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No, wait, I think I was right after all. Say we have a million urls, and a thousand of them are malicious. Our filter returns a positive result for all the mal
by hanoz 6y ago
No, wait, I think I was right after all.
Say we have a million urls, and a thousand of them are malicious. Our filter returns a positive result for all the malicious 1000 (no false negatives) and for the safe 999000 urls only 1% will return positive (low false positive), but that's still 9900 false positives. So a positive result only has a (1000 / (1000 + 9900)), i.e. 9%, chance of actually being malicious.
Even with a false positive result of only 0.1%, the probability of a positive result actually being malicious only rises to 50%, so still not in "high likelihood" territory.
- gopiandcode 6y agoNice example - you were right, my wording on that section was incorrect. sukilot quite nicely presents the error in my derivation - I guess I probably shouldn't try coming up with proofs on the spot - especially if they're not machine checked. I think what I probably should have said instead was that the low false positive rate means that only a small proportion of the honest URLs will be sent up.