http://arstechnica.com/news.ars/post/20071017-comp-sci-researchers-use-economic-theory-to-disrupt-malware-black-markets.html

This article by Justin Berka discusses an interesting campaign underway by researchers from Carnegie Mellon University, the International Computer Science Institute, and the University of California, San Diego. The goal is to analyze and befuddle online black market interactions.

According to Berka, the researchers employ two similar strategies to choke Black Market trade. Both methods operate by creating false “signals”, which are “transfer[s] of information between the parties in [a] market”. By either posting misleading information about individuals (a “slander attack”), or by creating false identities, the researchers aim to destroy the credibility of illegal transactions.

This project invokes interesting issues in light of our classwork. In particular, it involves our work on trade theory. In our discussions, we have only lightly touched upon the concept of credibility; in this model, however, credibility is paramount. In terms of our class models, credibility may be likened to a player’s expected payoff. The greater the credibility of a trader, the more likely a buyer or seller is to receive his end of the deal. Conversely, low credibility means that there is a greater chance that a trader (by which I mean a buyer or seller, not an intermediary) will be cheated, or simply have a bad experience. The latter case corresponds to a decrease in expected payoff, which is essentially the goal of this research project.

If the researcher’s activity makes other buyers or sellers seem less credible, the apparent expected payoff to a trader would decrease. The introduction of fake traders, on the other hand, would actually decrease the reliability of the black market’s interactions, and consequently a trader’s expected payoff as well.

Both of these forces exert a potentially global influence upon the market. If enough fake traders and enough “slander attacks” infiltrate a market, it can cast a shadow upon the market as a whole. Although this possibility exists, one must consider the nature of the players in a black market. I posit that players in such a market are somewhat reckless, perhaps even irrational. After all, how trustworthy can illegally operating traders be, much less a whole market of them? And what if one was caught? These two considerations seem to point to a certain daring nature that would characterize traders in a black market.

In our third assignment, we considered the effect of an irrational player in an auction. It seemed that the net effect of an irrational player was a decrease in expected payoff for all bidders in the auction. If we extend this example to a Black Market where traders can be considered irrational, the ploys of the researchers seem less effective. Someone who already hurts their expected payoffs may not be overly concerned with low credibility. Or perhaps such a person has established a well-known network of traders (a sub-set of the market) already. The latter case would allow a trader to better navigate the increased complexity of a Black Market under siege by the researchers. In any case, I feel that the initiative is clever and will likely enact some effect upon illicit trade, due to a decrease in expected payoffs.