. $i0,

, android.telephony.SmsManager $

. Java and . Lang, String $r2

, $i0 = virtualinvoke $r0.<com.example.dexman.eg2.MainActivity: int f(

, $i0 = neg $i0

, >(); i2 <= 10 goto label2, $i1 = virtualinvoke $r0.<com.example.dexman.eg2.MainActivity: int f(

, >(); <android.telephony.SmsManager: android.telephony, $i3 = virtualinvoke $r0.<com.example.dexman.eg2.MainActivity: int g(

, 24 $r2 = staticinvoke <java.lang.String: java.lang.String valueOf(int)>($i1)

, SmsManager: void sendTextMessage(java.lang.String, java.lang.String,java.lang.String, android.app.PendingIntent, android.app.PendingIntent)>("1234, virtualinvoke $r1.<android.telephony, vol.2

, for our approach to be able to deal with the huge number of malware samples that are uploaded to Internet every day

M. Leslous, V. Viet-triem, J. Tong, T. Lalande, and . Genet, GPFinder: Tracking the Invisible in Android Malware, 12th International Conference on Malicious and Unwanted Software, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01584989

M. Leslous, J. Lalande, and V. Tong, Poster: Using Implicit Calls to Improve Malware Dynamic Execution, 37th IEEE Symposium on Security and Privacy, 2016.

V. Viet, T. Tong, and A. Trulla, Mourad Leslous, Jean-François Lalande. Information flows at OS level unmask sophisticated Android malware, 14th International Conference on Security and Cryptography, vol.6, pp.578-585, 2017.

N. Kiss, J. Lalande, M. Leslous, and V. Tong, Kharon Dataset: Android Malware under a Microscope. USENIX Association. The LASER Workshop: Learning from Authoritative Security Experiment Results, p.1, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01311917

V. Viet, T. Tong, and J. Lalande, Mourad Leslous. Challenges in Android Malware Analysis. ERCIM News, ERCIM, pp.42-43, 2016.

J. Lalande, V. Viêt-triem, M. Tong, P. Leslous, and . Graux, Challenges for Reliable and Large Scale Evaluation of Android Malware Analysis, SHPCS 2018 -International Workshop on Security and High Performance Computing Systems, pp.1-3, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01844312

, Smartphone os market share, IDC, pp.2016-2026, 2016.

. Statista, Number of available applications in the google play store from december, 2009.

A. Google and . Security, Android _ Security _ 2017 _ Re -port _ Final.pdf, 2017.

P. Faruki, A. Bharmal, V. Laxmi, V. Ganmoor, M. S. Gaur et al., Android security: A survey of issues, malware penetration, and defenses, IEEE Communications Surveys Tutorials, vol.17, issue.2, pp.998-1022, 2015.

L. Li, D. Li, T. F. Bissyandé, J. Klein, Y. Le-traon et al., Understanding android app piggybacking: A systematic study of malicious code grafting, IEEE Transactions on Information Forensics and Security, vol.12, issue.6, pp.1269-1284, 2017.

S. Arzt, S. Rasthofer, C. Fritz, E. Bodden, A. Bartel et al., FlowDroid: Precise context, flow, field, objectsensitive and lifecycle-aware taint analysis for android apps, 35th ACM SIGPLAN Conference on Programming Language Design and Implementation, ser. PLDI '14, pp.259-269, 2014.

S. Poeplau, Y. Fratantonio, A. Bianchi, C. Kruegel, and G. Vigna, Execute this! analyzing unsafe and malicious dynamic code loading in android applications, Network and Distributed System Security (NDSS) Symposium, vol.14, pp.23-26, 2014.

A. Apvrille and R. Nigam, Obfuscation in android malware, and how to fight back, 2014.

V. Rastogi, Y. Chen, and X. Jiang, Droidchameleon: Evaluating android antimalware against transformation attacks, Proceedings of the 8th ACM SIGSAC symposium on Information, pp.329-334, 2013.

K. Tam, S. J. Khan, A. Fattori, and L. Cavallaro, Copperdroid: Automatic reconstruction of android malware behaviors, NDSS, 2015.

