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Using probabilistic generative models for ranking risks of Android apps

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/spe.v39:11openalex-snapshot

inferredcites →https://doi.org/10.1007/978-3-642-17758-3_17openalex-snapshot

Applying Behavioral Detection on Android-Based Devices

inferredcites →https://doi.org/10.1007/978-3-642-28166-2_11openalex-snapshot

Plagiarizing Smartphone Applications: Attack Strategies and Defense Techniques

inferredcites →https://doi.org/10.1007/bf00056168openalex-snapshot

Consumer processing of hazard warning information

inferredcites →https://doi.org/10.1109/acsac.2009.39openalex-snapshot

Semantically Rich Application-Centric Security in Android

inferredcites →https://doi.org/10.1109/sp.2012.16openalex-snapshot

Dissecting Android Malware: Characterization and Evolution

inferredcites →https://doi.org/10.1145/1653662.1653691openalex-snapshot

On lightweight mobile phone application certification

inferredcites →https://doi.org/10.1145/1755688.1755732openalex-snapshot

Apex

inferredcites →https://doi.org/10.1145/1837110.1837112openalex-snapshot

Do windows users follow the principle of least privilege?

inferredcites →https://doi.org/10.1145/1866307.1866317openalex-snapshot

A methodology for empirical analysis of permission-based security models and its application to android

inferredcites →https://doi.org/10.1145/1920261.1920313openalex-snapshot

Paranoid Android

inferredcites →https://doi.org/10.1145/2046614.2046626openalex-snapshot

Short paper

inferredcites →https://doi.org/10.1145/2046707.2046779openalex-snapshot

Android permissions demystified

inferredcites →https://doi.org/10.1145/2295136.2295141openalex-snapshot

Android permissions

inferredcites →https://doi.org/10.1145/967900.967989openalex-snapshot

Naive Bayes vs decision trees in intrusion detection systems

inferredcites →https://doi.org/10.1177/074391569401300101openalex-snapshot

Intended and Unintended Consequences of Warning Messages: A Review and Synthesis of Empirical Research

inferredcites →https://doi.org/10.3115/1067807.1067848openalex-snapshot

A comparison of event models for Naive Bayes anti-spam e-mail filtering

inferredcites →https://doi.org/10.5555/1924943.1924971openalex-snapshot

TaintDroid: an information-flow tracking system for realtime privacy monitoring on smartphones

inferredcites →https://doi.org/10.5555/944919.944937openalex-snapshot

Latent dirichlet allocation

inferredcites →https://doi.org/10.7551/mitpress/1120.003.0082openalex-snapshot

Latent Dirichlet Allocation

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.3457018openalex-extracted

Delaying Informed Consent: An Empirical Investigation of Mobile Apps' Upgrade Decisions

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inferred← citeshttps://doi.org/10.1002/cpe.6571openalex-snapshot

Security‐centric ranking algorithm and two privacy scores to mitigate intrusive apps

inferred← citeshttps://doi.org/10.1002/ett.3016openalex-snapshot

Identifying Android malware with system call co‐occurrence matrices

inferred← citeshttps://doi.org/10.1002/ett.3675openalex-snapshot

Android malware detection through generative adversarial networks

inferred← citeshttps://doi.org/10.1002/sec.1430openalex-snapshot

DroidScreening: a practical framework for real‐world Android malware analysis

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Measuring the risk value of sensitive dataflow path in Android applications

inferred← citeshttps://doi.org/10.1002/widm.1456openalex-snapshot

Gaining insights in datasets in the shade of “garbage in, garbage out” rationale: Feature space distribution fitting

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Android Malware Detection Using Category-Based Permission Vectors

inferred← citeshttps://doi.org/10.1007/978-3-030-12981-1_52openalex-snapshot

Using Hybrid Model for Android Malicious Application Detection Based on Population (Short Paper)

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Machine Learning Approach to Detect Malicious Mobile Apps

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On the Data Privacy, Security, and Risk Postures of IoT Mobile Companion Apps

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Android Malware Detection Using Deep Learning

inferred← citeshttps://doi.org/10.1007/978-3-031-15784-4_24openalex-snapshot

Enhancing Security Mechanism in Smart Phones Using Crowdsourcing

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Bayesian Learned Models Can Detect Adversarial Malware for Free

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Comprehensive Behavior Profiling for Proactive Android Malware Detection

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Are Your Training Datasets Yet Relevant?

