CatraDroid: A Call Trace Driven Detection of Malicious Behaiviors in Android Applications
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[1] Byung-Gon Chun,et al. TaintDroid: An Information-Flow Tracking System for Realtime Privacy Monitoring on Smartphones , 2010, OSDI.
[2] Yang Liu,et al. Semantic modelling of Android malware for effective malware comprehension, detection, and classification , 2016, ISSTA.
[3] Somesh Jha,et al. Retargeting Android applications to Java bytecode , 2012, SIGSOFT FSE.
[4] Mansour Ahmadi,et al. DroidScribe: Classifying Android Malware Based on Runtime Behavior , 2016, 2016 IEEE Security and Privacy Workshops (SPW).
[5] Haipeng Cai,et al. DroidCat: Effective Android Malware Detection and Categorization via App-Level Profiling , 2019, IEEE Transactions on Information Forensics and Security.
[6] Xin Sun,et al. Detection, Classification and Characterization of Android Malware Using API Data Dependency , 2015, SecureComm.
[7] Alessandra Gorla,et al. Mining Apps for Abnormal Usage of Sensitive Data , 2015, 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering.
[8] Zibin Zheng,et al. MalPat: Mining Patterns of Malicious and Benign Android Apps via Permission-Related APIs , 2018, IEEE Transactions on Reliability.
[9] Mohammad Emtiyaz Khan,et al. SmarPer: Context-Aware and Automatic Runtime-Permissions for Mobile Devices , 2017, 2017 IEEE Symposium on Security and Privacy (SP).
[10] Chao Yang,et al. DroidMiner: Automated Mining and Characterization of Fine-grained Malicious Behaviors in Android Applications , 2014, ESORICS.
[11] Yanfang Ye,et al. HinDroid: An Intelligent Android Malware Detection System Based on Structured Heterogeneous Information Network , 2017, KDD.
[12] Gaël Varoquaux,et al. Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..
[13] Simone Atzeni,et al. Evaluation of Android Malware Detection Based on System Calls , 2016, IWSPA@CODASPY.
[14] Eric Bodden,et al. A Machine-learning Approach for Classifying and Categorizing Android Sources and Sinks , 2014, NDSS.
[15] Jianfeng Ma,et al. A Novel Dynamic Android Malware Detection System With Ensemble Learning , 2018, IEEE Access.
[16] Andy Liaw,et al. Classification and Regression by randomForest , 2007 .
[17] Jacques Klein,et al. AndroZoo: Collecting Millions of Android Apps for the Research Community , 2016, 2016 IEEE/ACM 13th Working Conference on Mining Software Repositories (MSR).
[18] Simin Nadjm-Tehrani,et al. Crowdroid: behavior-based malware detection system for Android , 2011, SPSM '11.
[19] Christopher Krügel,et al. EdgeMiner: Automatically Detecting Implicit Control Flow Transitions through the Android Framework , 2015, NDSS.
[20] Jacques Klein,et al. FlowDroid: precise context, flow, field, object-sensitive and lifecycle-aware taint analysis for Android apps , 2014, PLDI.
[21] David W. Aha,et al. Instance-Based Learning Algorithms , 1991, Machine Learning.
[22] David Lie,et al. IntelliDroid: A Targeted Input Generator for the Dynamic Analysis of Android Malware , 2016, NDSS.
[23] Heng Yin,et al. DroidAPIMiner: Mining API-Level Features for Robust Malware Detection in Android , 2013, SecureComm.
[24] Zhong Chen,et al. AutoCog: Measuring the Description-to-permission Fidelity in Android Applications , 2014, CCS.
[25] Pat Langley,et al. Estimating Continuous Distributions in Bayesian Classifiers , 1995, UAI.
[26] Gianluca Dini,et al. MADAM: Effective and Efficient Behavior-based Android Malware Detection and Prevention , 2018, IEEE Transactions on Dependable and Secure Computing.
[27] Mu Zhang,et al. Semantics-Aware Android Malware Classification Using Weighted Contextual API Dependency Graphs , 2014, CCS.
[28] Wei Chen,et al. More Semantics More Robust: Improving Android Malware Classifiers , 2016, WISEC.
[29] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[30] Sankardas Roy,et al. Amandroid: A Precise and General Inter-component Data Flow Analysis Framework for Security Vetting of Android Apps , 2014, CCS.
[31] Konrad Rieck,et al. DREBIN: Effective and Explainable Detection of Android Malware in Your Pocket , 2014, NDSS.