Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Federated Learning with Differential Privacy: Algorithms and Performance
  Analysis   In this paper, to effectively prevent information leakage, we propose a novel
framework based on the concept of differential privacy (DP), in which
artificial noises are added to the parameters at the clients side before
aggregating, namely, noising before model aggregation FL (NbAFL). First, we
prove that the NbAFL can satisfy DP under distinct protection levels by
properly adapting different variances of artificial noises. Then we develop a
theoretical convergence bound of the loss function of the trained FL model in
the NbAFL. Specifically, the theoretical bound reveals the following three key
properties: 1) There is a tradeoff between the convergence performance and
privacy protection levels, i.e., a better convergence performance leads to a
lower protection level; 2) Given a fixed privacy protection level, increasing
the number $N$ of overall clients participating in FL can improve the
convergence performance; 3) There is an optimal number of maximum aggregation
times (communication rounds) in terms of convergence performance for a given
protection level. Furthermore, we propose a $K$-random scheduling strategy,
where $K$ ($1<K<N$) clients are randomly selected from the $N$ overall clients
to participate in each aggregation. We also develop the corresponding
convergence bound of the loss function in this case and the $K$-random
scheduling strategy can also retain the above three properties. Moreover, we
find that there is an optimal $K$ that achieves the best convergence
performance at a fixed privacy level. Evaluations demonstrate that our
theoretical results are consistent with simulations, thereby facilitating the
designs on various privacy-preserving FL algorithms with different tradeoff
requirements on convergence performance and privacy levels.

35
The categories of this paper are: mtrl-th
7
The categories of this paper are: hep-th
23
The categories of this paper are: solv-int
12
The categories of this paper are: nucl-th
4
The categories of this paper are: cond-mat
30
The categories of this paper are: q-alg
9
The categories of this paper are: nlin
26
The categories of this paper are: bayes-an
22
The categories of this paper are: chao-dyn
36
The categories of this paper are: cmp-lg
24
The categories of this paper are: dg-ga
37
The categories of this paper are: supr-con
13
The categories of this paper are: quant-ph
27
The categories of this paper are: comp-gas
18
The categories of this paper are: econ
2
The categories of this paper are: math