Computer science professor Dr. Ryan Garlick of University of North Texas has a very interesting setup for his symbolic processing course this semester: Each student’s objective is to contribute towards cracking the unsolved 340-character Zodiac cipher.
From a UNT news article:
Cracking the cipher is a difficult task for more than one reason, which is why Garlick, along with his students, are currently developing several computer software techniques that will hopefully make the process far more feasible.
“There are just too many possible keys to look at them all,” Garlick said. “There are 63 different symbols, and each can represent 26 possible letters (we think), which is just too many possible combinations to evaluate them all.”
This is where the computer techniques they are fashioning will hopefully come in handy. Corey Rosemurgy, an Austin senior and computer science major in Garlick’s class, is currently developing a genetic algorithm to solve the cipher.
“The genetic algorithm that I am developing models itself after the inherent properties of biological evolution and the theory of survival of the fittest where only the strong survive,” Rosemurgy said.
I was very interested to discover this course, since I have been working on a similar approach since around March of this year. In my free time (what little there is), I’ve been running experiments using ECJ, a Java-based evolutionary computing framework. So far, my focus has been on trying to get the algorithm to solve Zodiac’s 408-character cipher, which has a known solution. Using a dictionary-oriented approach, the algorithm was able to find the correct solution using a limited 400-word dictionary. Now I am trying to improve this by adding more words to the dictionary used by the algorithm. The basic idea is to get this test case working well before attempting to have it solve the really difficult 340-character cipher. This has proven to be very difficult, because the search space (number of possible solutions) is extremely large, and there is exactly one correct solution. The needle is tiny, and the haystack is vast. Evolutionary computing methods tend to be better-suited for finding really good solutions, rather than the one best solution, so this approach is quite challenging (if not flawed).
I’m glad that many people are still working on this problem; it would be nice to finally find a solution. Still, there is still a strong possibility that there is no solution, and the cipher is just gibberish designed to keep people unnecessarily busy. If so, then the Zodiac killer succeeded beyond his wildest dreams.
More info:
article | course page (of interest here are the syllabus and powerpoint presentation) | google code page and code repository for zodiac decoder software (this is the repository of software used and developed by students in the course)
16 responses to “Can evolution reveal a killer’s mind?”