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Privacy Requirements in Toy Computing

inferred← citeshttps://doi.org/10.1007/978-3-319-22915-7_41openalex-snapshot

Detection and Mitigation of Android Malware Through Hybrid Approach

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Evaluating Op-Code Frequency Histograms in Malware and Third-Party Mobile Applications

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Privacy-Enhanced Android for Smart Cities Applications

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Android Malware Detection Method Based on Function Call Graphs

inferred← citeshttps://doi.org/10.1007/978-3-319-47812-8_1openalex-snapshot

Introduction

inferred← citeshttps://doi.org/10.1007/978-3-319-47812-8_2openalex-snapshot

Background

inferred← citeshttps://doi.org/10.1007/978-3-319-47812-8_3openalex-snapshot

Semantics-Aware Android Malware Classification

inferred← citeshttps://doi.org/10.1007/978-3-319-59439-2_3openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/978-3-319-64701-2_14openalex-snapshot

DNA-Droid: A Real-Time Android Ransomware Detection Framework

inferred← citeshttps://doi.org/10.1007/978-3-319-69659-1_15openalex-snapshot

How to Make Information-Flow Analysis Based Defense Ineffective: An ART Behavior-Mask Attack

inferred← citeshttps://doi.org/10.1007/978-3-319-72598-7_12openalex-snapshot

Malicious Application Detection on Android Smartphones with Enhanced Static-Dynamic Analysis

inferred← citeshttps://doi.org/10.1007/978-3-319-78753-4_8openalex-snapshot

Empirical Analysis of Static Code Metrics for Predicting Risk Scores in Android Applications

inferred← citeshttps://doi.org/10.1007/978-3-319-78813-5_23openalex-snapshot

Visual Analysis of Android Malware Behavior Profile Based on $$PMCG_{droid}$$ : A Pruned Lightweight APP Call Graph

inferred← citeshttps://doi.org/10.1007/978-3-319-95933-7_10openalex-snapshot

Feature Analysis and Risk Assessment of Android Group Based on Clustering

inferred← citeshttps://doi.org/10.1007/978-3-642-38631-2_14openalex-snapshot

MADS: Malicious Android Applications Detection through String Analysis

inferred← citeshttps://doi.org/10.1007/978-981-10-8536-9_27openalex-snapshot

Statistical Approach Using Meta Features for Android Malware Detection System

inferred← citeshttps://doi.org/10.1007/978-981-13-1936-5_49openalex-snapshot

Comprehensive Behaviour of Malware Detection Using the Machine Learning Classifier

inferred← citeshttps://doi.org/10.1007/978-981-13-6052-7_42openalex-snapshot

Malwares Detection for Android and Windows System by Using Machine Learning and Data Mining

inferred← citeshttps://doi.org/10.1007/978-981-15-7345-3_44openalex-snapshot

A Novel Mechanism for Fraud Rank Detection in Social Networks

inferred← citeshttps://doi.org/10.1007/978-981-15-7981-3_31openalex-snapshot

Android Vault Application Behavior Analysis and Detection

inferred← citeshttps://doi.org/10.1007/978-981-16-3150-4_6openalex-snapshot

Android Malware Detection Method Based on App-Image Conversion

inferred← citeshttps://doi.org/10.1007/978-981-96-6294-4_17openalex-snapshot

An Accurate and Robust Deep Learning-Based Stacked Generalization Method for Android Malware Detection

inferred← citeshttps://doi.org/10.1007/978-981-99-7783-3_13openalex-snapshot

DeMAndApp: Detecting Malicious Android App

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Reliability score inference and recommendation using fuzzy-based technique for social media applications

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Entropy-based security risk measurement for Android mobile applications

inferred← citeshttps://doi.org/10.1007/s00500-025-10489-zopenalex-snapshot

Robust security risk estimation for android apps using nearest neighbor approach and hamming distance

