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SoK: The Impact of Unlabelled Data in Cyberthreat Detection

SoK: The Impact of Unlabelled Data in Cyberthreat Detection

18 May 2022
Giovanni Apruzzese
P. Laskov
A.T. Tastemirova
ArXivPDFHTML

Papers citing "SoK: The Impact of Unlabelled Data in Cyberthreat Detection"

6 / 6 papers shown
Title
Adversarial Evasion Attacks Practicality in Networks: Testing the Impact of Dynamic Learning
Adversarial Evasion Attacks Practicality in Networks: Testing the Impact of Dynamic Learning
Mohamed el Shehaby
Ashraf Matrawy
AAML
14
7
0
08 Jun 2023
A Survey on Malware Detection with Graph Representation Learning
A Survey on Malware Detection with Graph Representation Learning
Tristan Bilot
Nour El Madhoun
Khaldoun Al Agha
Anis Zouaoui
AAML
8
20
0
28 Mar 2023
"Real Attackers Don't Compute Gradients": Bridging the Gap Between
  Adversarial ML Research and Practice
"Real Attackers Don't Compute Gradients": Bridging the Gap Between Adversarial ML Research and Practice
Giovanni Apruzzese
Hyrum S. Anderson
Savino Dambra
D. Freeman
Fabio Pierazzi
Kevin A. Roundy
AAML
14
74
0
29 Dec 2022
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
11
19
0
24 Oct 2022
Poisoning the Unlabeled Dataset of Semi-Supervised Learning
Poisoning the Unlabeled Dataset of Semi-Supervised Learning
Nicholas Carlini
AAML
139
68
0
04 May 2021
How Did That Get In My Phone? Unwanted App Distribution on Android
  Devices
How Did That Get In My Phone? Unwanted App Distribution on Android Devices
Platon Kotzias
Juan Caballero
Leyla Bilge
MedIm
19
36
0
20 Oct 2020
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