Less is More: A privacy-respecting Android malware classifier using
Federated Learning

v1v2v3 (latest)

Less is More: A privacy-respecting Android malware classifier using Federated Learning

Proceedings on Privacy Enhancing Technologies (PoPETs), 2020

16 July 2020

Veelasha Moonsamy

ArXiv (abs)PDF HTML

Papers citing "Less is More: A privacy-respecting Android malware classifier using Federated Learning"

11 / 11 papers shown

Federated Cyber Defense: Privacy-Preserving Ransomware Detection Across Distributed Systems

Federated Cyber Defense: Privacy-Preserving Ransomware Detection Across Distributed Systems

Daniel M. Jimenez-Gutierrez

Joaquin Del Rio

Oleksii Sliusarenko

Xabi Uribe-Etxebarria

117

0

0

03 Nov 2025

Trust Driven On-Demand Scheme for Client Deployment in Federated
Learning

Trust Driven On-Demand Scheme for Client Deployment in Federated Learning

195

5

0

01 May 2024

FP-Fed: Privacy-Preserving Federated Detection of Browser Fingerprinting

FP-Fed: Privacy-Preserving Federated Detection of Browser FingerprintingNetwork and Distributed System Security Symposium (NDSS), 2023

Meenatchi Sundaram Muthu Selva Annamalai

Igor Bilogrevic

Emiliano De Cristofaro

234

5

0

28 Nov 2023

Exploring Machine Learning Models for Federated Learning: A Review of
Approaches, Performance, and Limitations

Exploring Machine Learning Models for Federated Learning: A Review of Approaches, Performance, and Limitations

Elaheh Jafarigol

Theodore Trafalis

Talayeh Razzaghi

Mona Zamankhani

191

5

0

17 Nov 2023

SoK: Pragmatic Assessment of Machine Learning for Network Intrusion
Detection

SoK: Pragmatic Assessment of Machine Learning for Network Intrusion DetectionEuropean Symposium on Security and Privacy (Euro S&P), 2023

Giovanni Apruzzese

382

48

0

30 Apr 2023

SoK: Content Moderation for End-to-End Encryption

SoK: Content Moderation for End-to-End EncryptionProceedings on Privacy Enhancing Technologies (PoPETs), 2023

Sarah Scheffler

Jonathan R. Mayer

302

33

0

07 Mar 2023

A Dynamic Weighted Federated Learning for Android Malware Classification

A Dynamic Weighted Federated Learning for Android Malware Classification

Ayushi Chaudhuri

Buddhadeb Pradhan

86

16

0

23 Nov 2022

Cerberus: Exploring Federated Prediction of Security Events

Cerberus: Exploring Federated Prediction of Security EventsConference on Computer and Communications Security (CCS), 2022

Mohammad Naseri

Enrico Mariconti

Gianluca Stringhini

Emiliano De Cristofaro

323

20

0

07 Sep 2022

CELEST: Federated Learning for Globally Coordinated Threat Detection

CELEST: Federated Learning for Globally Coordinated Threat DetectionIEEE Transactions on Information Forensics and Security (IEEE TIFS), 2022

Tina Eliassi-Rad

Jack W. Davidson

445

6

0

23 May 2022

Symbolic analysis meets federated learning to enhance malware identifier

Symbolic analysis meets federated learning to enhance malware identifierARES (ARES), 2022

Khanh-Huu-The Dam

Charles-Henry Bertrand Van Ouytsel

315

8

0

29 Apr 2022

Deep Learning for Android Malware Defenses: a Systematic Literature
Review

Deep Learning for Android Malware Defenses: a Systematic Literature ReviewACM Computing Surveys (CSUR), 2021

Chakkrit Tantithamthavorn

355

106

0

09 Mar 2021