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A deep learning system for health care IoT and smartphone malware detection

inferred← citeshttps://doi.org/10.1007/s00521-020-05450-0openalex-snapshot

Hybrid classification of Android malware based on fuzzy clustering and the gradient boosting machine

inferred← citeshttps://doi.org/10.1007/s10115-016-0918-zopenalex-snapshot

ALDROID: efficient update of Android anti-virus software using designated active learning methods

inferred← citeshttps://doi.org/10.1007/s10207-014-0250-0openalex-snapshot

Mobile-Sandbox: combining static and dynamic analysis with machine-learning techniques

inferred← citeshttps://doi.org/10.1007/s10207-024-00822-2openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s10207-025-01170-5openalex-snapshot

PICCdroid: A novel permissions and intent correlation coefficient based android malware detection method

inferred← citeshttps://doi.org/10.1007/s10515-025-00542-4openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s10586-017-0944-yopenalex-snapshot

Deep neural architectures for large scale android malware analysis

inferred← citeshttps://doi.org/10.1007/s10586-017-1260-2openalex-snapshot

Detecting sensitive data leakage via inter-applications on Android using a hybrid analysis technique

inferred← citeshttps://doi.org/10.1007/s10586-020-03083-5openalex-snapshot

Can machine learning model with static features be fooled: an adversarial machine learning approach

inferred← citeshttps://doi.org/10.1007/s10916-018-0966-xopenalex-snapshot

Root Exploit Detection and Features Optimization: Mobile Device and Blockchain Based Medical Data Management

inferred← citeshttps://doi.org/10.1007/s11036-019-01248-0openalex-snapshot

AdDroid: Rule-Based Machine Learning Framework for Android Malware Analysis

inferred← citeshttps://doi.org/10.1007/s11042-017-4586-0openalex-snapshot

Bio-inspired computational paradigm for feature investigation and malware detection: interactive analytics

inferred← citeshttps://doi.org/10.1007/s11042-024-18511-6openalex-snapshot

IPAnalyzer: A novel Android malware detection system using ranked Intents and Permissions

inferred← citeshttps://doi.org/10.1007/s11235-017-0296-1openalex-snapshot

Towards a threat assessment framework for apps collusion

inferred← citeshttps://doi.org/10.1007/s11280-017-0456-yopenalex-snapshot

Personalized app recommendation based on app permissions

inferred← citeshttps://doi.org/10.1007/s11416-016-0277-zopenalex-snapshot

Identification of malicious android app using manifest and opcode features

inferred← citeshttps://doi.org/10.1007/s12652-021-03376-6openalex-snapshot

A novel Android malware detection system: adaption of filter-based feature selection methods

inferred← citeshttps://doi.org/10.1007/s13042-021-01393-7openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s40010-026-01095-1openalex-snapshot

Smali Opcode-Based Android Malware Detection and Obfuscation Identification

inferred← citeshttps://doi.org/10.1007/s41019-022-00189-1openalex-snapshot

A Risk Estimation Mechanism for Android Apps based on Hybrid Analysis

inferred← citeshttps://doi.org/10.1007/s42488-019-00015-wopenalex-snapshot

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inferred← citeshttps://doi.org/10.1007/s42524-022-0228-yopenalex-snapshot

Large-scale App privacy governance

inferred← citeshttps://doi.org/10.1007/s42979-022-01543-wopenalex-snapshot

A Review on Malware Analysis for IoT and Android System

inferred← citeshttps://doi.org/10.1007/s43926-023-00047-0openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.asoc.2020.106089openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.cola.2019.03.004openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.comcom.2020.02.078openalex-snapshot

Towards predictive analysis of android vulnerability using statistical codes and machine learning for IoT applications

inferred← citeshttps://doi.org/10.1016/j.cose.2014.11.001openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.cose.2015.12.005openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.cose.2016.11.007openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.cose.2017.03.011openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.cose.2020.101750openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.cose.2021.102399openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.cosrev.2020.100358openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.diin.2015.02.001openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.diin.2015.06.002openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.diin.2016.04.013openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.diin.2018.01.001openalex-snapshot

