2\ Their neural network has two components: a file analyzer, shown in the image below, which does a high-capacity, non-linear analysis of a file's features...pic.twitter.com/ZtHuGyeg1F
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1\ A file seen at "Downloads\svchost.exe" that doesn't *look* like svchost.exe *might* be a problem. Indeed, @Sophos AI's @adarshdk, @kberlin and @EthanMRudd show that a neural net that takes a file's path alongside its contents gets ~30% better detection. https://arxiv.org/pdf/1905.06987.pdf …pic.twitter.com/ITRKYAtJBe
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3\ And a character string / file path analyzer, which does a high-capacity analysis of file path strings...pic.twitter.com/kledM9doLx
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4\ These analyses are then merged so that reasoning about the file path in the context of the binary, and vice-versa, can take place. Good targets for detection are, for example, unsigned system utilities that have been replaced by very different looking files.pic.twitter.com/JYnQXAMZ1n
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5\ The result, as would be intuitive, is much better detection accuracy. Please see the paper for more info!pic.twitter.com/YnbBHyjHmd
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