A. Abraham, R. Andriatsimandefitra, A. Brunelat, J. F. Lalande, and V. Viet-triem-tong, GroddDroid: a Gorilla for Triggering Malicious Behaviors, 10th International Conference on Malicious and Unwanted Software, pp.119-127, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01201743

R. Andriatsimandefitra and V. Viet-triem-tong, Capturing Android Malware Behaviour Using System Flow Graph, The 8th International Conference on Network and System Security, pp.534-541, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01018611

A. Bacci, F. Martinelli, E. Medvet, and F. Mercaldo, VizMal: A visualization tool for analyzing the behavior of Android malware, 4th International Conference on Information Systems Security and Privacy, vol.1, pp.517-525, 2018.


E. Bodden, Harvesting Runtime Values in Android Applications that feature Anti-Analysis Techniques, Network and Distributed System Security Symposium, pp.21-24, 2016.

I. Burguera, U. Zurutuza, and S. Nadjm-tehrani, Crowdroid: Behavior-Based Malware Detection System for Android, 1st ACM workshop on Security and privacy in smartphones and mobile devices, p.15, 2011.

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.1-27, 2015.

Y. Fratantonio, A. Bianchi, W. Robertson, E. Kirda, C. Kruegel et al., TriggerScope: Towards Detecting Logic Bombs in Android Applications, IEEE S&P, pp.1-33, 2016.

A. R. Grégio and R. D. Santos, Visualization techniques for malware behavior analysis. Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense X 8019, pp.801905-801905, 2011.

A. R. Grégio, A. O. Baruque, V. M. Afonso, D. S. Filho, P. L. De-geus et al., Interactive, Visual-Aided Tools to Analyze Malware Behavior, 12th international conference on Computational Science and Its Applications, vol.7336, pp.302-313, 2012.

N. Kiss, J. F. Lalande, M. Leslous, and V. Viet-triem-tong, Kharon dataset: Android malware under a microscope, The Learning from Authoritative Security Experiment Results Workshop. The USENIX Association, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01311917

L. Li, D. Li, T. F. Bissyande, 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.

M. Lindorfer and M. Neugschwandtner, ANDRUBIS-1,000,000 Apps Later: A View on Current Android Malware Behaviors, 3rd International Workshop on Building Analysis Datasets and Gathering Experience Returns for Security, 2014.


A. Long, J. Saxe, and R. Gove, Detecting Malware Samples with Similar Image Sets, The Eleventh Workshop on Visualization for Cyber Security, pp.88-95, 2014.

A. Paturi, M. Cherukuri, J. Donahue, and S. Mukkamala, Mobile malware visual analytics and similarities of Attack Toolkits (Malware gene analysis), 2013 International Conference on Collaboration Technologies and Systems (CTS), pp.149-154, 2013.

D. A. Quist and L. M. Liebrock, Visualizing compiled executables for malware analysis, 6th International Workshop on Visualization for Cyber Security, pp.27-32, 2009.


G. R. Santhanam, B. Holland, S. C. Kothari, and J. Mathews, Interactive visualization toolbox to detect sophisticated android malware, IEEE Symposium on Visualization for Cyber Security, pp.1-8, 2017.

K. Tam, S. Khan, A. Fattori, and L. Cavallaro, CopperDroid: Automatic Reconstruction of Android Malware Behaviors, 22nd Annual Network and Distributed System Security Symposium, 2015.

P. Trinius, T. Holz, J. Gobel, and F. C. Freiling, Visual analysis of malware behavior using treemaps and thread graphs, 6th International Workshop on Visualization for Cyber Security, pp.33-38, 2009.

M. Wagner, F. Fischer, R. Luh, A. Haberson, A. Rind et al., A Survey of Visualization Systems for Malware Analysis, pp.105-125

I. Cagliari, , 2015.

M. Wagner, W. Aigner, A. Rind, H. Dornhackl, K. Kadletz et al., Problem Characterization and Abstraction for Visual Analytics in Behaviorbased Malware Pattern Analysis, Eleventh Workshop on Visualization for Cyber Security, pp.9-16, 2014.

L. Weichselbaum, Andrubis: Android Malware Under The Magnifying Glass, 2014.

L. K. Yan and H. Yin, DroidScope: seamlessly reconstructing the OS and Dalvik semantic views for dynamic Android malware analysis, USENIX Security Symposium. p. 29. USENIX Association, 2012.

W. Zhuo and Y. Nadjin, MalwareVis: Entity-based Visualization of Malware Network Traces, The Ninth International Symposium on Visualization for Cyber Security, pp.41-47, 2012.