Fast & Furious: Modelling Malware Detection as Evolving Data Streams

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Fast & Furious: Modelling Malware Detection as Evolving Data Streams

24 May 2022

Fabrício Ceschin

Heitor Murilo Gomes

Luiz S. Oliveira

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Papers citing "Fast & Furious: Modelling Malware Detection as Evolving Data Streams"

8 / 8 papers shown

Title
Reactive Soft Prototype Computing for Concept Drift Streams Christoph Raab Moritz Heusinger Frank-Michael Schleif 46 122 0 10 Jul 2020
A Preliminary Study On the Sustainability of Android Malware Detection Haipeng Cai 53 103 0 22 Jul 2018
TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time Feargus Pendlebury Fabio Pierazzi Roberto Jordaney Johannes Kinder Lorenzo Cavallaro 60 359 0 20 Jul 2018
Scikit-Multiflow: A Multi-output Streaming Framework Jacob Montiel Jesse Read Albert Bifet T. Abdessalem 37 307 0 12 Jul 2018
Learning to Evade Static PE Machine Learning Malware Models via Reinforcement Learning Hyrum S. Anderson Anant Kharkar Bobby Filar David Evans P. Roth AAML 73 210 0 26 Jan 2018
MaMaDroid: Detecting Android Malware by Building Markov Chains of Behavioral Models (Extended Version) Lucky Onwuzurike Enrico Mariconti Panagiotis Andriotis Emiliano De Cristofaro Gordon J. Ross Gianluca Stringhini 35 169 0 20 Nov 2017
Adaptive and Scalable Android Malware Detection through Online Learning A. Narayanan Liu Yang Lihui Chen Jinliang Liu 39 70 0 23 Jun 2016
Distributed Representations of Words and Phrases and their Compositionality Tomas Mikolov Ilya Sutskever Kai Chen G. Corrado J. Dean NAI OCL 402 33,560 0 16 Oct 2013

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