Literature Database

An Adaptive Empirical Bayesian Method for Sparse Deep Learning

Authors: Wei Deng, Xiao Zhang, Faming Liang, Guang Lin | Published: 2019-10-23 | Updated: 2020-04-13
Convergence Guarantee
Optimization Strategy
Deep Learning Technology

Wasserstein Smoothing: Certified Robustness against Wasserstein Adversarial Attacks

Authors: Alexander Levine, Soheil Feizi | Published: 2019-10-23
Wasserstein Distance
Performance Evaluation
Adversarial Example

A Useful Taxonomy for Adversarial Robustness of Neural Networks

Authors: Leslie N. Smith | Published: 2019-10-23
Adversarial Example
Adversarial Training
Effectiveness Analysis of Defense Methods

ASNM Datasets: A Collection of Network Traffic Features for Testing of Adversarial Classifiers and Network Intrusion Detectors

Authors: Ivan Homoliak, Petr Hanacek | Published: 2019-10-23
Modification of Network Traffic
Taxonomy of Attacks
Vulnerability Attack Method

A Context-aware Framework for Detecting Sensor-based Threats on Smart Devices

Authors: Amit Kumar Sikder, Hidayet Aksu, A. Selcuk Uluagac | Published: 2019-10-22
Sensor Information Management
Performance Evaluation Metrics
Anomaly Detection Algorithm

Cross-Representation Transferability of Adversarial Attacks: From Spectrograms to Audio Waveforms

Authors: Karl Michel Koerich, Mohammad Esmaeilpour, Sajjad Abdoli, Alceu de Souza Britto Jr., Alessandro Lameiras Koerich | Published: 2019-10-22 | Updated: 2020-07-29
Adversarial Learning
Performance Evaluation
Adversarial Transferability

Adversarial Example Detection by Classification for Deep Speech Recognition

Authors: Saeid Samizade, Zheng-Hua Tan, Chao Shen, Xiaohong Guan | Published: 2019-10-22
Adversarial Learning
Adversarial Transferability
Malfunction of Voice Assistants

Abnormal Client Behavior Detection in Federated Learning

Authors: Suyi Li, Yong Cheng, Yang Liu, Wei Wang, Tianjian Chen | Published: 2019-10-22 | Updated: 2019-12-06
Client Contribution Assessment
Poisoning
Anomaly Detection Method

Edge Dithering for Robust Adaptive Graph Convolutional Networks

Authors: Vassilis N. Ioannidis, Georgios B. Giannakis | Published: 2019-10-21
Graph Neural Network
Poisoning
Model Architecture

GraphSAC: Detecting anomalies in large-scale graphs

Authors: Vassilis N. Ioannidis, Dimitris Berberidis, Georgios B. Giannakis | Published: 2019-10-21
Graph Representation Learning
Data Contamination Detection
Performance Evaluation