Research graph
References from On the effectiveness of memory analysis in revealing maliciousness in android applications. Local targets link to admitted publications; unresolved targets remain external evidence.
Limits of static analysis for malware detection
2007 · External reference
Drebin: effective and explainable detection of android malware in your pocket
2014 · External reference
Mamadroid: detecting android malware by building Markov chains of behavioral models (Extended version)
10.1145/3313391 · 2019 · External reference
Didroid: android malware classification and characterization using deep image learning
2020 · External reference
Entroplyzer: android malware classification and characterization using entropy analysis of dynamic characteristics
2021 · External reference
Yes, machine learning can be more secure! a case study on android malware detection
10.1109/tdsc.2017.2700270 · 2019 · External reference
Adversarial patterns: building robust android malware classifiers
10.1145/3717607 · 2025 · External reference
A comprehensive analysis of adversarial attacks against android’s malware detection models
2025 · External reference
The evolution of android malware and android analysis techniques
10.1145/3017427 · 2017 · External reference
Andrubis – 1,000,000 apps later: a view on current android malware behaviors
2014 · External reference
Android malware classification using optimum feature selection and ensemble machine learning
10.1016/j.iotcps.2023.03.001 · 2023 · External reference
Light up that droid! on the effectiveness of static analysis features against app obfuscation for android malware detection
10.1016/j.jnca.2024.104094 · 2025 · External reference
Data drift in android malware detection
2024 · External reference
Unmasking the veiled: a comprehensive analysis of android evasive malware
10.1145/3634737.3637658 · 2024 · External reference
Challenging antivirus against elusive android malware over time
2025 · External reference
Analyzing the impact of obfuscation on the runtime execution of android apps at kernel level
2024 · External reference
On the feasibility of android stegomalware: a detection study
2025 · External reference
Analysis and detection of android stegomalware: the impact of the loading stage
10.1145/3733102.3733122 · 2025 · External reference
Would you mind hiding my malware? Building malicious android apps with stegopack
10.1016/j.pmcj.2025.102060 · 2025 · External reference
cRGB_mem: at the intersection of memory forensics and machine learning
2023 · External reference
Malware images: visualization and automatic classification
10.1145/2016904.2016908 · 2011 · External reference
Windows malware detector using convolutional neural network based on visualization images
10.1109/tetc.2019.2910086 · 2021 · External reference
Robustness of image-based malware classification models trained with generative adversarial networks
10.1145/3590777.3590792 · 2023 · External reference
From malware samples to fractal images: a new paradigm for classification
10.1016/j.matcom.2023.11.032 · 2024 · External reference
Dexray: a simple, yet effective deep learning approach to android malware detection based on image representation of bytecode
10.1007/978-3-030-87839-9_4 · 2021 · External reference
Adversarial examples for semantic segmentation and object detection
2017 · External reference
Fooling automated surveillance cameras: adversarial patches to attack person detection
2019 · External reference
Universal physical camouflage attacks on object detectors
2020 · External reference
Adversarial EXEmples: a survey and experimental evaluation of practical attacks on machine learning for windows malware detection
10.1145/3473039 · 2021 · External reference
Adversarial example attacks in the physical world
10.1007/978-3-030-62460-6_51 · 2020 · External reference
From image to code: executable adversarial examples of android applications
10.1145/3404555.3404574 · 2020 · External reference
A survey on practical adversarial examples for malware classifiers
2021 · External reference
Adversarial malware binaries: evading deep learning for malware detection in executables
2018 · External reference
Arms race in adversarial malware detection: a survey
10.1145/3484491 · 2021 · External reference
Androzoo: collecting millions of android apps for the research community
10.1145/2901739.2903508 · 2016 · External reference
Unresolved reference
External reference
Unresolved reference
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A systematic literature review of android malware detection using static analysis
10.1109/access.2020.3002842 · 2020 · External reference
Enhancing android malware detection explainability through function call graph APIs
2024 · External reference
DroidScribe: classifying android malware based on runtime behavior
2016 · External reference
CANDYMAN: classifying android malware families by modelling dynamic traces with Markov chains
10.1016/j.engappai.2018.06.006 · 2018 · External reference
Droiddetector: android malware characterization and detection using deep learning
10.1109/tst.2016.7399288 · 2016 · External reference
SAMADroid: a novel 3-level hybrid malware detection model for android operating system
10.1109/access.2018.2792941 · 2018 · External reference
