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Future antivirus software should be very effective if this approach is fully realized. In some tests, deep learning has resulted in 20 percent higher detection than existing solutions.
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.
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.