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Feature Importance Guided Attack: A Model Agnostic Adversarial Attack

Feature Importance Guided Attack: A Model Agnostic Adversarial Attack

28 June 2021
Gilad Gressel
Niranjan Hegde
A. Sreekumar
Rishikumar Radhakrishnan
Kalyani Harikumar
Michael C. Darling
Krishnashree Achuthan
    AAML
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Papers citing "Feature Importance Guided Attack: A Model Agnostic Adversarial Attack"

10 / 10 papers shown
Title
FitCF: A Framework for Automatic Feature Importance-guided Counterfactual Example Generation
FitCF: A Framework for Automatic Feature Importance-guided Counterfactual Example Generation
Qianli Wang
Nils Feldhus
Simon Ostermann
Luis Felipe Villa-Arenas
Sebastian Möller
Vera Schmitt
AAML
34
0
0
01 Jan 2025
Constrained Adaptive Attack: Effective Adversarial Attack Against Deep
  Neural Networks for Tabular Data
Constrained Adaptive Attack: Effective Adversarial Attack Against Deep Neural Networks for Tabular Data
Thibault Simonetto
Salah Ghamizi
Maxime Cordy
AAML
OOD
36
2
0
02 Jun 2024
Biathlon: Harnessing Model Resilience for Accelerating ML Inference
  Pipelines
Biathlon: Harnessing Model Resilience for Accelerating ML Inference Pipelines
Chaokun Chang
Eric Lo
Chunxiao Ye
21
2
0
18 May 2024
MISLEAD: Manipulating Importance of Selected features for Learning
  Epsilon in Evasion Attack Deception
MISLEAD: Manipulating Importance of Selected features for Learning Epsilon in Evasion Attack Deception
Vidit Khazanchi
Pavan Kulkarni
Yuvaraj Govindarajulu
Manojkumar Somabhai Parmar
AAML
29
0
0
24 Apr 2024
Tabdoor: Backdoor Vulnerabilities in Transformer-based Neural Networks
  for Tabular Data
Tabdoor: Backdoor Vulnerabilities in Transformer-based Neural Networks for Tabular Data
Bart Pleiter
Behrad Tajalli
Stefanos Koffas
Gorka Abad
Jing Xu
Martha Larson
S. Picek
LMTD
AAML
35
1
0
13 Nov 2023
Raze to the Ground: Query-Efficient Adversarial HTML Attacks on
  Machine-Learning Phishing Webpage Detectors
Raze to the Ground: Query-Efficient Adversarial HTML Attacks on Machine-Learning Phishing Webpage Detectors
Biagio Montaruli
Luca Demetrio
Maura Pintor
Luca Compagna
Davide Balzarotti
Battista Biggio
AAML
24
5
0
04 Oct 2023
Multi-SpacePhish: Extending the Evasion-space of Adversarial Attacks
  against Phishing Website Detectors using Machine Learning
Multi-SpacePhish: Extending the Evasion-space of Adversarial Attacks against Phishing Website Detectors using Machine Learning
Ying Yuan
Giovanni Apruzzese
Mauro Conti
AAML
23
19
0
24 Oct 2022
An Adversarial Attack Analysis on Malicious Advertisement URL Detection
  Framework
An Adversarial Attack Analysis on Malicious Advertisement URL Detection Framework
Ehsan Nowroozi
A. Abhishek
Mohammadreza Mohammadi
Mauro Conti
AAML
33
30
0
27 Apr 2022
Adversarial Attacks for Tabular Data: Application to Fraud Detection and
  Imbalanced Data
Adversarial Attacks for Tabular Data: Application to Fraud Detection and Imbalanced Data
F. Cartella
Orlando Anunciação
Yuki Funabiki
D. Yamaguchi
Toru Akishita
Olivier Elshocht
AAML
55
71
0
20 Jan 2021
The Threat of Adversarial Attacks on Machine Learning in Network
  Security -- A Survey
The Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey
Olakunle Ibitoye
Rana Abou-Khamis
Mohamed el Shehaby
Ashraf Matrawy
M. O. Shafiq
AAML
24
68
0
06 Nov 2019
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