--Data analytics and machine learning techniques are being rapidly adopted into the power system, including power system control as well as electricity market design. In this paper, from an adversarial machine learning point of view, we examine the vulnerability of data-driven electricity market design. More precisely, we follow the idea that consumer's load profile should uniquely determine its electricity rate, which yields a clustering oriented pricing scheme. We first identify the strategic behaviors of malicious users by defining a notion of disguising. Based on this notion, we characterize the sensitivity zones to evaluate the percentage of malicious users in each cluster . Based on a thorough cost benefit analysis, we conclude with the vulnerability analysis.

"A reasoned, even cournterempathic analysis of moral obligation and likely consequences is a better guide to planning for the future than the gut wrench of empathy." This is the argument presented by Paul Bloom in his latest book, Against Empathy. He argues that a more fair and reliable guide for one's morality is rational compassion; a morality based on facts, cost/benefit analysis and rational thinking. For the most part, I agree with him. I think back to all of the conflicts that I have witnessed or been engaged in, whether with friends, colleagues or family.