious entities to identify a user account as being false in nature.

Category - Countermeasures against malicious traffic using deception as countermeasure, e.g. honeypots, honeynets, decoys or entrapment.

Systems and methods for polluting phishing campaign responses (US20200053120A1)

Techniques for polluting phishing campaign responses with content that includes fake sensitive information of a type that is being sought in phishing messages. Embodiments disclosed herein identify phishing messages that are designed to fraudulently obtain sensitive information. Rather than simply quarantining these phishing messages from users' accounts to prevent users from providing “real” sensitive information, embodiments disclosed herein analyze these phishing messages to determine what type(s) of information is being sought and then respond to these phishing messages with “fake” sensitive information of these type(s). For example, if a phishing message is seeking sensitive credit card and/or banking account information, some fake information of this type(s) may be generated and sent in response to the phishing message. In various implementations, a natural language processing (NLP) model may be used to analyze the phishing message and/or generate a response thereto.

Category - Countermeasures against malicious traffic using deception as countermeasure, e.g. honeypots, honeynets, decoys or entrapment.

Interested in working together? Reach out.