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Napadi na algoritme za
strojno učenje
Simon.Belak@hekovnik.si
@sbelak
Hek.si konferenca 18. 4. 2014
CV Dazzle
Strojno učenje je
povsod
zaznava udorov
zaznava goljufij
zaznava zlonamerne kode
ocene tveganja
HFTpostavljanje diagnoz
SPAM filtri
zaznava terorističnih zarot
logistično planiranje
Szegedy et al.: Intriguing properties of neural networks
• 100 % napačna klasifikacija
• Posplošitev čez modele
• Posplošitev čez učne podatke
Zakaj?
Razvozlavanje in
nezveznosti
Zastrupljanje učenja
Biggio et al.: Poisoning Attacks against Support Vector Machines
Koliko informacij ima
napadalec?
• algoritem
• hiperparametri
• značilke
• učni podatki
• porazdelitev
• rezultati
Barreno et al.:Can Machine Learning Be Secure?
Barreno et al.:Can Machine Learning Be Secure?
http://arxiv.org/pdf/1312.6199v4.pdf
http://arxiv.org/pdf/1206.6389v1.pdf
http://blaine-nelson.com/research/pubs/Huang-Joseph-AISec-2011
http://www.cs.berkeley.edu/~tygar/papers/Machine_Learning_Securit
y/asiaccs06.pdf
http://www.ecmlpkdd2013.org/wp-content/uploads/2013/07/527.pdf

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Napadi na algoritme za strojno učenje