We have developed a neural network for generic detection of a particular class of computer viruses-the so called boot sector viruses that infect the boot sector of a floppy disk or a hard drive. This is an important and relatively tractable subproblem of generic virus detection. Only about 5% of all known viruses are boot sector viruses, yet they account for nearly 90% of all virus incidents. We have successfully deployed our neural network as a commercial product, distributing it to millions of PC users worldwide as part of the IBM AntiVirus software package. We faced several challenges in taking our neural network from a research idea to a commercial product. These included designing an appropriate input representation scheme; dealing with the scarcity of available training data; finding an appropriate trade off point between false positives and false negatives to conform to user expectations; and making the software conform to strict constraints on memory and speed of computation needed to run on PCs. The article discusses our methods for handling these challenges
To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.