Y. Fratantonio, A. Bianchi, W. Robertson, E. Kirda, C. Kruegel et al., Triggerscope: Towards detecting logic bombs in android applications, Security and Privacy (SP), pp.377-396, 2016.

M. Y. Wong and D. Lie, Intellidroid: A targeted input generator for the dynamic analysis of android malware, NDSS, vol.16, pp.21-24, 2016.

I. Burguera, U. Zurutuza, and S. Nadjm-tehrani, Crowdroid: Behavior-based malware detection system for android, Proceedings of the 1st ACM workshop on Security and privacy in smartphones and mobile devices, pp.15-26, 2011.

H. Gunadi and A. Tiu, Efficient runtime monitoring with metric temporal logic: A case study in the android operating system, International Symposium on Formal Methods, pp.296-311, 2014.

F. E. Allen, Control flow analysis, Proceedings of a Symposium on Compiler Optimization, pp.1-19, 1970.

X. Pan, X. Wang, Y. Duan, H. Wang, and . Yin, Dark hazard: Learningbased, large-scale discovery of hidden sensitive operations in android apps, Proceedings of the ISOC Network and Distributed System Security Symposium (NDSS, 2017.

S. Hao, B. Liu, S. Nath, W. G. Halfond, and R. Govindan, Puma: Programmable ui-automation for large-scale dynamic analysis of mobile apps, Proceedings of the 12th annual international conference on Mobile systems, applications, and services, pp.204-217, 2014.

S. Rasthofer, S. Arzt, S. Triller, and M. Pradel, Making malory behave maliciously: Targeted fuzzing of android execution environments, Proceedings of the 39th International Conference on Software Engineering, ser. ICSE '17, pp.300-311, 2017.

A. Abraham, R. Andriatsimandefitra, A. Brunelat, J. Lalande, V. Viet-triem et al., Grodddroid: A gorilla for triggering malicious behaviors, 10th International Conference on Malicious and Unwanted Software, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01201743

S. Rasthofer, S. Arzt, M. Miltenberger, and E. Bodden, Harvesting runtime data in android applications for identifying malware and enhancing code analysis, EC SPRIDE, Tech. Rep, 2015.

F. Wei, Y. Li, S. Roy, X. Ou, and W. Zhou, Deep ground truth analysis of current android malware, International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment, pp.252-276, 2017.

M. Leslous, V. Viet-triem, J. Tong, T. Lalande, and . Genet, GPFinder: Tracking the Invisible in Android Malware, 12th International Conference on Malicious and Unwanted Software, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01584989

N. Kiss, J. Lalande, M. Leslous, and V. V. Tong, Kharon dataset: Android malware under a microscope, The LASER Workshop: Learning from Authoritative Security Experiment Results (LASER 2016), pp.1-12, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01311917

Z. Aung and W. Zaw, Permission-based android malware detection, International Journal of Scientific and Technology Research, vol.2, issue.3, pp.228-234, 2013.

H. Peng, C. Gates, B. Sarma, N. Li, Y. Qi et al., Using probabilistic generative models for ranking risks of android apps, Proceedings of the 2012 ACM conference on Computer and communications security, pp.241-252, 2012.

V. Moonsamy, J. Rong, and S. Liu, Mining permission patterns for contrasting clean and malicious android applications, Future Generation Computer Systems, vol.36, pp.122-132, 2014.

C. Huang, Y. Tsai, and C. Hsu, Performance evaluation on permissionbased detection for android malware, Advances in Intelligent Systems and Applications, vol.2, pp.111-120, 2013.

J. Schütte, R. Fedler, and D. Titze, Condroid: Targeted dynamic analysis of android applications, 2015 IEEE 29th International Conference on Advanced Information Networking and Applications, pp.571-578, 2015.

C. Zheng, S. Zhu, S. Dai, G. Gu, X. Gong et al., Smartdroid: An automatic system for revealing ui-based trigger conditions in android applications, 2nd ACM workshop on Security and privacy in smartphones and mobile devices, pp.93-104, 2012.

