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1905.05137
Cited By
Analyzing Adversarial Attacks Against Deep Learning for Intrusion Detection in IoT Networks
Global Communications Conference (GLOBECOM), 2019
13 May 2019
Olakunle Ibitoye
Omair Shafiq
Ashraf Matrawy
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Papers citing
"Analyzing Adversarial Attacks Against Deep Learning for Intrusion Detection in IoT Networks"
28 / 28 papers shown
A Transformer-Based Approach for DDoS Attack Detection in IoT Networks
Sandipan Dey
Payal Santosh Kate
Vatsala Upadhyay
Abhishek Vaish
126
1
0
14 Aug 2025
Enhancing IoT Security with CNN and LSTM-Based Intrusion Detection Systems
Afrah Gueriani
Hamza Kheddar
A. Mazari
187
37
0
28 May 2024
Large Scale Foundation Models for Intelligent Manufacturing Applications: A Survey
Haotian Zhang
S. D. Semujju
Zhicheng Wang
Xianwei Lv
Kang Xu
...
Jing Wu
Zhuo Long
Zhicheng Wang
Xiaoguang Ma
Wensheng Liang
UQCV
AI4TS
AI4CE
368
27
0
11 Dec 2023
SoK: Realistic Adversarial Attacks and Defenses for Intelligent Network Intrusion Detection
Computers & security (Comput. Secur.), 2023
João Vitorino
Isabel Praça
Eva Maia
AAML
222
30
0
13 Aug 2023
Meta-Analysis and Systematic Review for Anomaly Network Intrusion Detection Systems: Detection Methods, Dataset, Validation Methodology, and Challenges
IET Networks (IN), 2023
Z. K. Maseer
R. Yusof
Baidaa Al-Bander
Abdulgbar Saif
Qusay Kanaan Kadhim
176
28
0
05 Aug 2023
SoK: Adversarial Evasion Attacks Practicality in NIDS Domain and the Impact of Dynamic Learning
Mohamed el Shehaby
Ashraf Matrawy
AAML
402
8
0
08 Jun 2023
Review on the Feasibility of Adversarial Evasion Attacks and Defenses for Network Intrusion Detection Systems
Islam Debicha
Benjamin Cochez
Tayeb Kenaza
Thibault Debatty
Jean-Michel Dricot
Wim Mees
AAML
175
8
0
13 Mar 2023
Wild Networks: Exposure of 5G Network Infrastructures to Adversarial Examples
IEEE Transactions on Network and Service Management (IEEE TNSM), 2022
Giovanni Apruzzese
Rodion Vladimirov
A.T. Tastemirova
Pavel Laskov
AAML
244
20
0
04 Jul 2022
Security of Machine Learning-Based Anomaly Detection in Cyber Physical Systems
International Conference on Computer Communications and Networks (ICCCN), 2022
Zahra Jadidi
S. Pal
Nithesh Nayak K
A. Selvakkumar
C. Chang
Maedeh Beheshti
A. Jolfaei
AAML
181
16
0
12 Jun 2022
Liuer Mihou: A Practical Framework for Generating and Evaluating Grey-box Adversarial Attacks against NIDS
Ke He
Dan Dongseong Kim
Jing Sun
J. Yoo
Young Hun Lee
H. Kim
AAML
152
7
0
12 Apr 2022
AdIoTack: Quantifying and Refining Resilience of Decision Tree Ensemble Inference Models against Adversarial Volumetric Attacks on IoT Networks
Computers & security (Comput. Secur.), 2022
Arman Pashamokhtari
Gustavo E. A. P. A. Batista
Hassan Habibi Gharakheili
AAML
202
10
0
18 Mar 2022
Federated Learning for Privacy Preservation in Smart Healthcare Systems: A Comprehensive Survey
IEEE journal of biomedical and health informatics (IEEE JBHI), 2022
Mansoor Ali
F. Naeem
M. Tariq
Georges Kaddoum
252
196
0
18 Mar 2022
A Method Based on Deep Learning for the Detection and Characterization of Cybersecurity Incidents in Internet of Things Devices
Jhon Alexánder Parra
S. Gutiérrez
J. Branch
168
4
0
01 Mar 2022
An accurate IoT Intrusion Detection Framework using Apache Spark
Mohamed Abushwereb
Mouhammd Alkasassbeh
Mohammad Almseidin
Muhannad K. Mustafa
257
14
0
21 Feb 2022
Adversarial Machine Learning In Network Intrusion Detection Domain: A Systematic Review
Huda Ali Alatwi
C. Morisset
AAML
259
27
0
06 Dec 2021
Emerging Trends of Recently Published Datasets for Intrusion Detection Systems (IDS): A Survey
Rishabh Jindal
A. Anwar
142
3
0
02 Oct 2021
Poisoning Online Learning Filters: DDoS Attacks and Countermeasures
W. Tann
E. Chang
AAML
132
0
0
27 Jul 2021
Hack The Box: Fooling Deep Learning Abstraction-Based Monitors
Sara Al Hajj Ibrahim
M. Nassar
AAML
165
2
0
10 Jul 2021
DetectX -- Adversarial Input Detection using Current Signatures in Memristive XBar Arrays
IEEE Transactions on Circuits and Systems Part 1: Regular Papers (TCAS-I), 2021
Abhishek Moitra
Priyadarshini Panda
AAML
89
7
0
22 Jun 2021
Modeling Realistic Adversarial Attacks against Network Intrusion Detection Systems
Giovanni Apruzzese
M. Andreolini
Luca Ferretti
Mirco Marchetti
M. Colajanni
AAML
277
136
0
17 Jun 2021
Launching Adversarial Attacks against Network Intrusion Detection Systems for IoT
Journal of Cybersecurity and Privacy (JCP), 2021
Pavlos Papadopoulos
Oliver Thornewill von Essen
Nikolaos Pitropakis
C. Chrysoulas
Alexios Mylonas
William J. Buchanan
AAML
267
54
0
26 Apr 2021
Adversarial Training for Deep Learning-based Intrusion Detection Systems
Islam Debicha
Thibault Debatty
Jean-Michel Dricot
Wim Mees
AAML
104
25
0
20 Apr 2021
DiPSeN: Differentially Private Self-normalizing Neural Networks For Adversarial Robustness in Federated Learning
Computers & security (Comput. Secur.), 2021
Olakunle Ibitoye
M. O. Shafiq
Ashraf Matrawy
FedML
132
23
0
08 Jan 2021
Evaluation of Adversarial Training on Different Types of Neural Networks in Deep Learning-based IDSs
International Symposium on Networks, Computers and Communications (ISNCC), 2020
Rana Abou-Khamis
Ashraf Matrawy
AAML
182
59
0
08 Jul 2020
Adversarial Machine Learning Attacks and Defense Methods in the Cyber Security Domain
Ishai Rosenberg
A. Shabtai
Yuval Elovici
Lior Rokach
AAML
246
12
0
05 Jul 2020
Anomalous Example Detection in Deep Learning: A Survey
Saikiran Bulusu
B. Kailkhura
Yue Liu
P. Varshney
Basel Alomair
AAML
372
48
0
16 Mar 2020
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
452
72
0
06 Nov 2019
Directional Adversarial Training for Cost Sensitive Deep Learning Classification Applications
Engineering applications of artificial intelligence (EAAI), 2019
M. Terzi
Gian Antonio Susto
Pratik Chaudhari
OOD
AAML
131
17
0
08 Oct 2019
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