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1911.01921
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DLA: Dense-Layer-Analysis for Adversarial Example Detection
European Symposium on Security and Privacy (EuroS&P), 2019
5 November 2019
Philip Sperl
Ching-yu Kao
Peng Chen
Konstantin Böttinger
AAML
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Papers citing
"DLA: Dense-Layer-Analysis for Adversarial Example Detection"
19 / 19 papers shown
Evaluating the robustness of adversarial defenses in malware detection systems
Mostafa Jafari
Alireza Shameli-Sendi
AAML
217
2
0
14 May 2025
AED-PADA:Improving Generalizability of Adversarial Example Detection via Principal Adversarial Domain Adaptation
Heqi Peng
Yun-an Wang
Ruijie Yang
Beichen Li
Rui Wang
Yuanfang Guo
AAML
208
4
0
19 Apr 2024
Fortify the Guardian, Not the Treasure: Resilient Adversarial Detectors
Raz Lapid
Almog Dubin
Moshe Sipper
AAML
249
8
0
18 Apr 2024
PASA: Attack Agnostic Unsupervised Adversarial Detection using Prediction & Attribution Sensitivity Analysis
Dipkamal Bhusal
Md Tanvirul Alam
M. K. Veerabhadran
Michael Clifford
Sara Rampazzi
Nidhi Rastogi
AAML
259
5
0
12 Apr 2024
AdvCheck: Characterizing Adversarial Examples via Local Gradient Checking
Computers & security (Comput. Secur.), 2023
Ruoxi Chen
Haibo Jin
Jinyin Chen
Haibin Zheng
AAML
257
1
0
25 Mar 2023
PAD: Towards Principled Adversarial Malware Detection Against Evasion Attacks
IEEE Transactions on Dependable and Secure Computing (IEEE TDSC), 2023
Deqiang Li
Shicheng Cui
Yun Li
Jia Xu
Fu Xiao
Shouhuai Xu
AAML
398
31
0
22 Feb 2023
Nowhere to Hide: A Lightweight Unsupervised Detector against Adversarial Examples
Hui Liu
Bo Zhao
Kehuan Zhang
Peng Liu
AAML
218
7
0
16 Oct 2022
Be Your Own Neighborhood: Detecting Adversarial Example by the Neighborhood Relations Built on Self-Supervised Learning
International Conference on Machine Learning (ICML), 2022
Zhiyuan He
Yijun Yang
Pin-Yu Chen
Qiang Xu
Tsung-Yi Ho
AAML
253
10
0
31 Aug 2022
Detecting and Recovering Adversarial Examples from Extracting Non-robust and Highly Predictive Adversarial Perturbations
Mingyu Dong
Jiahao Chen
Diqun Yan
Jingxing Gao
Li Dong
Rangding Wang
AAML
180
0
0
30 Jun 2022
Adversarial Example Detection in Deployed Tree Ensembles
Laurens Devos
Wannes Meert
Jesse Davis
AAML
155
2
0
27 Jun 2022
Detecting Adversarial Perturbations in Multi-Task Perception
IEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2022
Marvin Klingner
V. Kumar
S. Yogamani
Andreas Bär
Tim Fingscheidt
AAML
338
17
0
02 Mar 2022
What You See is Not What the Network Infers: Detecting Adversarial Examples Based on Semantic Contradiction
Network and Distributed System Security Symposium (NDSS), 2022
Yijun Yang
Ruiyuan Gao
Yu Li
Qiuxia Lai
Qiang Xu
GAN
AAML
259
25
0
24 Jan 2022
Feature-Filter: Detecting Adversarial Examples through Filtering off Recessive Features
Hui Liu
Bo Zhao
Minzhi Ji
Yuefeng Peng
Jiabao Guo
Peng Liu
AAML
285
3
0
19 Jul 2021
Evading Adversarial Example Detection Defenses with Orthogonal Projected Gradient Descent
International Conference on Learning Representations (ICLR), 2021
Oliver Bryniarski
Nabeel Hingun
Pedro Pachuca
Vincent Wang
Nicholas Carlini
AAML
213
42
0
28 Jun 2021
Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart
Computer Vision and Pattern Recognition (CVPR), 2021
Tianyu Pang
Huishuai Zhang
Di He
Yinpeng Dong
Hang Su
Wei Chen
Jun Zhu
Tie-Yan Liu
AAML
250
25
0
31 May 2021
NoiLIn: Improving Adversarial Training and Correcting Stereotype of Noisy Labels
Jingfeng Zhang
Xilie Xu
Bo Han
Tongliang Liu
Gang Niu
Li-zhen Cui
Masashi Sugiyama
NoLa
AAML
245
9
0
31 May 2021
Adversarial Examples Detection with Bayesian Neural Network
IEEE Transactions on Emerging Topics in Computational Intelligence (IEEE TETCI), 2021
Yao Li
Tongyi Tang
Cho-Jui Hsieh
T. C. Lee
GAN
AAML
227
3
0
18 May 2021
Optimizing Information Loss Towards Robust Neural Networks
Philip Sperl
Konstantin Böttinger
AAML
170
3
0
07 Aug 2020
A
3
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A
3
: Activation Anomaly Analysis
Philip Sperl
Jan-Philipp Schulze
Konstantin Böttinger
234
6
0
03 Mar 2020
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