Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Trojan Signatures in DNN Weights   Deep neural networks have been shown to be vulnerable to backdoor, or trojan,
attacks where an adversary has embedded a trigger in the network at training
time such that the model correctly classifies all standard inputs, but
generates a targeted, incorrect classification on any input which contains the
trigger. In this paper, we present the first ultra light-weight and highly
effective trojan detection method that does not require access to the
training/test data, does not involve any expensive computations, and makes no
assumptions on the nature of the trojan trigger. Our approach focuses on
analysis of the weights of the final, linear layer of the network. We
empirically demonstrate several characteristics of these weights that occur
frequently in trojaned networks, but not in benign networks. In particular, we
show that the distribution of the weights associated with the trojan target
class is clearly distinguishable from the weights associated with other
classes. Using this, we demonstrate the effectiveness of our proposed detection
method against state-of-the-art attacks across a variety of architectures,
datasets, and trigger types.

14
The categories of this paper are: math-ph
31
The categories of this paper are: ao-sci
4
The categories of this paper are: cond-mat
8
The categories of this paper are: hep-ex
15
The categories of this paper are: nucl-ex
2
The categories of this paper are: math
34
The categories of this paper are: chem-ph
36
The categories of this paper are: cmp-lg
26
The categories of this paper are: bayes-an
22
The categories of this paper are: chao-dyn
6
The categories of this paper are: astro-ph
32
The categories of this paper are: atom-ph
33
The categories of this paper are: plasm-ph
27
The categories of this paper are: comp-gas
7
The categories of this paper are: hep-th
20
The categories of this paper are: acc-phys