S. Smalley and R. Craig, Security enhanced (se) android: Bringing flexible mac to android, NDSS, vol.310, pp.20-38, 2013.

P. A. Loscocco, S. D. Smalley, P. A. Muckelbauer, R. C. Taylor, S. J. Turner et al., The inevitability of failure: The flawed assumption of security in modern computing environments, Proceedings of the 21st National Information Systems Security Conference, vol.10, pp.303-314, 1998.

F. E. Allen, Control flow analysis, Proceedings of a Symposium on Compiler Optimization, pp.1-19, 1970.

E. J. Chikofsky and J. H. Cross, Reverse engineering and design recovery: A taxonomy, IEEE software, vol.7, issue.1, pp.13-17, 1990.
DOI : 10.1109/52.43044

R. Vallee-rai and L. J. Hendren, Jimple: Simplifying java bytecode for analyses and transformations, 1998.

R. Vallée-rai, P. Co, E. Gagnon, L. Hendren, P. Lam et al., Soota java bytecode optimization framework, 1999 Conference of the Centre for Advanced Studies on Collaborative Research, p.13, 1999.

L. Li, T. F. Bissyandé, M. Papadakis, S. Rasthofer, A. Bartel et al., Static analysis of android apps: A systematic literature review, Information and Software Technology, vol.88, pp.67-95, 2017.

J. Dean, D. Grove, and C. Chambers, Optimization of object-oriented programs using static class hierarchy analysis, European Conference on ObjectOriented Programming, pp.77-101, 1995.
DOI : 10.1007/3-540-49538-x_5

URL : http://www.cs.ucla.edu/~palsberg/tba/papers/dean-grove-chambers-ecoop95.pdf

D. F. Bacon and P. F. Sweeney, Fast static analysis of c++ virtual function calls, ACM Sigplan Notices, vol.31, issue.10, pp.324-341, 1996.

V. Sundaresan, L. Hendren, C. Razafimahefa, R. Vallée-rai, P. Lam et al., Practical virtual method call resolution for Java, vol.10, 2000.
DOI : 10.1145/353171.353189

URL : http://www.archipel.uqam.ca/8367/1/Gagnon-2000a-preprint.pdf

O. Lhoták and L. Hendren, Scaling java points-to analysis using spark, pp.978-981, 2003.

L. O. Andersen, Program analysis and specialization for the c programming language, 1994.

B. Steensgaard, Points-to analysis in almost linear time, Proceedings of the 23rd ACM SIGPLAN-SIGACT symposium on Principles of programming languages, pp.32-41, 1996.
DOI : 10.1145/237721.237727

URL : http://www.cs.trinity.edu/~mlewis/CSCI3294-F01/Papers/Steensgaard96.pdf

X. Zhou, S. Demetriou, D. He, M. Naveed, X. Pan et al., Identity, location, disease and more: Inferring your secrets from android public resources, Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security, pp.1017-1028, 2013.
DOI : 10.1145/2508859.2516661

G. Meng, Y. Xue, C. Mahinthan, A. Narayanan, Y. Liu et al., Mystique: Evolving android malware for auditing anti-malware tools, Proceedings of the 11th ACM on Asia conference on computer and communications security, pp.365-376, 2016.

Y. Zhang, Y. Li, T. Tan, and J. Xue, Ripple: Reflection analysis for android apps in incomplete information environments, Software: Practice and Experience, vol.48, issue.8, pp.1419-1437, 2018.

L. Li, T. F. Bissyandé, D. Octeau, and J. Klein, Droidra: Taming reflection to support whole-program analysis of android apps, Proceedings of the 25th International Symposium on Software Testing and Analysis, pp.318-329, 2016.

G. Suarez-tangil, J. E. Tapiador, F. Lombardi, and R. Pietro, Alterdroid: Differential fault analysis of obfuscated smartphone malware, IEEE Transactions on Mobile Computing, vol.15, issue.4, pp.789-802, 2016.

