Hello,
I am working through your implementation of the OPT attack,
If my understand is not wrong , the part of binary_search_local may waste some opportunities of query:
if model.predict_label(x0+lbd*theta) == y0:
lbd_lo = lbd
lbd_hi = lbd*1.01
nquery += 1
while model.predict_label(x0+lbd_hi*theta) == y0:
lbd_hi = lbd_hi*1.01
nquery += 1
if lbd_hi > 20:
return float('inf'), nquery
In my opinion, if add lbd_lo = lbd_hi , you know, just like :
if model.predict_label(x0+lbd*theta) == y0:
lbd_lo = lbd
lbd_hi = lbd*1.01
nquery += 1
while model.predict_label(x0+lbd_hi*theta) == y0:
lbd_lo = lbd_hi
lbd_hi = lbd_hi*1.01
nquery += 1
if lbd_hi > 20:
return float('inf'), nquery
Some opportunities of querying may be saved in the process of binary search.
I wonder if u could clarify this issue for me,
Thanks a miiiiiiiiiiiiillion!
Hello,
I am working through your implementation of the OPT attack,
If my understand is not wrong , the part of binary_search_local may waste some opportunities of query:
In my opinion, if add lbd_lo = lbd_hi , you know, just like :
Some opportunities of querying may be saved in the process of binary search.
I wonder if u could clarify this issue for me,
Thanks a miiiiiiiiiiiiillion!