Evading anti-virus software isn’t exactly easy, but if malware authors have a mind to do so, they can design their malware to mutate in such a way that anti-virus software can’t keep up. That’s why an Israeli startup by the name of Deep Instinct is developing an artificial neural network, which is essentially software that mimics the human brain, that can identify all kinds of malware just by looking at them, which means no amount of mutation will prevent them from being identified.
Computer malware can often evade antivirus security software if the author changes a few lines of code or designs the program to automatically mutate before each new infection. Artificial neural networks, trained to recognize the characteristics of malicious code by looking at millions of examples of malware and non-malware files, could perhaps offer a far better way to catch such nefarious code. An approach known as deep learning, which involves training a network with many layers of simulated neurons using huge quantities of data, is being tested by several companies. An Israeli startup called Deep Instinct plans to launch an antivirus service based on the approach in the coming months. The company claims that its software is significantly better at catching modified versions of existing malware than current antivirus software. Those claims have yet to be independently verified, but others are exploring the use of deep learning for antivirus software, and their published results suggest it could help turn the tide in the battle against malware infections.