Y. Chen, Y. Zhang, Z. Wang, L. Xia, C. Bao et al., Adaptive android kernel live patching, Proceedings of the 26th USENIX Security Symposium (USENIX Security 17, 2017.

C. Ren, P. Liu, and S. Zhu, Windowguard: Systematic protection of gui security in android, Proc. of the Annual Symposium on Network and Distributed System Security (NDSS, 2017.

G. Costa, P. Gasti, A. Merlo, and S. Yu, Flex: A flexible code authentication framework for delegating mobile app customization, Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security, pp.389-400, 2016.

J. Seo, D. Kim, D. Cho, I. Shin, and T. Kim, Flexdroid: Enforcing in-app privilege separation in android, NDSS, 2016.

M. Backes, S. Bugiel, C. Hammer, O. Schranz, and P. V. Styp-rekowsky, Boxify: Full-fledged app sandboxing for stock android, 2015.

X. Wang, K. Sun, Y. Wang, and J. Jing, Deepdroid: Dynamically enforcing enterprise policy on android devices, NDSS, 2015.

G. S. Tuncay, S. Demetriou, K. Ganju, and C. A. Gunter, Resolving the predicament of android custom permissions, ISOC Network and Distributed Systems Security Symposium (NDSS), 2018.

S. Rasthofer, S. Arzt, E. Lovat, and E. Bodden, Droidforce: Enforcing complex, data-centric, system-wide policies in android, Availability, Reliability and Security, pp.40-49, 2014.

C. Yagemann and W. Du, Intentio ex machina: Android intent access control via an extensible application hook, European Symposium on Research in Computer Security, pp.383-400, 2016.

D. Arp, M. Spreitzenbarth, M. Hubner, H. Gascon, K. Rieck et al., Drebin: Effective and explainable detection of android malware in your pocket, Ndss, vol.14, pp.23-26, 2014.

H. Fu, Z. Zheng, S. Bose, M. Bishop, and P. Mohapatra, Leaksemantic: Identifying abnormal sensitive network transmissions in mobile applications, IN-FOCOM 2017-IEEE Conference on Computer Communications, pp.1-9, 2017.

A. Continella, Y. Fratantonio, M. Lindorfer, A. Puccetti, A. Zand et al., Obfuscation-resilient privacy leak detection for mobile apps through differential analysis, Proceedings of the ISOC Network and Distributed System Security Symposium (NDSS, pp.1-16, 2017.

K. Xu, Y. Li, and R. H. Deng, Iccdetector: Icc-based malware detection on android, IEEE Transactions on Information Forensics and Security, vol.11, issue.6, pp.1252-1264, 2016.

R. Slavin, X. Wang, M. B. Hosseini, J. Hester, R. Krishnan et al., Toward a framework for detecting privacy policy violations in android application code, Proceedings of the 38th International Conference on Software Engineering, pp.25-36, 2016.

X. Chen and S. Zhu, Droidjust: Automated functionality-aware privacy leakage analysis for android applications, Proceedings of the 8th ACM Conference on Security & Privacy in Wireless and Mobile Networks, p.5, 2015.

L. Li, A. Bartel, T. F. Bissyandé, J. Klein, Y. Le-traon et al., Iccta: Detecting inter-component privacy leaks in android apps, Proceedings of the 37th International Conference on Software Engineering, vol.1, pp.280-291, 2015.

V. Avdiienko, K. Kuznetsov, A. Gorla, A. Zeller, S. Arzt et al., Mining apps for abnormal usage of sensitive data, Proceedings of the 37th International Conference on Software Engineering, vol.1, pp.426-436, 2015.

S. Arzt, S. Rasthofer, and E. Bodden, Susi: A tool for the fully automated classification and categorization of android sources and sinks, 2013.

A. Martín, A. Calleja, H. D. Menéndez, J. Tapiador, and D. Camacho, Adroit: Android malware detection using meta-information, Computational Intelligence (SSCI), pp.1-8, 2016.

