Divide and Conquer: Recovering Contextual Information of Behaviors in Android Apps Around Limited-Quantity Audit Logs
暂无分享,去创建一个
[1] Alessandra Gorla,et al. Checking app behavior against app descriptions , 2014, ICSE.
[2] Tudor Dumitras,et al. FeatureSmith: Automatically Engineering Features for Malware Detection by Mining the Security Literature , 2016, CCS.
[3] Matthew L. Dering,et al. Composite Constant Propagation: Application to Android Inter-Component Communication Analysis , 2015, 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering.
[4] Tulika Mitra,et al. Automated Partitioning of Android Applications for Trusted Execution Environments , 2016, 2016 IEEE/ACM 38th International Conference on Software Engineering (ICSE).
[5] William Enck,et al. AppsPlayground: automatic security analysis of smartphone applications , 2013, CODASPY.
[6] Yajin Zhou,et al. RiskRanker: scalable and accurate zero-day android malware detection , 2012, MobiSys '12.
[7] Eric Bodden,et al. StubDroid: Automatic Inference of Precise Data-Flow Summaries for the Android Framework , 2016, 2016 IEEE/ACM 38th International Conference on Software Engineering (ICSE).
[8] Mu Zhang,et al. AppSealer: Automatic Generation of Vulnerability-Specific Patches for Preventing Component Hijacking Attacks in Android Applications , 2014, NDSS.
[9] Jacques Klein,et al. IccTA: Detecting Inter-Component Privacy Leaks in Android Apps , 2015, 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering.
[10] Michael Pradel,et al. Making Malory Behave Maliciously: Targeted Fuzzing of Android Execution Environments , 2017, 2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE).
[11] Jacques Klein,et al. DroidRA: taming reflection to support whole-program analysis of Android apps , 2016, ISSTA.
[12] Philipp von Styp-Rekowsky,et al. Mining Sandboxes , 2016, 2016 IEEE/ACM 38th International Conference on Software Engineering (ICSE).
[13] Aristide Fattori,et al. CopperDroid: Automatic Reconstruction of Android Malware Behaviors , 2015, NDSS.
[14] Ayumu Kubota,et al. Kernel-based Behavior Analysis for Android Malware Detection , 2011, 2011 Seventh International Conference on Computational Intelligence and Security.
[15] Hang Zhang,et al. Android Root and its Providers: A Double-Edged Sword , 2015, CCS.
[16] Jeff H. Perkins,et al. Information Flow Analysis of Android Applications in DroidSafe , 2015, NDSS.
[17] Peng Wang,et al. AsDroid: detecting stealthy behaviors in Android applications by user interface and program behavior contradiction , 2014, ICSE.
[18] Christopher Krügel,et al. TriggerScope: Towards Detecting Logic Bombs in Android Applications , 2016, 2016 IEEE Symposium on Security and Privacy (SP).
[19] Alessandra Gorla,et al. Mining Apps for Abnormal Usage of Sensitive Data , 2015, 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering.
[20] Heng Yin,et al. Dark Hazard: Learning-based, Large-Scale Discovery of Hidden Sensitive Operations in Android Apps , 2017, NDSS.
[21] Ondrej Lhoták,et al. The Soot framework for Java program analysis: a retrospective , 2011 .
[22] Hongfei Yan,et al. DroidForensics: Accurate Reconstruction of Android Attacks via Multi-layer Forensic Logging , 2017, AsiaCCS.
[23] Yajin Zhou,et al. Hey, You, Get Off of My Market: Detecting Malicious Apps in Official and Alternative Android Markets , 2012, NDSS.
[24] Eric Bodden,et al. Harvesting Runtime Values in Android Applications That Feature Anti-Analysis Techniques , 2016, NDSS.
[25] Sankardas Roy,et al. Amandroid: A Precise and General Inter-component Data Flow Analysis Framework for Security Vetting of Android Apps , 2014, CCS.
[26] Yuan Zhang,et al. AppIntent: analyzing sensitive data transmission in android for privacy leakage detection , 2013, CCS.
[27] Jacques Klein,et al. FlowDroid: precise context, flow, field, object-sensitive and lifecycle-aware taint analysis for Android apps , 2014, PLDI.
[28] John C. S. Lui,et al. TaintART: A Practical Multi-level Information-Flow Tracking System for Android RunTime , 2016, CCS.
[29] Wenke Lee,et al. CHEX: statically vetting Android apps for component hijacking vulnerabilities , 2012, CCS.
[30] Eric Bodden,et al. A Machine-learning Approach for Classifying and Categorizing Android Sources and Sinks , 2014, NDSS.
[31] Peng Ning,et al. EASEAndroid: Automatic Policy Analysis and Refinement for Security Enhanced Android via Large-Scale Semi-Supervised Learning , 2015, USENIX Security Symposium.
[32] Heng Yin,et al. DroidAPIMiner: Mining API-Level Features for Robust Malware Detection in Android , 2013, SecureComm.
[33] Michael Backes,et al. Boxify: Full-fledged App Sandboxing for Stock Android , 2015, USENIX Security Symposium.
[34] Nicolas Christin,et al. Evading android runtime analysis via sandbox detection , 2014, AsiaCCS.
[35] Heng Yin,et al. DroidScope: Seamlessly Reconstructing the OS and Dalvik Semantic Views for Dynamic Android Malware Analysis , 2012, USENIX Security Symposium.
[36] Byung-Gon Chun,et al. TaintDroid: An Information-Flow Tracking System for Realtime Privacy Monitoring on Smartphones , 2010, OSDI.
[37] Tao Xie,et al. AppContext: Differentiating Malicious and Benign Mobile App Behaviors Using Context , 2015, 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering.
[38] Jacques Klein,et al. Combining static analysis with probabilistic models to enable market-scale Android inter-component analysis , 2016, POPL.
[39] V. N. Venkatakrishnan,et al. SLEUTH: Real-time Attack Scenario Reconstruction from COTS Audit Data , 2018, USENIX Security Symposium.
[40] Xue Liu,et al. Effective Real-Time Android Application Auditing , 2015, 2015 IEEE Symposium on Security and Privacy.
[41] Yongbo Li,et al. SARRE: Semantics-Aware Rule Recommendation and Enforcement for Event Paths on Android , 2016, IEEE Transactions on Information Forensics and Security.
[42] Jacques Klein,et al. Effective Inter-Component Communication Mapping in Android: An Essential Step Towards Holistic Security Analysis , 2013, USENIX Security Symposium.
[43] Jacques Klein,et al. Effective inter-component communication mapping in Android with Epicc: an essential step towards holistic security analysis , 2013 .
[44] Dawn Xiaodong Song,et al. Contextual Policy Enforcement in Android Applications with Permission Event Graphs , 2013, NDSS.
[45] Yajin Zhou,et al. Dissecting Android Malware: Characterization and Evolution , 2012, 2012 IEEE Symposium on Security and Privacy.
[46] Yuan Zhang,et al. Vetting undesirable behaviors in android apps with permission use analysis , 2013, CCS.