4,096 research outputs found
Cross cultural perspectives of decision-making and control in multinational corporations operating in ASEAN
Kajian ini membincangkan isu-isu persekitaran budaya negara ASEAN dan cabaran-cabarannya terhadap pengurus-pengurus korporat multi-nasional. Kajian ini melaporkan penemuan terhadap corak membuat keputusan, kawalan dan pengurusan budaya serta aspek gelagat. Walaupun penemuan ini mempunyai persamaan dengan kajian lain, namun terdapat perbezaan dalam corak membuat keputusan, kawalan dan pengurusan budaya serta aspek gelagat
Multi-party Poisoning through Generalized -Tampering
In a poisoning attack against a learning algorithm, an adversary tampers with
a fraction of the training data with the goal of increasing the
classification error of the constructed hypothesis/model over the final test
distribution. In the distributed setting, might be gathered gradually from
data providers who generate and submit their shares of
in an online way.
In this work, we initiate a formal study of -poisoning attacks in
which an adversary controls of the parties, and even for each
corrupted party , the adversary submits some poisoned data on
behalf of that is still "-close" to the correct data (e.g.,
fraction of is still honestly generated). For , this model
becomes the traditional notion of poisoning, and for it coincides with
the standard notion of corruption in multi-party computation.
We prove that if there is an initial constant error for the generated
hypothesis , there is always a -poisoning attacker who can decrease
the confidence of (to have a small error), or alternatively increase the
error of , by . Our attacks can be implemented in
polynomial time given samples from the correct data, and they use no wrong
labels if the original distributions are not noisy.
At a technical level, we prove a general lemma about biasing bounded
functions through an attack model in which each
block might be controlled by an adversary with marginal probability
in an online way. When the probabilities are independent, this coincides with
the model of -tampering attacks, thus we call our model generalized
-tampering. We prove the power of such attacks by incorporating ideas from
the context of coin-flipping attacks into the -tampering model and
generalize the results in both of these areas
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