Napadi na sajber bezbednost: koji skup podataka treba koristiti za evaluaciju sistema za detekciju upada?

Ključne reči: ADFA, AWID, CAIDA, CIC-IDS-2017, CSE-CIC-2018, DARPA, ISCX 2012, KDD Cup ’99, Kyoto 2006 , NSL-KDD, UNSW-NB15

Sažetak


Uvod: Analiza velikih skupova podataka koji se koriste za detekciju upada postaje istraživački izazov. U radu su predstavljeni najčešće korišćeni skupovi podataka. ADFA sadrži dva skupa podataka sa zapisima iz Linux-a i Unix-a. AWID je zasnovan na realnoj normalnoj aktivnosti i aktivnosti upada u IEEE 802.11 Wi-Fi mrežu. CAIDA sadrži podatke sa geografskih i topološki različitih regiona. CIC-IDS-2017 je bazirana na protokolima: HTTP, HTTPS, FTP, SSH i email. CSE-CIC-2018 uključuje apstraktne modele distribucije za aplikacije, protokole i mrežne entitete nižeg nivoa. DARPA sadrži podatke o mrežnom saobraćaju. ISCX 2012 je skup podataka različitih višestepenih napada i stvarnog mrežnog saobraćaja sa pozadinskim šumom. KDD Cup ‘99 je simulirana baza podataka virtualnog mrežnog okruženja. Kyoto 2006+ sadrži zapise realnog mrežnog saobraćajai koristi se isključivo za detekciju anomalija. NSL-KDD koriguje probleme iz KDD Cup ’99 izazvane redundantnim zapisima i duplikatima. UNSW-NB-15 nastaje kombinacijom realnog i sintetizovanog saobraćaja koji opisuje aktivnosti tipa napada na mrežni saobraćaj.

Metode: Ovaj rad koristi kvalitativnu i kvantitativnu tehnologiju. Razmatrane su naučne reference i javno dostupne informacije o datim bazama podataka.

Rezultati: Baze podataka se često simuliraju da bi bili ispunjeni ciljevi koje zahteva određena organizacija. Broj realnih baza podataka je veoma mali u poređenju sa simuliranim bazama podataka. Detekcija anomalija danas se retko koristi.

Zaključak: Prikazane su glavne karakteristike i komparativna analiza skupova podataka u pogledu datuma nastanka, veličine, broja atributa, vrste saobraćaja i namene.

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Objavljeno
2023/12/04
Rubrika
Originalni naučni radovi