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EXPLAIN-IT: Towards Explainable AI for Unsupervised Network Traffic
  Analysis

EXPLAIN-IT: Towards Explainable AI for Unsupervised Network Traffic Analysis

3 March 2020
Andrea Morichetta
P. Casas
Marco Mellia
ArXiv (abs)PDFHTML

Papers citing "EXPLAIN-IT: Towards Explainable AI for Unsupervised Network Traffic Analysis"

10 / 10 papers shown
Characterizing Event-themed Malicious Web Campaigns: A Case Study on War-themed Websites
Characterizing Event-themed Malicious Web Campaigns: A Case Study on War-themed Websites
Maraz Mia
Mir Mehedi Ahsan Pritom
Tariqul Islam
Shouhuai Xu
235
2
0
29 Sep 2025
Uncertainty Awareness and Trust in Explainable AI- On Trust Calibration using Local and Global Explanations
Uncertainty Awareness and Trust in Explainable AI- On Trust Calibration using Local and Global Explanations
Carina Newen
Daniel Bodemer
Sonja Glantz
Emmanuel Müller
Magdalena Wischnewski
Lenka Schnaubert
262
0
0
10 Sep 2025
Do you see what I see? An Ambiguous Optical Illusion Dataset exposing limitations of Explainable AI
Do you see what I see? An Ambiguous Optical Illusion Dataset exposing limitations of Explainable AI
Carina Newen
Luca Hinkamp
Maria Ntonti
Emmanuel Müller
280
0
0
27 May 2025
Beyond Model Interpretability: Socio-Structural Explanations in Machine
  Learning
Beyond Model Interpretability: Socio-Structural Explanations in Machine LearningAi & Society (AS), 2024
Andrew Smart
Atoosa Kasirzadeh
319
12
0
05 Sep 2024
Deep Learning-driven Community Resilience Rating based on Intertwined Socio-Technical Systems Features
Deep Learning-driven Community Resilience Rating based on Intertwined Socio-Technical Systems Features
Kai Yin
Bo Li
Ali Mostafavi
140
6
0
03 Nov 2023
KnAC: an approach for enhancing cluster analysis with background
  knowledge and explanations
KnAC: an approach for enhancing cluster analysis with background knowledge and explanations
Szymon Bobek
M. Kuk
Jakub Brzegowski
Edyta Brzychczy
Grzegorz J. Nalepa
297
13
0
16 Dec 2021
Applications of Explainable AI for 6G: Technical Aspects, Use Cases, and
  Research Challenges
Applications of Explainable AI for 6G: Technical Aspects, Use Cases, and Research Challenges
Shen Wang
M. Qureshi
Luis Miralles-Pechuán
Thien Huynh-The
Thippa Reddy Gadekallu
Madhusanka Liyanage
284
36
0
09 Dec 2021
DeepAID: Interpreting and Improving Deep Learning-based Anomaly
  Detection in Security Applications
DeepAID: Interpreting and Improving Deep Learning-based Anomaly Detection in Security ApplicationsConference on Computer and Communications Security (CCS), 2021
Dongqi Han
Zhiliang Wang
Wenqi Chen
Ying Zhong
Su Wang
Han Zhang
Jiahai Yang
Xingang Shi
Xia Yin
AAML
245
113
0
23 Sep 2021
VitrAI -- Applying Explainable AI in the Real World
VitrAI -- Applying Explainable AI in the Real World
Marc Hanussek
Falko Kötter
Maximilien Kintz
Jens Drawehn
160
3
0
12 Feb 2021
A multi-component framework for the analysis and design of explainable
  artificial intelligence
A multi-component framework for the analysis and design of explainable artificial intelligenceMachine Learning and Knowledge Extraction (MLKE), 2020
S. Atakishiyev
H. Babiker
Nawshad Farruque
R. Goebel1
Myeongjung Kima
M. H. Motallebi
J. Rabelo
T. Syed
O. R. Zaïane
220
46
0
05 May 2020
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