Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
2402.02452
Cited By
XAI-CF -- Examining the Role of Explainable Artificial Intelligence in Cyber Forensics
4 February 2024
Shahid Alam
Zeynep Altıparmak
Re-assign community
ArXiv
PDF
HTML
Papers citing
"XAI-CF -- Examining the Role of Explainable Artificial Intelligence in Cyber Forensics"
50 / 52 papers shown
Title
SIFT -- File Fragment Classification Without Metadata
Shahid Alam
18
2
0
05 Oct 2023
ProtoExplorer: Interpretable Forensic Analysis of Deepfake Videos using Prototype Exploration and Refinement
M. D. L. D. Bouter
J. Pardo
Z. Geradts
M. Worring
48
10
0
20 Sep 2023
Adversarial attacks and defenses in explainable artificial intelligence: A survey
Hubert Baniecki
P. Biecek
AAML
64
66
0
06 Jun 2023
A Survey on Explainable Artificial Intelligence for Cybersecurity
Gaith Rjoub
Jamal Bentahar
Omar Abdel Wahab
R. Mizouni
Alyssa Song
Robin Cohen
Hadi Otrok
Azzam Mourad
49
29
0
07 Mar 2023
Explainable Artificial Intelligence Applications in Cyber Security: State-of-the-Art in Research
Zhibo Zhang
H. A. Hamadi
Ernesto Damiani
C. Yeun
Fatma Taher
AAML
72
156
0
31 Aug 2022
SAFARI: Versatile and Efficient Evaluations for Robustness of Interpretability
Wei Huang
Xingyu Zhao
Gao Jin
Xiaowei Huang
AAML
50
30
0
19 Aug 2022
Generative Adversarial Networks
Gilad Cohen
Raja Giryes
GAN
225
30,089
0
01 Mar 2022
An Objective Metric for Explainable AI: How and Why to Estimate the Degree of Explainability
Francesco Sovrano
F. Vitali
53
31
0
11 Sep 2021
Research trends, challenges, and emerging topics of digital forensics: A review of reviews
Fran Casino
Thomas K. Dasaklis
G. Spathoulas
M. Anagnostopoulos
Amrita Ghosal
István Bor̈oc̈z
A. Solanas
Mauro Conti
Constantinos Patsakis
44
82
0
10 Aug 2021
Fooling Partial Dependence via Data Poisoning
Hubert Baniecki
Wojciech Kretowicz
P. Biecek
AAML
47
23
0
26 May 2021
If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques
Mark T. Keane
Eoin M. Kenny
Eoin Delaney
Barry Smyth
CML
58
146
0
26 Feb 2021
Assessing Information Quality in IoT Forensics: Theoretical Framework and Model Implementation
Federico Costantini
Fausto Galvan
M. Stefani
Sebastiano Battiato
25
3
0
29 Dec 2020
Is there a role for statistics in artificial intelligence?
Sarah Friedrich
G. Antes
S. Behr
Harald Binder
W. Brannath
...
H. Leitgöb
Markus Pauly
A. Steland
A. Wilhelm
T. Friede
34
49
0
13 Sep 2020
The role of explainability in creating trustworthy artificial intelligence for health care: a comprehensive survey of the terminology, design choices, and evaluation strategies
A. Markus
J. Kors
P. Rijnbeek
78
464
0
31 Jul 2020
On quantitative aspects of model interpretability
An-phi Nguyen
María Rodríguez Martínez
43
114
0
15 Jul 2020
Explainable Artificial Intelligence: a Systematic Review
Giulia Vilone
Luca Longo
XAI
61
270
0
29 May 2020
Why Fairness Cannot Be Automated: Bridging the Gap Between EU Non-Discrimination Law and AI
Sandra Wachter
Brent Mittelstadt
Chris Russell
FaML
50
280
0
12 May 2020
Dense Passage Retrieval for Open-Domain Question Answering
Vladimir Karpukhin
Barlas Oğuz
Sewon Min
Patrick Lewis
Ledell Yu Wu
Sergey Edunov
Danqi Chen
Wen-tau Yih
RALM
154
3,739
0
10 Apr 2020
Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAI
L. Arras
Ahmed Osman
Wojciech Samek
XAI
AAML
56
156
0
16 Mar 2020
Measuring the Quality of Explanations: The System Causability Scale (SCS). Comparing Human and Machine Explanations
Andreas Holzinger
André M. Carrington
Heimo Muller
LRM
XAI
ELM
66
308
0
19 Dec 2019
Founding The Domain of AI Forensics
I. Baggili
Vahid Behzadan
29
16
0
11 Dec 2019
"How do I fool you?": Manipulating User Trust via Misleading Black Box Explanations
Himabindu Lakkaraju
Osbert Bastani
56
254
0
15 Nov 2019
Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods
Dylan Slack
Sophie Hilgard
Emily Jia
Sameer Singh
Himabindu Lakkaraju
FAtt
AAML
MLAU
66
814
0
06 Nov 2019
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI
Alejandro Barredo Arrieta
Natalia Díaz Rodríguez
Javier Del Ser
Adrien Bennetot
Siham Tabik
...
