Towards an interpretable deep learning model for mobile malware detection and family identification

[1]  David Lorge Parnas,et al.  Why Engineers Should Not Use Artificial Intelligence , 1988 .

[2]  Sencun Zhu,et al.  Detecting Software Theft via System Call Based Birthmarks , 2009, 2009 Annual Computer Security Applications Conference.

[3]  B. S. Manjunath,et al.  Malware images: visualization and automatic classification , 2011, VizSec '11.

[4]  Yajin Zhou,et al.  Dissecting Android Malware: Characterization and Evolution , 2012, 2012 IEEE Symposium on Security and Privacy.

[5]  Heng Yin,et al.  DroidScope: Seamlessly Reconstructing the OS and Dalvik Semantic Views for Dynamic Android Malware Analysis , 2012, USENIX Security Symposium.

[6]  Gerardo Canfora,et al.  A Classifier of Malicious Android Applications , 2013, 2013 International Conference on Availability, Reliability and Security.

[7]  L. Cavallaro,et al.  A System Call-Centric Analysis and Stimulation Technique to Automatically Reconstruct Android Malware Behaviors , 2013 .

[8]  Konrad Rieck,et al.  DREBIN: Effective and Explainable Detection of Android Malware in Your Pocket , 2014, NDSS.

[9]  Dan Arp,et al.  Drebin : � Efficient and Explainable Detection of Android Malware in Your Pocket , 2014 .

[10]  Seong-je Cho,et al.  A kernel-based monitoring approach for analyzing malicious behavior on Android , 2014, SAC.

[11]  Muttukrishnan Rajarajan,et al.  Android Security: A Survey of Issues, Malware Penetration, and Defenses , 2015, IEEE Communications Surveys & Tutorials.

[12]  Eric Medvet,et al.  Detecting Android malware using sequences of system calls , 2015, DeMobile@SIGSOFT FSE.

[13]  Bolei Zhou,et al.  Learning Deep Features for Discriminative Localization , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[14]  Yanfang Ye,et al.  Deep4MalDroid: A Deep Learning Framework for Android Malware Detection Based on Linux Kernel System Call Graphs , 2016, 2016 IEEE/WIC/ACM International Conference on Web Intelligence Workshops (WIW).

[15]  Oluwasanmi Koyejo,et al.  Examples are not enough, learn to criticize! Criticism for Interpretability , 2016, NIPS.

[16]  Zhenlong Yuan,et al.  DroidDetector: Android Malware Characterization and Detection Using Deep Learning , 2016 .

[17]  Seth Flaxman,et al.  EU regulations on algorithmic decision-making and a "right to explanation" , 2016, ArXiv.

[18]  Paul Voigt,et al.  The EU General Data Protection Regulation (GDPR) , 2017 .

[19]  Ameet Talwalkar,et al.  Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization , 2016, J. Mach. Learn. Res..

[20]  Adam Doupé,et al.  Deep Android Malware Detection , 2017, CODASPY.

[21]  D. Parnas.  The real risks of artificial intelligence , 2017, Communications of the ACM.

[22]  M. Goddard.  The EU General Data Protection Regulation (GDPR): European Regulation that has a Global Impact , 2017 .

[23]  Abdelouahid Derhab,et al.  Android Malware Detection using Deep Learning on API Method Sequences , 2017, ArXiv.

[24]  Yanfang Ye,et al.  Deep Neural Networks for Automatic Android Malware Detection , 2017, 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

[25]  Rui Zhang,et al.  Malware identification using visualization images and deep learning , 2018, Comput. Secur..

[26]  Mohsen Guizani,et al.  Discovering Communities of Malapps on Android-based Mobile Cyber-physical Systems , 2018, Ad Hoc Networks.

[27]  Xiangliang Zhang,et al.  Detecting Android malicious apps and categorizing benign apps with ensemble of classifiers , 2018, Future Gener. Comput. Syst..

[28]  Mark Stamp,et al.  Deep Learning versus Gist Descriptors for Image-based Malware Classification , 2018, ICISSP.

[29]  Abdelouahid Derhab,et al.  MalDozer: Automatic framework for android malware detection using deep learning , 2018, Digit. Investig..

[30]  Filip Karlo Dosilovic,et al.  Explainable artificial intelligence: A survey , 2018, 2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO).

[31]  Antonella Santone,et al.  Neural Networks for Lung Cancer Detection through Radiomic Features , 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

[32]  Matti Pietikäinen,et al.  Deep Learning for Generic Object Detection: A Survey , 2018, International Journal of Computer Vision.

[33]  Antonella Santone,et al.  A “pay-how-you-drive” car insurance approach through cluster analysis , 2018, Soft Computing.

[34]  Alexander LeNail,et al.  NN-SVG: Publication-Ready Neural Network Architecture Schematics , 2019, J. Open Source Softw..

[35]  Fabio Martinelli,et al.  On the effectiveness of system API-related information for Android ransomware detection , 2018, Comput. Secur..

[36]  Abhishek Das,et al.  Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).

[37]  Tim Miller,et al.  Explanation in Artificial Intelligence: Insights from the Social Sciences , 2017, Artif. Intell..

[38]  Gerardo Canfora,et al.  LEILA: Formal Tool for Identifying Mobile Malicious Behaviour , 2019, IEEE Transactions on Software Engineering.

[39]  Franco Turini,et al.  A Survey of Methods for Explaining Black Box Models , 2018, ACM Comput. Surv..

[40]  Mohammed F. Tolba,et al.  Hyperspectral Image Classification Using Deep Learning Technique , 2020, AICV.

[41]  Georgios Kambourakis,et al.  A Survey on Mobile Malware Detection Techniques , 2020, IEICE Trans. Inf. Syst..

[42]  Sakir Sezer,et al.  DL-Droid: Deep learning based android malware detection using real devices , 2019, Comput. Secur..

[43]  Antonella Santone,et al.  Call Graph and Model Checking for Fine-Grained Android Malicious Behaviour Detection , 2020, Applied Sciences.

[44]  Lamjed Ben Said,et al.  On the use of artificial malicious patterns for android malware detection , 2020, Comput. Secur..

[45]  Antonella Santone,et al.  Image-based Malware Family Detection: An Assessment between Feature Extraction and Classification Techniques , 2020, IoTBDS.

[46]  Sencun Zhu,et al.  Privacy Risk Analysis and Mitigation of Analytics Libraries in the Android Ecosystem , 2020, IEEE Transactions on Mobile Computing.

[47]  Antonio J. Plaza,et al.  Image Segmentation Using Deep Learning: A Survey , 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.