In the last ten years, using biology as a source of inspiration has become widespread in long-term research for security in information technology. The reason is that problems faced by distributed computer systems when under attack are reminiscent of those that their biological counterparts have had to deal with (and find solutions for) throughout their evolution. Indeed, pathogens attempting to invade an organism, or a population of organisms, have probably been around from the very beginning of life on earth, and with them, the vital necessity to limit the damage they cause.
This can be done in two different ways either by keeping the invader in check at the individual level, or by preventing it from compromising the survival of the entire population. Similarly, two main currents can be distinguished in bio-inspired IT security one focused on the microscopic level (immune response), the other on macroscopic dynamics (epidemic control).
An illustration of the microscopic approach can be found in the seminal work by Stephanie Forrest et al [1] on artificial immune systems. The primary aim of this research is to devise strategies to successfully and efficiently discriminate between the equivalents of self and non-self in very large sets of heterogeneous data. This would typically be achieved by training a population of antigens that would only match bit-strings that are totally absent from uncontaminated files. The main advantage of this approach is that, in theory, it would be able to identify unforeseen modifications, thereby pointing...
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