M. Grace, Y. Zhou, Q. Zhang, S. Zou, and X. Jiang, Riskranker: Scalable and accurate zero-day android malware detection, Proceedings of the 10th international conference on Mobile systems, applications, and services, pp.281-294, 2012.

G. Suarez-tangil, J. E. Tapiador, P. Peris-lopez, and J. Blasco, Dendroid: A text mining approach to analyzing and classifying code structures in android malware families, Expert Systems with Applications, vol.41, issue.4, pp.1104-1117, 2014.

G. Suarez-tangil, S. K. Dash, M. Ahmadi, J. Kinder, G. Giacinto et al., Droidsieve: Fast and accurate classification of obfuscated android malware, Proceedings of the Seventh ACM on Conference on Data and Application Security and Privacy, pp.309-320, 2017.

S. Mutti, Y. Fratantonio, A. Bianchi, L. Invernizzi, J. Corbetta et al., Baredroid: Large-scale analysis of android apps on real devices, Proceedings of the 31st Annual Computer Security Applications Conference, pp.71-80, 2015.

F. Maggi, A. Valdi, and S. Zanero, Andrototal: A flexible, scalable toolbox and service for testing mobile malware detectors, Proceedings of the Third ACM workshop on Security and privacy in smartphones & mobile devices, pp.49-54, 2013.

C. Zheng, S. Zhu, S. Dai, G. Gu, X. Gong et al., Smartdroid: An automatic system for revealing ui-based trigger conditions in android applications, Proceedings of the second ACM workshop on Security and privacy in smartphones and mobile devices, pp.93-104, 2012.

S. K. Dash, G. Suarez-tangil, S. Khan, K. Tam, M. Ahmadi et al., Droidscribe: Classifying android malware based on runtime behavior, Security and Privacy Workshops (SPW), pp.252-261, 2016.
DOI : 10.1109/spw.2016.25

R. Spreitzer, F. Kirchengast, D. Gruss, and S. Mangard, Procharvester: Fully automated analysis of procfs side-channel leaks on android, Proceedings of the 2018 on Asia Conference on Computer and Communications Security, pp.749-763, 2018.

L. Li, D. Li, T. F. Bissyandé, J. Klein, H. Cai et al., Automatically locating malicious packages in piggybacked android apps, Proceedings of the 4th International Conference on Mobile Software Engineering and Systems, pp.170-174, 2017.

L. Yan and H. Yin, Droidscope: Seamlessly reconstructing the os and dalvik semantic views for dynamic android malware analysis, USENIX security symposium, pp.569-584, 2012.

F. Bellard, Qemu, a fast and portable dynamic translator, USENIX Annual Technical Conference, FREENIX Track, vol.41, p.46, 2005.

L. Xue, Y. Zhou, T. Chen, X. Luo, and G. Gu, Malton: Towards on-device noninvasive mobile malware analysis for art, 26th USENIX Security Symposium (USENIX Security 17, 2017.

Y. Aafer, W. Du, and H. Yin, DroidAPIMiner: Mining api-level features for robust malware detection in android, Security and Privacy in Communication Networks, ser. LNICST, vol.127, pp.86-103, 2013.

X. Hu, T. Chiueh, and K. G. Shin, Large-scale malware indexing using function-call graphs, Proceedings of the 16th ACM conference on Computer and communications security, pp.611-620, 2009.
DOI : 10.1145/1653662.1653736

C. Kolbitsch, P. M. Comparetti, C. Kruegel, E. Kirda, X. Zhou et al., Effective and efficient malware detection at the end host, USENIX security symposium, vol.4, pp.351-366, 2009.

H. Gascon, F. Yamaguchi, D. Arp, and K. Rieck, Structural detection of android malware using embedded call graphs, Proceedings of the 2013 ACM workshop on Artificial intelligence and security, pp.45-54, 2013.