An in-depth analysis of Android malware using hybrid techniques

inferred← citeshttps://doi.org/10.1016/j.dss.2016.09.006openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.eswa.2013.07.106openalex-snapshot

Dendroid: A text mining approach to analyzing and classifying code structures in Android malware families

inferred← citeshttps://doi.org/10.1016/j.future.2016.05.035openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.future.2017.01.019openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.future.2017.04.041openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.future.2018.06.053openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.future.2019.07.070openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.future.2020.03.052openalex-snapshot

Decompiled APK based malicious code classification

inferred← citeshttps://doi.org/10.1016/j.infsof.2016.03.004openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.infsof.2020.106290openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.intmar.2018.12.001openalex-snapshot

App Adoption: The Effect on Purchasing of Customers who have Used a Mobile Website Previously

inferred← citeshttps://doi.org/10.1016/j.jisa.2018.02.002openalex-snapshot

Instance based security risk value estimation for Android applications

inferred← citeshttps://doi.org/10.1016/j.jisa.2020.102718openalex-snapshot

Multi-view deep learning for zero-day Android malware detection

inferred← citeshttps://doi.org/10.1016/j.knosys.2018.03.018openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.measurement.2018.10.034openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.neucom.2017.07.030openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.procs.2020.06.081openalex-snapshot

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inferred← citeshttps://doi.org/10.1016/j.procs.2021.09.105openalex-snapshot

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inferred← citeshttps://doi.org/10.1049/iet-ifs.2013.0095openalex-snapshot

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inferred← citeshttps://doi.org/10.1049/iet-ifs.2014.0099openalex-snapshot

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inferred← citeshttps://doi.org/10.1080/01969722.2013.803889openalex-snapshot

MAMA: MANIFEST ANALYSIS FOR MALWARE DETECTION IN ANDROID

inferred← citeshttps://doi.org/10.1093/comjnl/bxz109openalex-snapshot

New Security Risk Value Estimate Method for Android Applications

inferred← citeshttps://doi.org/10.1109/access.2017.2771470openalex-snapshot

Machine Learning-Based Malicious Application Detection of Android

inferred← citeshttps://doi.org/10.1109/access.2018.2815660openalex-snapshot

Malware Threats and Detection for Industrial Mobile-IoT Networks

inferred← citeshttps://doi.org/10.1109/access.2018.2864992openalex-snapshot

EasyPrivacy: Context-Aware Resource Usage Control System for Android Platform

inferred← citeshttps://doi.org/10.1109/access.2020.2974911openalex-snapshot

Engineering Privacy in Smartphone Apps: A Technical Guideline Catalog for App Developers

inferred← citeshttps://doi.org/10.1109/access.2021.3049819openalex-snapshot

Detection, Traceability, and Propagation of Mobile Malware Threats

inferred← citeshttps://doi.org/10.1109/access.2024.3501277openalex-snapshot

Malware Detection and Classification in Android Application Using Simhash-Based Feature Extraction and Machine Learning

inferred← citeshttps://doi.org/10.1109/acdsa65407.2025.11166547openalex-snapshot

High-Accuracy Android Ransomware Detection Using SMALI Code-Based Analysis

inferred← citeshttps://doi.org/10.1109/aisp.2017.8324089openalex-snapshot

A novel method to detect android malware using Locality Sensitive Hashing algorithms

inferred← citeshttps://doi.org/10.1109/ares.2015.57openalex-snapshot

Effectiveness of Opcode ngrams for Detection of Multi Family Android Malware

inferred← citeshttps://doi.org/10.1109/ase.2019.00023openalex-snapshot

MalScan: Fast Market-Wide Mobile Malware Scanning by Social-Network Centrality Analysis

inferred← citeshttps://doi.org/10.1109/asew.2015.17openalex-snapshot

Extending Manual GUI Testing Beyond Defects by Building Mental Models of Software Behavior

inferred← citeshttps://doi.org/10.1109/auteee50969.2020.9315607openalex-snapshot

Malware Detection Based on Feature Library and Machine Learning

inferred← citeshttps://doi.org/10.1109/bigdata47090.2019.9005669openalex-snapshot

