A team at Wake Forest University is working on a genetic algorithm to proactively discover more secure computer configurations.
Genetic algorithms are search heuristics inspired by evolution and often used for optimization. They start with a population of solutions that are evaluated for fitness and then allowed to create offspring with a chance of mutation. The offspring then become the new population of solutions in the next run of the algorithm. During each cycle of the process, solutions that are determined to be more fit are given a greater chance to create offspring.
Funded by a grant from the Pacific Northwest National Laboratory (PNNL), Computer Science Professor Errin Fulp and graduate student Michael Crouse, are trying to use such an algorithm to “improve defense mechanisms of similar computing infrastructures with minimal human interaction,” according to information released by the university.
“Typically, administrators configure hundreds and sometimes thousands of machines the same way, meaning a virus that infects one could affect any computer on the same network,” said Crouse. “If successful, automating the ability to ward off attacks could play a crucial role in protecting highly sensitive data within large organizations.”
Read more at Campus Technology