A comparison of graph neural networks for malware classification
10.1007/s11416-023-00493-y · 2024 · External reference
Volmemdroid-investigating android malware insights with volatile memory artifacts
10.1016/j.eswa.2024.124347 · 2024 · External reference
Unresolved reference
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Unresolved reference
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10.5220/0010603600002998
10.5220/0010603600002998 · External reference
Real-time triggering of android memory dumps for stealthy attack investigation
10.1007/978-3-030-70852-8_2 · 2021 · External reference
Responding to targeted stealthy attacks on android using timely-captured memory dumps
10.1109/access.2022.3160531 · 2022 · External reference
Unresolved reference
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Unresolved reference
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DroidScraper: a tool for android in-memory object recovery and reconstruction
2019 · External reference
“Tipped off by your memory allocator”: device-wide user activity sequencing from android memory images (Timeliner)
2018 · External reference
Vedrando: a novel way to reveal stealthy attack steps on android through memory forensics
10.3390/jcp3030019 · 2023 · External reference
A survey on deep learning in medical image analysis
10.1016/j.media.2017.07.005 · 2017 · External reference
A guide to deep learning in healthcare
10.1038/s41591-018-0316-z · 2019 · External reference
Are we ready for autonomous driving? The KITTI vision benchmark suite
2013 · External reference
Object detection in 20 years: a survey
2019 · External reference
You only look once: unified, real-time object detection
2016 · External reference
Unresolved reference
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Unresolved reference
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Unresolved reference
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Activation analysis of a byte-based deep neural network for malware classification
2019 · External reference
Malvis: large-scale bytecode visualization framework for explainable android malware detection
10.3390/jcp5040109 · 2025 · External reference
Index for rating diagnostic tests
10.1002/1097-0142(1950)3:1<32::aid-cncr2820030106>3.0.co;2-3 · 1950 · External reference
Unresolved reference
1998 · External reference
Color indexing
10.1007/bf00130487 · 1991 · External reference
Similarity of color images
1995 · External reference
Textural features for image classification
10.1109/tsmc.1973.4309314 · 1973 · External reference
Multiresolution gray-scale and rotation invariant texture classification with local binary patterns
10.1109/tpami.2002.1017623 · 2002 · External reference
Histograms of oriented gradients for human detection
2005 · External reference
Unresolved reference
External reference
Visual pattern recognition by moment invariants
10.1109/tit.1962.1057692 · 1962 · External reference
Unresolved reference
2018 · External reference
The curvelet transform for image denoising
10.1109/tip.2002.1014998 · 2002 · External reference
Unresolved reference
2016 · External reference
Deep learning
10.1038/nature14539 · 2015 · External reference
Unresolved reference
2016 · External reference
Generalizing from a few examples: a survey on few-shot learning
10.1145/3386252 · 2020 · External reference
Prototypical networks for few-shot learning
2017 · External reference
Android authorship attribution through string analysis
10.1145/3230833.3230849 · 2018 · External reference
Applying NLP techniques to malware detection in a practical environment
10.1007/s10207-021-00553-8 · 2022 · External reference
Grad-CAM: visual explanations from deep networks via gradient-based localization
2017 · External reference
Towards explainable CNNs for android malware detection
10.1016/j.procs.2021.03.118 · 2021 · External reference
DroidBot: a lightweight UI-guided test input generator for android
2017 · External reference
ImageNet: a large-scale hierarchical image database
2009 · External reference
Deep residual learning for image recognition
2016 · External reference
EfficientNet: rethinking model scaling for convolutional neural networks
2019 · External reference
MobileNets: efficient convolutional neural networks for mobile vision applications
2017 · External reference
ConvNeXt V2: co-designing and scaling convnets with masked autoencoders
2023 · External reference
An image is worth 16x16 words: transformers for image recognition at scale
2021 · External reference
Going deeper with convolutions
2015 · External reference
Very deep convolutional networks for large-scale image recognition
2015 · External reference
Resnet-based network for recognizing daily and transitional activities based on smartphone sensors
2022 · External reference
Index for rating diagnostic tests
10.1002/1097-0142(1950)3:1<32::aid-cncr2820030106>3.0.co;2-3 · ExternalCitation · doi-reference
Adversarial example attacks in the physical world
10.1007/978-3-030-62460-6_51 · ExternalCitation · doi-reference
Real-time triggering of android memory dumps for stealthy attack investigation
10.1007/978-3-030-70852-8_2 · ExternalCitation · doi-reference