Identifying Android Malware Families Using Android-Oriented Metrics

inferred← citeshttps://doi.org/10.1109/bigdata47090.2019.9005989openalex-snapshot

ACE – An Anomaly Contribution Explainer for Cyber-Security Applications

inferred← citeshttps://doi.org/10.1109/cic.2017.00021openalex-snapshot

Detecting Android Malwares by Mining Statically Registered Broadcast Receivers

inferred← citeshttps://doi.org/10.1109/cis.2016.0145openalex-snapshot

Mmda: Metadata Based Malware Detection on Android

inferred← citeshttps://doi.org/10.1109/cit.2016.76openalex-snapshot

An Android Malware Detection Approach Using Bayesian Inference

inferred← citeshttps://doi.org/10.1109/cns.2014.6997523openalex-snapshot

DroidGraph: discovering Android malware by analyzing semantic behavior

inferred← citeshttps://doi.org/10.1109/cns53000.2021.9705047openalex-snapshot

Automatic Detection of Android Steganography Apps via Symbolic Execution and Tree Matching

inferred← citeshttps://doi.org/10.1109/cogsima.2013.6523820openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/compcomm.2015.7387530openalex-snapshot

Using association statistics to rank risk of Android application

inferred← citeshttps://doi.org/10.1109/compsac.2015.103openalex-snapshot

MARVIN: Efficient and Comprehensive Mobile App Classification through Static and Dynamic Analysis

inferred← citeshttps://doi.org/10.1109/cscloud.2015.21openalex-snapshot

Survey on Privacy Protection of Android Devices

inferred← citeshttps://doi.org/10.1109/dsc.2017.13openalex-snapshot

FgDetector: Fine-Grained Android Malware Detection

inferred← citeshttps://doi.org/10.1109/dsn.2014.30openalex-snapshot

On Tracking Information Flows through JNI in Android Applications

inferred← citeshttps://doi.org/10.1109/eurosp.2017.24openalex-snapshot

LUNA: Quantifying and Leveraging Uncertainty in Android Malware Analysis through Bayesian Machine Learning

inferred← citeshttps://doi.org/10.1109/eurosp51992.2021.00044openalex-snapshot

ANDRuspex: Leveraging Graph Representation Learning to Predict Harmful App Installations on Mobile Devices

inferred← citeshttps://doi.org/10.1109/glocom.2013.6831175openalex-snapshot

Detecting GPS information leakage in Android applications

inferred← citeshttps://doi.org/10.1109/glocom.2014.7417472openalex-snapshot

Claim What You Need: A Text-Mining Approach on Android Permission Request Authorization

inferred← citeshttps://doi.org/10.1109/glocom.2015.7417472openalex-snapshot

Claim What You Need: A Text-Mining Approach on Android Permission Request Authorization

inferred← citeshttps://doi.org/10.1109/hpcc-smartcity-dss.2016.0211openalex-snapshot

The Concept of Attack Scenarios and Its Applications in Android Malware Detection

inferred← citeshttps://doi.org/10.1109/ic3.2015.7346711openalex-snapshot

Heterogeneous feature space for Android malware detection

inferred← citeshttps://doi.org/10.1109/icact.2015.7224777openalex-snapshot

DroidExec: Root exploit malware recognition against wide variability via folding redundant function-relation graph

inferred← citeshttps://doi.org/10.1109/icaiqsa64000.2024.10882428openalex-snapshot

TrojanDroid: Leveraging Machine Learning for Robust Android Malware Detection

inferred← citeshttps://doi.org/10.1109/icc.2014.6883451openalex-snapshot

RemindU: A secure and efficient location based reminder system

inferred← citeshttps://doi.org/10.1109/icccn.2016.7568487openalex-snapshot

ActivityHijacker: Hijacking the Android Activity Component for Sensitive Data

inferred← citeshttps://doi.org/10.1109/icccn61486.2024.10637591openalex-snapshot

Improving Android Malware Detection with Entropy Bytecode-to-Image Encoding Framework

