On the public citation graph
Malware detection on android smartphones using keywords vector and SVM
0 signed · 30 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-319-04283-1_6openalex-snapshot
DroidAPIMiner: Mining API-Level Features for Robust Malware Detection in Android
inferredcites →https://doi.org/10.1109/asiajcis.2012.18openalex-snapshot
DroidMat: Android Malware Detection through Manifest and API Calls Tracing
inferredcites →https://doi.org/10.1109/ictai.2013.53openalex-snapshot
Machine Learning for Android Malware Detection Using Permission and API Calls
inferredcites →https://doi.org/10.1145/1653662.1653691openalex-snapshot
On lightweight mobile phone application certification
inferredcites →https://doi.org/10.1145/2046707.2046779openalex-snapshot
Android permissions demystified
inferredcites →https://doi.org/10.1145/2133601.2133640openalex-snapshot
Detecting repackaged smartphone applications in third-party android marketplaces
inferredcites →https://doi.org/10.14722/ndss.2014.23247openalex-snapshot
Drebin: Effective and Explainable Detection of Android Malware in Your Pocket
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-030-29551-6_63openalex-snapshot
Permission-Based Feature Scaling Method for Lightweight Android Malware Detection
inferred← citeshttps://doi.org/10.1007/978-3-031-69986-3_6openalex-snapshot
Guarding the Digital Frontier: A Logistic Regression Approach to Malware Detection
inferred← citeshttps://doi.org/10.1007/s10207-024-00822-2openalex-snapshot
A comprehensive review on permissions-based Android malware detection
inferred← citeshttps://doi.org/10.1007/s10586-021-03459-1openalex-snapshot
An efficient malware detection approach with feature weighting based on Harris Hawks optimization
inferred← citeshttps://doi.org/10.1007/s12652-020-01957-5openalex-snapshot
RETRACTED ARTICLE: A novel permission ranking system for android malware detection—the permission grader
inferred← citeshttps://doi.org/10.1016/j.eswa.2022.117833openalex-snapshot
DroidMalwareDetector: A novel Android malware detection framework based on convolutional neural network
inferred← citeshttps://doi.org/10.1016/j.future.2019.03.041openalex-snapshot
Consumer-facing technology fraud: Economics, attack methods and potential solutions
inferred← citeshttps://doi.org/10.1016/j.jnca.2024.104021openalex-snapshot
PHIGrader: Evaluating the effectiveness of Manifest file components in Android malware detection using Multi Criteria Decision Making techniques
inferred← citeshttps://doi.org/10.1089/3dp.2022.0316openalex-snapshot
AI-Based Knowledge Extraction from the Bioprinting Literature for Identifying Technology Trends
inferred← citeshttps://doi.org/10.1109/access.2020.3007571openalex-snapshot
An Android Malware Detection Approach Based on SIMGRU
inferred← citeshttps://doi.org/10.1109/access.2025.3577775openalex-snapshot
Evaluating Lightweight Transformers With Local Explainability for Android Malware Detection
inferred← citeshttps://doi.org/10.1109/bitcon63716.2024.10985471openalex-snapshot
An Android Malware Detection Approach Based On SIMGRU
inferred← citeshttps://doi.org/10.1109/icaase51408.2020.9380104openalex-snapshot
Android Malware Detection using Convolutional Deep Neural Networks
inferred← citeshttps://doi.org/10.1109/iceccs.2019.00014openalex-snapshot
MobiDroid: A Performance-Sensitive Malware Detection System on Mobile Platform
inferred← citeshttps://doi.org/10.1109/tifs.2018.2866319openalex-snapshot
A Multimodal Deep Learning Method for Android Malware Detection Using Various Features
inferred← citeshttps://doi.org/10.1109/tifs.2020.3025436openalex-snapshot
A Performance-Sensitive Malware Detection System Using Deep Learning on Mobile Devices
inferred← citeshttps://doi.org/10.1145/3424978.3425005openalex-snapshot
Multi-classification of Android Applications Based on Convolutional Neural Networks
inferred← citeshttps://doi.org/10.4018/978-1-7998-8545-0.ch036openalex-snapshot
Towards Privacy Risk Analysis in Android Applications Using Machine Learning Approaches
inferred← citeshttps://doi.org/10.4018/ijesma.2019040101openalex-snapshot
Towards Privacy Risk Analysis in Android Applications Using Machine Learning Approaches
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.