Dexray: a simple, yet effective deep learning approach to android malware detection based on image representation of bytecode
10.1007/978-3-030-87839-9_4 · ExternalCitation · doi-reference
Color indexing
10.1007/bf00130487 · ExternalCitation · doi-reference
Applying NLP techniques to malware detection in a practical environment
10.1007/s10207-021-00553-8 · ExternalCitation · doi-reference
A comparison of graph neural networks for malware classification
10.1007/s11416-023-00493-y · ExternalCitation · doi-reference
CANDYMAN: classifying android malware families by modelling dynamic traces with Markov chains
10.1016/j.engappai.2018.06.006 · ExternalCitation · doi-reference
Volmemdroid-investigating android malware insights with volatile memory artifacts
10.1016/j.eswa.2024.124347 · ExternalCitation · doi-reference
Android malware classification using optimum feature selection and ensemble machine learning
10.1016/j.iotcps.2023.03.001 · ExternalCitation · doi-reference
Light up that droid! on the effectiveness of static analysis features against app obfuscation for android malware detection
10.1016/j.jnca.2024.104094 · ExternalCitation · doi-reference
From malware samples to fractal images: a new paradigm for classification
10.1016/j.matcom.2023.11.032 · ExternalCitation · doi-reference
A survey on deep learning in medical image analysis
10.1016/j.media.2017.07.005 · ExternalCitation · doi-reference
Would you mind hiding my malware? Building malicious android apps with stegopack
10.1016/j.pmcj.2025.102060 · ExternalCitation · doi-reference
Towards explainable CNNs for android malware detection
10.1016/j.procs.2021.03.118 · ExternalCitation · doi-reference
Deep learning
10.1038/nature14539 · ExternalCitation · doi-reference
A guide to deep learning in healthcare
10.1038/s41591-018-0316-z · ExternalCitation · doi-reference
SAMADroid: a novel 3-level hybrid malware detection model for android operating system
10.1109/access.2018.2792941 · ExternalCitation · doi-reference
A systematic literature review of android malware detection using static analysis
10.1109/access.2020.3002842 · ExternalCitation · doi-reference
Responding to targeted stealthy attacks on android using timely-captured memory dumps
10.1109/access.2022.3160531 · ExternalCitation · doi-reference
Yes, machine learning can be more secure! a case study on android malware detection
10.1109/tdsc.2017.2700270 · ExternalCitation · doi-reference
Windows malware detector using convolutional neural network based on visualization images
10.1109/tetc.2019.2910086 · ExternalCitation · doi-reference
The curvelet transform for image denoising
10.1109/tip.2002.1014998 · ExternalCitation · doi-reference
Visual pattern recognition by moment invariants
10.1109/tit.1962.1057692 · ExternalCitation · doi-reference
Multiresolution gray-scale and rotation invariant texture classification with local binary patterns
10.1109/tpami.2002.1017623 · ExternalCitation · doi-reference
Textural features for image classification
10.1109/tsmc.1973.4309314 · ExternalCitation · doi-reference
Droiddetector: android malware characterization and detection using deep learning
10.1109/tst.2016.7399288 · ExternalCitation · doi-reference
Malware images: visualization and automatic classification
10.1145/2016904.2016908 · ExternalCitation · doi-reference
Androzoo: collecting millions of android apps for the research community
10.1145/2901739.2903508 · ExternalCitation · doi-reference
The evolution of android malware and android analysis techniques
10.1145/3017427 · ExternalCitation · doi-reference
Android authorship attribution through string analysis
10.1145/3230833.3230849 · ExternalCitation · doi-reference
Mamadroid: detecting android malware by building Markov chains of behavioral models (Extended version)
10.1145/3313391 · ExternalCitation · doi-reference
Generalizing from a few examples: a survey on few-shot learning
10.1145/3386252 · ExternalCitation · doi-reference
From image to code: executable adversarial examples of android applications
10.1145/3404555.3404574 · ExternalCitation · doi-reference
Adversarial EXEmples: a survey and experimental evaluation of practical attacks on machine learning for windows malware detection
10.1145/3473039 · ExternalCitation · doi-reference
Arms race in adversarial malware detection: a survey
10.1145/3484491 · ExternalCitation · doi-reference
Robustness of image-based malware classification models trained with generative adversarial networks
10.1145/3590777.3590792 · ExternalCitation · doi-reference
Unmasking the veiled: a comprehensive analysis of android evasive malware
10.1145/3634737.3637658 · ExternalCitation · doi-reference
Adversarial patterns: building robust android malware classifiers
10.1145/3717607 · ExternalCitation · doi-reference
Analysis and detection of android stegomalware: the impact of the loading stage
10.1145/3733102.3733122 · ExternalCitation · doi-reference
Vedrando: a novel way to reveal stealthy attack steps on android through memory forensics
10.3390/jcp3030019 · ExternalCitation · doi-reference
Malvis: large-scale bytecode visualization framework for explainable android malware detection
10.3390/jcp5040109 · ExternalCitation · doi-reference
10.5220/0010603600002998
10.5220/0010603600002998 · ExternalCitation · doi-reference
