Android Malware Detection

Benchmarks archive 2025-07-28

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Datasets archive 2025-07-28

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Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

19 shown of 19 papers with code (76 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Continuous Learning for Android Malware Detection
  8 Feb 2023 2 repositories listed
  We propose a new hierarchical contrastive learning scheme, and a new sample selection technique to continuously train the Android malware classifier.
• Evaluating the Robustness of Adversarial Defenses in Malware Detection Systems
  14 May 2025 1 repository listed
  Adversarially trained defenses, including AT-rFGSM-k, AT-MaxMA, improves robustness under small budgets but remains vulnerable to unrestricted perturbations, with attack success rates of 99.
• Crystal ball: From innovative attacks to attack effectiveness classifier
  24 Dec 2024 1 repository listed
  This study presents a set of innovative problem-based evasion attacks against well-known Android malware detection systems, which decrease their detection rate by up to 97%.
• MASKDROID: Robust Android Malware Detection with Masked Graph Representations
  29 Sep 2024 1 repository listed
  Among the various tools employed in malware detection, graph representations (e.
• DetectBERT: Towards Full App-Level Representation Learning to Detect Android Malware
  29 Aug 2024 1 repository listed
  Recent advancements in ML and DL have significantly improved Android malware detection, yet many methodologies still rely on basic static analysis, bytecode, or function call graphs that often fail to capture complex…
• Improving Adversarial Robustness in Android Malware Detection by Reducing the Impact of Spurious Correlations
  27 Aug 2024 1 repository listed
  In particular, our defense can improve adversarial robustness by up to 55% against realistic evasion attacks compared to Sec-SVM.
• MalPurifier: Enhancing Android Malware Detection with Adversarial Purification against Evasion Attacks
  11 Dec 2023 1 repository listed
  In this paper, we introduce MalPurifier, a novel adversarial purification framework specifically engineered for Android malware detection.
• Efficient Concept Drift Handling for Batch Android Malware Detection Models
  18 Sep 2023 1 repository listed
  Particularly, we analyze the effect of two aspects in the efficiency and performance of the detectors: 1) the frequency with which the models are retrained, and 2) the data used for retraining.
• Efficient Query-Based Attack against ML-Based Android Malware Detection under Zero Knowledge Setting
  5 Sep 2023 1 repository listed
  The widespread adoption of the Android operating system has made malicious Android applications an appealing target for attackers.
• Level Up with ML Vulnerability Identification: Leveraging Domain Constraints in Feature Space for Robust Android Malware Detection
  30 May 2022 1 repository listed
  The primary approach to identifying vulnerable regions involves investigating realizable AEs, but generating these feasible apps poses a challenge.
• Towards a Fair Comparison and Realistic Evaluation Framework of Android Malware Detectors based on Static Analysis and Machine Learning
  25 May 2022 1 repository listed
  As in other cybersecurity areas, machine learning (ML) techniques have emerged as a promising solution to detect Android malware.
• MaMaDroid2.0 -- The Holes of Control Flow Graphs
  28 Feb 2022 1 repository listed
  The changes in the ratio between benign and malicious samples have a clear effect on each one of the models, resulting in a decrease of more than 40% in their detection rate.
• EvadeDroid: A Practical Evasion Attack on Machine Learning for Black-box Android Malware Detection
  7 Oct 2021 1 repository listed
  The proposed manipulation technique is a query-efficient optimization algorithm that can find and inject optimal sequences of transformations into malware apps.
• Can We Leverage Predictive Uncertainty to Detect Dataset Shift and Adversarial Examples in Android Malware Detection?
  20 Sep 2021 1 repository listed
  Our main findings are: (i) predictive uncertainty indeed helps achieve reliable malware detection in the presence of dataset shift, but cannot cope with adversarial evasion attacks; (ii) approximate Bayesian methods are…
• DexRay: A Simple, yet Effective Deep Learning Approach to Android Malware Detection based on Image Representation of Bytecode
  5 Sep 2021 1 repository listed
  This work-in-progress paper contributes to the domain of Deep Learning based Malware detection by providing a sound, simple, yet effective approach (with available artefacts) that can be the basis to scope the many…
• heterogeneous temporal graph transformer: an intelligent system for evolving android malware detection
  14 Aug 2021 1 repository listed
  To capture malware evolution, we further consider the temporal dependence and introduce a heterogeneous temporal graph to jointly model malware propagation and evolution by considering heterogeneous spatial dependencies…
• Deep Learning for Android Malware Defenses: a Systematic Literature Review
  9 Mar 2021 1 repository listed
  In this paper, we conducted a systematic literature review to search and analyze how deep learning approaches have been applied in the context of malware defenses in the Android environment.
• Why an Android App is Classified as Malware? Towards Malware Classification Interpretation
  24 Apr 2020 1 repository listed
  In this paper, to fill this gap, we propose a novel and interpretable ML-based approach (named XMal) to classify malware with high accuracy and explain the classification result meanwhile.
• AndrODet: An Adaptive Android Obfuscation Detector
  1 Jan 2019 1 repository listed
  This is typically applied to protect intellectual property in benign apps, or to hinder the process of extracting actionable information in the case malware.