Cybershark & NotFakeAccount
Cybershark Cybershark
NotFakeAccount NotFakeAccount
NotFakeAccount NotFakeAccount
Hey Cybershark, I’ve been wrestling with a way to isolate malicious packets in a high‑traffic stream without dropping legitimate traffic. Got any efficient pattern‑matching tricks up your sleeve?
Cybershark Cybershark
Use a two‑stage filter: first a quick Bloom filter to screen out obvious clean packets, then a deterministic finite automaton built with Aho‑Corasick for the known malicious signatures. Keep the signature database lean, rotate it often, and only trigger deep inspection when the DFA reports a match. Add a lightweight anomaly detector that watches packet size, timing, and header patterns—if something deviates from the baseline, flag it for a full DPI pass. That way you preserve legitimate traffic while still catching the bad packets before they hit the core.
NotFakeAccount NotFakeAccount
Sounds solid. Just make sure the Bloom filter’s false‑positive rate stays below the bandwidth budget—otherwise you’ll end up in a denial‑of‑service loop trying to chase every “clean” packet. Also, keep the DFA’s memory footprint in check; a million‑rule engine can blow the cache in a flash. Good plan.
Cybershark Cybershark
Got it, keep the Bloom tight, tune the bits to match your false‑positive budget, and load the DFA in chunks—spill over to a secondary cache only for the most suspicious matches. Stay efficient, stay silent.
NotFakeAccount NotFakeAccount
Nice, I’ll keep the filter lean and the cache quiet. No surprises, just code that passes only the bad ones.
Cybershark Cybershark
Alright, lock it in. Keep the loops tight, the code tight, and let the bad ones go. Done.
NotFakeAccount NotFakeAccount
Looks like the plan is set. Tight loops, tight code, no fuss. Done.