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SoK: Modeling Explainability in Security Analytics for Interpretability,
  Trustworthiness, and Usability
v1v2 (latest)

SoK: Modeling Explainability in Security Analytics for Interpretability, Trustworthiness, and Usability

ARES (ARES), 2022
31 October 2022
Dipkamal Bhusal
Rosalyn Shin
Ajay Ashok Shewale
M. K. Veerabhadran
Michael Clifford
Sara Rampazzi
Nidhi Rastogi
    FAttAAML
ArXiv (abs)PDFHTML

Papers citing "SoK: Modeling Explainability in Security Analytics for Interpretability, Trustworthiness, and Usability"

9 / 9 papers shown
Title
FACE: Faithful Automatic Concept Extraction
FACE: Faithful Automatic Concept Extraction
Dipkamal Bhusal
Michael Clifford
Sara Rampazzi
Nidhi Rastogi
CVBM
92
1
0
13 Oct 2025
Concept-Based Masking: A Patch-Agnostic Defense Against Adversarial Patch Attacks
Concept-Based Masking: A Patch-Agnostic Defense Against Adversarial Patch Attacks
Ayushi Mehrotra
Derek Peng
Dipkamal Bhusal
Nidhi Rastogi
AAML
81
0
0
05 Oct 2025
Smaller is Better: Enhancing Transparency in Vehicle AI Systems via Pruning
Smaller is Better: Enhancing Transparency in Vehicle AI Systems via Pruning
Sanish Suwal
Shaurya Garg
Dipkamal Bhusal
Michael Clifford
Nidhi Rastogi
AAML
86
1
0
24 Sep 2025
Do Sparse Subnetworks Exhibit Cognitively Aligned Attention? Effects of Pruning on Saliency Map Fidelity, Sparsity, and Concept Coherence
Do Sparse Subnetworks Exhibit Cognitively Aligned Attention? Effects of Pruning on Saliency Map Fidelity, Sparsity, and Concept Coherence
Sanish Suwal
Dipkamal Bhusal
Michael Clifford
Nidhi Rastogi
168
1
0
23 Sep 2025
ConCap: Practical Network Traffic Generation for Flow-based Intrusion Detection Systems
ConCap: Practical Network Traffic Generation for Flow-based Intrusion Detection Systems
Miel Verkerken
Laurens D'hooge
B. Volckaert
F. Turck
Giovanni Apruzzese
109
0
0
19 Sep 2025
PASA: Attack Agnostic Unsupervised Adversarial Detection using
  Prediction & Attribution Sensitivity Analysis
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
178
5
0
12 Apr 2024
Adversarial Patterns: Building Robust Android Malware Classifiers
Adversarial Patterns: Building Robust Android Malware ClassifiersACM Computing Surveys (ACM CSUR), 2022
Dipkamal Bhusal
Nidhi Rastogi
AAML
251
4
0
04 Mar 2022
Multi-Label Classification of Thoracic Diseases using Dense
  Convolutional Network on Chest Radiographs
Multi-Label Classification of Thoracic Diseases using Dense Convolutional Network on Chest Radiographs
Dipkamal Bhusal
S. Panday
122
9
0
08 Feb 2022
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAttFaML
1.8K
19,183
0
16 Feb 2016
1