M. Lillack, C. Kästner, and E. Bodden, Tracking load-time configuration options, 29th ACM/IEEE International Conference on Automated Software Engineering, ser. ASE '14, pp.445-456, 2014.
DOI : 10.1109/tse.2017.2756048

W. Klieber, L. Flynn, A. Bhosale, L. Jia, and L. Bauer, Android taint flow analysis for app sets, 3rd ACM SIGPLAN International Workshop on the State of the Art in Java Program Analysis, ser. SOAP '14, pp.1-6, 2014.
DOI : 10.1145/2614628.2614633

URL : http://www.cs.cmu.edu/~wklieber/papers/soap2014-android.pdf

D. Octeau, P. Mcdaniel, S. Jha, A. Bartel, E. Bodden et al., Effective inter-component communication mapping in android with epicc: An essential step towards holistic security analysis, 22Nd USENIX Conference on Security, ser. SEC'13, pp.978-979, 2013.

M. Graa, N. Cuppens-boulahia, F. Cuppens, and A. Cavalli, Detecting control flow in smarphones: Combining static and dynamic analyses, 4th International Symposium on Cyberspace Safety and Security, pp.33-47, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00785180

T. Wu, J. Liu, Z. Xu, C. Guo, Y. Zhang et al., Light-weight, inter-procedural and callback-aware resource leak detection for android apps, IEEE Transactions on Software Engineering, vol.42, issue.11, pp.1054-1076, 2016.

M. Junaid, D. Liu, and D. Kung, Dexteroid: Detecting malicious behaviors in android apps using reverse-engineered life cycle models, Computers and Security, vol.59, pp.167-4048, 2016.

S. Yang, D. Yan, H. Wu, Y. Wang, and A. Rountev, Static control-flow analysis of user-driven callbacks in android applications, Proceedings of the 37th International Conference on Software Engineering, vol.1, pp.89-99, 2015.

A. Salem, Stimulation and detection of android repackaged malware with active learning, 2018.

Y. Cao, Y. Fratantonio, A. Bianchi, M. Egele, C. Kruegel et al., EdgeMiner: Automatically detecting implicit control flow transitions through the android framework, The 2015 Network and Distributed System Security, 2015.
DOI : 10.14722/ndss.2015.23140

L. Li, D. Li, T. F. Bissyandé, J. Klein, Y. Le-traon et al., Understanding android app piggybacking: A systematic study of malicious code grafting, IEEE Transactions on Information Forensics and Security, vol.12, issue.6, pp.1269-1284, 2017.

K. Allix, T. F. Bissyandé, J. Klein, and Y. Le-traon, Androzoo: Collecting millions of android apps for the research community, 13th International Conference on Mining Software Repositories, pp.468-471, 2016.

R. Vallee-rai and L. Hendren, Jimple: Simplifying java bytecode for analyses and transformations, 2004.

L. De-moura and N. Bjørner, Z3: An efficient smt solver, Tools and Algorithms for the Construction and Analysis of Systems, pp.337-340, 2008.

A. Mohaisen and O. Alrawi, Av-meter: An evaluation of antivirus scans and labels, International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment, pp.112-131, 2014.

F. Maggi, A. Bellini, G. Salvaneschi, and S. Zanero, Finding non-trivial malware naming inconsistencies, International Conference on Information Systems Security, pp.144-159, 2011.
DOI : 10.1007/978-3-642-25560-1_10

M. Hurier, G. Suarez-tangil, S. K. Dash, T. F. Bissyandé, Y. L. Traon et al., Euphony: Harmonious unification of cacophonous anti-virus vendor labels for android malware, Proceedings of the 14th International Conference on Mining Software Repositories, pp.425-435, 2017.

X. Jiang and Y. Zhou, Dissecting android malware: Characterization and evolution, 2012 IEEE Symposium on Security and Privacy, pp.95-109, 2012.

A. Salem and A. Pretschner, Poking the bear: Lessons learned from probing three android malware datasets, Proceedings of the 1st International Workshop on Advances in Mobile App Analysis, pp.19-24, 2018.

L. Georget, M. Jaume, F. Tronel, G. Piolle, and V. V. Tong, Verifying the reliability of operating system-level information flow control systems in linux, IEEE/ACM 5th International FME Workshop on, pp.10-16, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01535862