inferred← citeshttps://doi.org/10.1109/iccecome.2018.8659213openalex-snapshot

Risk Identification of Personally Identifiable Information from Collective Mobile App Data

inferred← citeshttps://doi.org/10.1109/iccnc.2018.8390391openalex-snapshot

An Android Malware Detection Approach Using Weight-Adjusted Deep Learning

inferred← citeshttps://doi.org/10.1109/iccpct.2015.7159512openalex-snapshot

Cloud based security solution for android smartphones

inferred← citeshttps://doi.org/10.1109/iccsnt.2015.7490915openalex-snapshot

Two effective methods to detect mobile malware

inferred← citeshttps://doi.org/10.1109/icdcs.2015.37openalex-snapshot

Towards Understanding the Advertiser's Perspective of Smartphone User Privacy

inferred← citeshttps://doi.org/10.1109/icdcs.2017.297openalex-snapshot

Understanding the Market-Level and Network-Level Behaviors of the Android Malware Ecosystem

inferred← citeshttps://doi.org/10.1109/icdm.2012.86openalex-snapshot

Mining Permission Request Patterns from Android and Facebook Applications

inferred← citeshttps://doi.org/10.1109/icisce.2016.161openalex-snapshot

Ultra-Lightweight Malware Detection of Android Using 2-Level Machine Learning

inferred← citeshttps://doi.org/10.1109/icmla.2014.10openalex-snapshot

High Precision Screening for Android Malware with Dimensionality Reduction

inferred← citeshttps://doi.org/10.1109/icmlc.2014.7009096openalex-snapshot

Static detection of Android malware by using permissions and API calls

inferred← citeshttps://doi.org/10.1109/icmlc.2018.8526997openalex-snapshot

Onamd: An Online Android Malware Detection Approach

inferred← citeshttps://doi.org/10.1109/icoei48184.2020.9142880openalex-snapshot

Malware Detection in Smartphone Using SVM

inferred← citeshttps://doi.org/10.1109/icse.2015.50openalex-snapshot

AppContext: Differentiating Malicious and Benign Mobile App Behaviors Using Context

inferred← citeshttps://doi.org/10.1109/icsess.2015.7339027openalex-snapshot

MalDetector-using permission combinations to evaluate malicious features of Android App

inferred← citeshttps://doi.org/10.1109/iemcon.2017.8117152openalex-snapshot

AndroPIn: Correlating Android permissions and intents for malware detection

inferred← citeshttps://doi.org/10.1109/iiai-aai.2016.237openalex-snapshot

Merging Permission and API Features for Android Malware Detection

inferred← citeshttps://doi.org/10.1109/iiki.2015.34openalex-snapshot

PAPDroid: Personalization Awareness Privacy Protection in Android

inferred← citeshttps://doi.org/10.1109/iscisc.2016.7736461openalex-snapshot

A new approach for effective malware detection in Android-based devices

inferred← citeshttps://doi.org/10.1109/iscisc.2017.8488366openalex-snapshot

Proposing a New Feature for Structure-Aware Analysis of Android Malwares

inferred← citeshttps://doi.org/10.1109/isdfs.2017.7916512openalex-snapshot

Clustering and visualization of mobile application permissions for end users and malware analysts

inferred← citeshttps://doi.org/10.1109/issre.2015.7381837openalex-snapshot

Piecing together app behavior from multiple artifacts: A case study

inferred← citeshttps://doi.org/10.1109/itnec48623.2020.9085180openalex-snapshot

An Intelligent Recommendation Mobile Application Privacy Risk Evaluation Method Based on Optimized SVM

inferred← citeshttps://doi.org/10.1109/malware.2015.7413684openalex-snapshot

Automatically combining static malware detection techniques

inferred← citeshttps://doi.org/10.1109/milcom.2013.170openalex-snapshot

Rapid Permissions-Based Detection and Analysis of Mobile Malware Using Random Decision Forests

inferred← citeshttps://doi.org/10.1109/mobilecloud.2014.22openalex-snapshot

A Two-Layered Permission-Based Android Malware Detection Scheme

inferred← citeshttps://doi.org/10.1109/mobilesoft.2017.14openalex-snapshot

Predicting Android Application Security and Privacy Risk with Static Code Metrics