S. Gil-Lopez
Daniel Molina
Richard Benjamins
Raja Chatila
Francisco Herrera
XAI
113
6,235
0
22 Oct 2019
One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques
Vijay Arya
Rachel K. E. Bellamy
Pin-Yu Chen
Amit Dhurandhar
Michael Hind
...
Karthikeyan Shanmugam
Moninder Singh
Kush R. Varshney
Dennis L. Wei
Yunfeng Zhang
XAI
57
392
0
06 Sep 2019
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
Nils Reimers
Iryna Gurevych
1.0K
12,129
0
27 Aug 2019
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDa
FaML
534
4,333
0
23 Aug 2019
Multilingual Universal Sentence Encoder for Semantic Retrieval
Yinfei Yang
Daniel Cer
Amin Ahmad
Mandy Guo
Jax Law
...
Steve Yuan
Chris Tar
Yun-hsuan Sung
B. Strope
R. Kurzweil
3DV
64
477
0
09 Jul 2019
Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI
Shane T. Mueller
R. Hoffman
W. Clancey
Abigail Emrey
Gary Klein
XAI
47
286
0
05 Feb 2019
Metrics for Explainable AI: Challenges and Prospects
R. Hoffman
Shane T. Mueller
Gary Klein
Jordan Litman
XAI
72
725
0
11 Dec 2018
Towards the Development of Realistic Botnet Dataset in the Internet of Things for Network Forensic Analytics: Bot-IoT Dataset
Nickolaos Koroniotis
Nour Moustafa
E. Sitnikova
B. Turnbull
44
1,219
0
02 Nov 2018
Stakeholders in Explainable AI
Alun D. Preece
Daniel Harborne
Dave Braines
Richard J. Tomsett
Supriyo Chakraborty
38
155
0
29 Sep 2018
Transparency and Explanation in Deep Reinforcement Learning Neural Networks
R. Iyer
Yuezhang Li
Huao Li
M. Lewis
R. Sundar
Katia Sycara
42
174
0
17 Sep 2018
Enabling Trust in Deep Learning Models: A Digital Forensics Case Study
Aditya K
Slawomir Grzonkowski
NhienAn Lekhac
32
27
0
03 Aug 2018
Local Rule-Based Explanations of Black Box Decision Systems
Riccardo Guidotti
A. Monreale
Salvatore Ruggieri
D. Pedreschi
Franco Turini
F. Giannotti
123
437
0
28 May 2018
A Survey Of Methods For Explaining Black Box Models
Riccardo Guidotti
A. Monreale
Salvatore Ruggieri
Franco Turini
D. Pedreschi
F. Giannotti
XAI
120
3,938
0
06 Feb 2018
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR
Sandra Wachter
Brent Mittelstadt
Chris Russell
MLAU
98
2,348
0
01 Nov 2017
What Does Explainable AI Really Mean? A New Conceptualization of Perspectives
Derek Doran
Sarah Schulz
Tarek R. Besold
XAI
66
438
0
02 Oct 2017
Interpretable & Explorable Approximations of Black Box Models
Himabindu Lakkaraju
Ece Kamar
R. Caruana
J. Leskovec
FAtt
57
254
0
04 Jul 2017
Explanation in Artificial Intelligence: Insights from the Social Sciences
Tim Miller
XAI
236
4,249
0
22 Jun 2017
A Unified Approach to Interpreting Model Predictions
Scott M. Lundberg
Su-In Lee
FAtt
863
21,815
0
22 May 2017
Interpretable Explanations of Black Boxes by Meaningful Perturbation
Ruth C. Fong
Andrea Vedaldi
FAtt
AAML
74
1,517
0
11 Apr 2017
Axiomatic Attribution for Deep Networks
Mukund Sundararajan
Ankur Taly
Qiqi Yan
OOD
FAtt
175
5,968
0
04 Mar 2017
Towards A Rigorous Science of Interpretable Machine Learning
Finale Doshi-Velez
Been Kim
XAI
FaML
371
3,776
0
28 Feb 2017
Forensic Analysis of the ChatSecure Instant Messaging Application on Android Smartphones
C. Anglano
M. Canonico
Marco Guazzone
26
52
0
21 Oct 2016
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
Ramprasaath R. Selvaraju
Michael Cogswell
Abhishek Das
Ramakrishna Vedantam
Devi Parikh
Dhruv Batra
FAtt
252
19,929
0
07 Oct 2016
Interpretable Two-level Boolean Rule Learning for Classification
Guolong Su
Dennis L. Wei
Kush R. Varshney
Dmitry Malioutov
56
52
0
18 Jun 2016
Making Tree Ensembles Interpretable
Satoshi Hara
K. Hayashi
55
71
0
17 Jun 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAtt
FaML
917
16,931
0
16 Feb 2016
Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model
Benjamin Letham
Cynthia Rudin
Tyler H. McCormick
D. Madigan
FAtt
60
743
0
05 Nov 2015
1
2
Next