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Transcending Transcend: Revisiting Malware Classification in the
  Presence of Concept Drift

Transcending Transcend: Revisiting Malware Classification in the Presence of Concept Drift

8 October 2020
Federico Barbero
Feargus Pendlebury
Fabio Pierazzi
Lorenzo Cavallaro
ArXivPDFHTML

Papers citing "Transcending Transcend: Revisiting Malware Classification in the Presence of Concept Drift"

13 / 13 papers shown
Title
LAMD: Context-driven Android Malware Detection and Classification with LLMs
LAMD: Context-driven Android Malware Detection and Classification with LLMs
Xingzhi Qian
Xinran Zheng
Yiling He
Shuo Yang
Lorenzo Cavallaro
116
3
0
18 Feb 2025
Defending against Adversarial Malware Attacks on ML-based Android Malware Detection Systems
Defending against Adversarial Malware Attacks on ML-based Android Malware Detection Systems
Ping He
Lorenzo Cavallaro
Shouling Ji
AAML
178
0
0
23 Jan 2025
MalMixer: Few-Shot Malware Classification with Retrieval-Augmented Semi-Supervised Learning
MalMixer: Few-Shot Malware Classification with Retrieval-Augmented Semi-Supervised Learning
Eric Li
Yifan Zhang
Yu Huang
Kevin Leach
70
0
0
20 Sep 2024
TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time (Extended Version)
TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time (Extended Version)
Zeliang Kan
Shae McFadden
Daniel Arp
Feargus Pendlebury
Roberto Jordaney
Johannes Kinder
Fabio Pierazzi
Lorenzo Cavallaro
51
1
0
02 Feb 2024
Deep Neural Rejection against Adversarial Examples
Deep Neural Rejection against Adversarial Examples
Angelo Sotgiu
Ambra Demontis
Marco Melis
Battista Biggio
Giorgio Fumera
Xiaoyi Feng
Fabio Roli
AAML
54
69
0
01 Oct 2019
TESSERACT: Eliminating Experimental Bias in Malware Classification
  across Space and Time
TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time
Feargus Pendlebury
Fabio Pierazzi
Roberto Jordaney
Johannes Kinder
Lorenzo Cavallaro
49
358
0
20 Jul 2018
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust
  Deep Learning
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning
Nicolas Papernot
Patrick McDaniel
OOD
AAML
149
508
0
13 Mar 2018
Learning to Evade Static PE Machine Learning Malware Models via
  Reinforcement Learning
Learning to Evade Static PE Machine Learning Malware Models via Reinforcement Learning
Hyrum S. Anderson
Anant Kharkar
Bobby Filar
David Evans
P. Roth
AAML
67
208
0
26 Jan 2018
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning
Battista Biggio
Fabio Roli
AAML
116
1,409
0
08 Dec 2017
Context-aware, Adaptive and Scalable Android Malware Detection through
  Online Learning (extended version)
Context-aware, Adaptive and Scalable Android Malware Detection through Online Learning (extended version)
A. Narayanan
Mahinthan Chandramohan
Lihui Chen
Yang Liu
25
87
0
03 Jun 2017
Intriguing properties of neural networks
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
259
14,912
1
21 Dec 2013
Conditional validity of inductive conformal predictors
Conditional validity of inductive conformal predictors
V. Vovk
222
416
0
12 Sep 2012
A tutorial on conformal prediction
A tutorial on conformal prediction
Glenn Shafer
V. Vovk
447
1,141
0
21 Jun 2007
1