inferred← citeshttps://doi.org/10.1109/mobilesoft.2017.22openalex-snapshot

ACCUSE: Helping Users to Minimize Android App Privacy Concerns

inferred← citeshttps://doi.org/10.1109/msr.2017.57openalex-snapshot

Euphony: Harmonious Unification of Cacophonous Anti-Virus Vendor Labels for Android Malware

inferred← citeshttps://doi.org/10.1109/ngmast.2014.23openalex-snapshot

Android Malware Detection Using Parallel Machine Learning Classifiers

inferred← citeshttps://doi.org/10.1109/pst.2017.00039openalex-snapshot

How Much Privilege Does an App Need? Investigating Resource Usage of Android Apps (Short Paper)

inferred← citeshttps://doi.org/10.1109/qrs.2015.36openalex-snapshot

Potential Component Leaks in Android Apps: An Investigation into a New Feature Set for Malware Detection

inferred← citeshttps://doi.org/10.1109/qrs.2015.37openalex-snapshot

Machine Learning Based Hybrid Behavior Models for Android Malware Analysis

inferred← citeshttps://doi.org/10.1109/raics.2015.7488446openalex-snapshot

Efficient risk analysis for Android applications

inferred← citeshttps://doi.org/10.1109/sai.2015.7237302openalex-snapshot

Android malware detection: An eigenspace analysis approach

inferred← citeshttps://doi.org/10.1109/saner48275.2020.9054863openalex-snapshot

Resource Race Attacks on Android

inferred← citeshttps://doi.org/10.1109/saner56733.2023.00065openalex-snapshot

RGDroid: Detecting Android Malware with Graph Convolutional Networks against Structural Attacks

inferred← citeshttps://doi.org/10.1109/sera65747.2025.11154598openalex-snapshot

Stealthy No More: An Effective Ensemble Learning Approach for Detecting Android RATs

inferred← citeshttps://doi.org/10.1109/smartiot52359.2021.00044openalex-snapshot

A Risk Assessment Mechanism for Android Apps

inferred← citeshttps://doi.org/10.1109/sp.2016.29openalex-snapshot

Following Devil's Footprints: Cross-Platform Analysis of Potentially Harmful Libraries on Android and iOS

inferred← citeshttps://doi.org/10.1109/spw.2016.33openalex-snapshot

Analysis of Code Heterogeneity for High-Precision Classification of Repackaged Malware

inferred← citeshttps://doi.org/10.1109/surv.2013.101613.00077openalex-snapshot

Evolution, Detection and Analysis of Malware for Smart Devices

inferred← citeshttps://doi.org/10.1109/tase.2015.16openalex-snapshot

An Effective Approach to Measuring and Assessing the Risk of Android Application

inferred← citeshttps://doi.org/10.1109/tase.2018.00015openalex-snapshot

RepassDroid: Automatic Detection of Android Malware Based on Essential Permissions and Semantic Features of Sensitive APIs

inferred← citeshttps://doi.org/10.1109/tc.2022.3143439openalex-snapshot

Lightweight, Effective Detection and Characterization of Mobile Malware Families

inferred← citeshttps://doi.org/10.1109/tdsc.2013.58openalex-snapshot

Effective Risk Communication for Android Apps

inferred← citeshttps://doi.org/10.1109/tdsc.2014.2302293openalex-snapshot

Generating Summary Risk Scores for Mobile Applications

inferred← citeshttps://doi.org/10.1109/tdsc.2014.2355839openalex-snapshot

A Probabilistic Discriminative Model for Android Malware Detection with Decompiled Source Code

inferred← citeshttps://doi.org/10.1109/tdsc.2014.2366457openalex-snapshot

Towards Automated Risk Assessment and Mitigation of Mobile Applications

inferred← citeshttps://doi.org/10.1109/tdsc.2017.2700270openalex-snapshot

Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection

inferred← citeshttps://doi.org/10.1109/tdsc.2017.2745575openalex-snapshot

Detection of Repackaged Android Malware with Code-Heterogeneity Features

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