Machine Learning-Based Malware Detection for Android Applications: History Matters!

Keywords

Malware, Computer science, Android (operating system), Machine learning, Artificial intelligence

References

• Mal-ID: Automatic Malware Detection Using Common Segment Analysis and Meta-FeaturesGil Tahan, Lior Rokach, Yuval Shaḥar — 2012
• Polonium: Tera-Scale Graph Mining for Malware DetectionDuen Horng Chau, Carey Nachenberg, Jeffrey Wilhelm — 2013
• A Study of Android Application SecurityWilliam Enck, Damien Octeau, Patrick McDaniel — 2011
• Classification of malware using structured control flowSilvio Cesare, Yang Xiang — 2010
• N-grams-based File Signatures for Malware DetectionIgor Santos, Yoseba K. Penya, Jaime Devesa — 2009
• A Survey of Malware Detection TechniquesNwokedi Idika, Aditya P. Mathur — 2007
• A New Android Malware Detection Approach Using Bayesian ClassificationS. Y. Yerima, S. Sezer, G. McWilliams — 2013
• A methodology for empirical analysis of permission-based security models and its application to androidDavid Barrera, H. Güneş Kayacık, Paul C. van Oorschot — 2010
• Reducing the window of opportunity for Android malware Gotta catch ’em allAxelle Apvrille, Tim Strazzere — 2012
• DroidMat: Android Malware Detection through Manifest and API Calls TracingDong-Jie Wu, Ching-Hao Mao, Te-En Wei — 2012
• Android botnets on the rise: Trends and characteristicsHeloise Pieterse, Martin S. Olivier — 2012
• Using probabilistic generative models for ranking risks of Android appsHao Peng, Chris Gates, Bhaskar Sarma — 2012
• Automatically securing permission-based software by reducing the attack surface: an application to AndroidAlexandre Bartel, Jacques Klein, Yves Le Traon — 2012
• A Classifier of Malicious Android ApplicationsGerardo Canfora, Francesco Mercaldo, Corrado Aaron Visaggio — 2013
• A Machine Learning Approach to Android Malware DetectionJustin Sahs, Latifur Khan — 2012
• MAST: triage for market-scale mobile malware analysisSaurabh Chakradeo, Bradley Reaves, Patrick Traynor — 2013
• Smartphone Dual Defense Protection Framework: Detecting Malicious Applications in Android MarketsXin Su, Mooi Choo Chuah, Gang Tan — 2012
• Structural detection of android malware using embedded call graphsHugo Gascón, Fabian Yamaguchi, Daniel J. Arp — 2013
• Empirical evaluation of the tarantula automatic fault-localization techniqueJames A. Jones, Mary Jean Harrold — 2005
• Applying machine learning classifiers to dynamic Android malware detection at scaleBrandon Amos, Hamilton Turner, Jules White — 2013

Cited by

• Permission-based Malware Detection Mechanisms on Android: Analysis and PerspectivesFranklin Tchakounté — 2014
• Mystique: Evolving Android Malware for Auditing Anti-Malware ToolsGuozhu Meng, Yinxing Xue, Mahinthan Chandramohan — 2016
• Semantic modelling of Android malware for effective malware comprehension, detection, and classificationGuozhu Meng, Yinxing Xue, Zhengzi Xu — 2016
• Toward Engineering a Secure Android EcosystemMeng Xu, Chengyu Song, Ji Yang — 2016
• Prescience: Probabilistic Guidance on the Retraining Conundrum for Malware DetectionAmit Deo, Santanu Kumar Dash, Guillermo Suárez‐Tangil — 2016
• Evaluating Behavioral Biometrics for Continuous Authentication: Challenges and MetricsSimon Eberz, Kasper Rasmussen, Vincent Lenders — 2017
• A multi-view context-aware approach to Android malware detection and malicious code localizationA. Sankara Narayanan, Mahinthan Chandramohan, Lihui Chen — 2017
• Data Science for Software MaintenanceLaura Inozemtseva — 2017
• A semantic-based analysis of Android malware for detection, generation, and trend analysisGuozhu Meng — 2017
• A pragmatic android malware detection procedurePaolo Palumbo, Luiza Sayfullina, Dmitriy Komashinskiy — 2017
• Revisiting Static Analysis of Android MalwareFrançois Gagnon, Frédéric Massicotte — 2017
• Investigating Android permissions and intents for malware detectionFauzia Idrees Abro — 2018
• Permission-based Feature Selection for Android Malware Detection and AnalysisChit La, Khin Aye Mar — 2018
• Program analysis and machine learning techniques for mobile securityCharlie Zhan Yi Soh — 2019
• Android Fragmentation in Malware DetectionLong Nguyen-Vu, Jinung Ahn, Souhwan Jung — 2019
• Malicious Code Detection Based on Code Semantic FeaturesYu Zhang, Binglong Li — 2020
• Problem-Space Evasion Attacks in the Android OS: a SurveyHarel Berger, Chen Hajaj, Amit Dvir — 2022
• DNN and Cryptography based Data Monitoring System for IoMT EnvironmentSandesh Shivananda, M. Sathya, K. Janani — 2023
• Technical Report 2016-1 — Royal Holloway , University of London Misleading Metrics : On Evaluating Machine Learning for Malware with ConfidenceRoberto Jordaney, I. Nouretdinov — 2016
• DMDAM: Data Mining Based Detection of Android MalwareAbhishek Bhattacharya, R. T. Goswami — 2017

Related papers

• Dissecting Android Malware: Characterization and EvolutionYajin Zhou, Xuxian Jiang — 2012
• DREBIN: Effective and Explainable Detection of Android Malware in Your PocketDaniel J. Arp, Michael Spreitzenbarth, Malte Hübner — 2014
• A Comprehensive Survey on Machine Learning Techniques for Android Malware DetectionVasileios Kouliaridis, Georgios Kambourakis — 2021
• Hybrid-Based Malware Analysis for Effective and Efficiency Android Malware DetectionRaden Budiarto Hadiprakoso, Herman Kabetta, I Komang Setia Buana — 2020
• DeepFlow: Deep learning-based malware detection by mining Android application for abnormal usage of sensitive dataDali Zhu, Hao Jin, Ying Yang — 2017
• Toward Never-Ending Learner for Malware Analysis (NELMA)Moumita Kamal, Douglas A. Talbert — 2020