Many significant breaches have resulted from adversaries knowing who to target, how to target them and where to target them. Most corporations are not effectively using the largest collection of targeting data that is available on the public internet and fail to build and refine data driven threat models using the information that our adversaries are using against us. Targeted User Analytics and Human Honeypots is a research project I am working on to identify and model targeting methods with the hope of tipping the scales in our favor to defend our networks, users and critical systems. LinkedIn is the largest collection of Business Social Networking data available to “unathenticated” persons on the public internet. With the right techniques this data can be mined to identify and enrich targets. The purpose of my talk is to present targeting techniques through a use case and to demonstrate the value of other enrichment methods involving data sets that are widely available or collected from corporate security tools. The end result is analytics that predict who will be targeted and why they are more likely to be compromised if they are targeted. This will allow for proactive action to be taken to defend users and our assets.