Skip to main navigation
Skip to search
Skip to main content
Illinois Experts Home
LOGIN & Help
Link opens in a new tab
Search content at Illinois Experts
Home
Profiles
Research units
Research & Scholarship
Datasets
Honors
Press/Media
Activities
DBA: DISTRIBUTED BACKDOOR ATTACKS AGAINST FEDERATED LEARNING
Chulin Xie
, Keli Huang
, Pin Yu Chen
,
Bo Li
Siebel School of Computing and Data Science
Research output
:
Contribution to conference
›
Paper
›
peer-review
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'DBA: DISTRIBUTED BACKDOOR ATTACKS AGAINST FEDERATED LEARNING'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Assessment Framework
10%
Attack Performance
10%
Attack Success Rate
10%
Backdoor
30%
Backdoor Attack
20%
Data Distribution
20%
Distributed Backdoor Attack
100%
Distributed Denial of Service (DDoS)
10%
Distributed Learning
10%
Distribution Ratio
10%
Diverse Datasets
10%
Evade
10%
Evaluation Results
10%
Feature Importance Score
10%
Federated Learning
100%
Finance Data
10%
Global Triggers
20%
Heterogeneous Data
10%
Image Data
10%
Learning Algorithm
10%
Learning Data
10%
Learning Methodology
10%
Local Patterns
10%
Machine Learning Models
10%
Poison's Ratio
10%
Robust Federated Learning
10%
Scale Factor
10%
Threat Assessment
10%
Training Data
10%
Training Set
10%
Trigger Factor
10%
Two-state
10%
Visual Features
10%
Visual Interpretation
10%
Vulnerability
10%
Computer Science
Backdoors
100%
Data Distribution
13%
Distributed Learning
6%
Distributed Nature
6%
Evaluation Result
6%
Federated Learning
100%
Heterogeneous Data
6%
Learning Algorithm
6%
Learning System
6%
Machine Learning
6%
Scaling Factor
6%
Threat Assessment
6%
Training Data
6%
Visual Feature
6%