Confidentiality of training data induced by releasing machine-learning models, and has
recently received increasing attention. Motivated by existing MI attacks and other previous …

Although numerous attacks revealed the vulnerability of different PUF families to non-
invasive Machine Learning (ML) attacks, the question is still open whether all PUFs might be …

We show a directed and robust analogue of a boolean isoperimetric-type theorem of
Talagrand Geom. Funct. Anal., 3 (1993), pp. 295--314. As an application, we give a …

Given oracle access to a Boolean function f:{0, 1} n->{0, 1}, we design a randomized tester
that takes as input a parameter ε> 0, and outputs Yes if the function is monotonically non …

We consider the problem of testing whether an unknown Boolean function f:{-1, 1} n→{-1, 1}
is monotone versus ε-far from every monotone function. The two main results of this paper …

We prove a lower bound of Ω (n 1/3) for the query complexity of any two-sided and adaptive
algorithm that tests whether an unknown Boolean function f:{0, 1} n→{0, 1} is monotone …

As PUFs become ubiquitous for commercial products (eg, FPGAs from Xilinx, Altera, and
Microsemi), attacks against these primitives are evolving toward more omnipresent and …

The problem of testing monotonicity for Boolean functions on the hypergrid, f:[n] d→{0, 1} is a
classic topic in property testing. When n= 2, the domain is the hypercube. For the hypercube …

Unfortunately, none of the candidate [PUF] constructions have a proof of computational
security, and further, most, if not all, of them have been shown to be susceptible to ML …

We describe a Õ (d 5/6)-query monotonicity tester for Boolean functions f:[n] d→{0, 1} on the
n hypergrid. This is the first o (d) monotonicity tester with query complexity independent of n …