Smartphone Traffic Analysis: A Contemporary Survey of the State-of-the-Art
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[1] Mauro Conti,et al. The Dark Side(-Channel) of Mobile Devices: A Survey on Network Traffic Analysis , 2017, IEEE Communications Surveys & Tutorials.
[2] Yajin Zhou,et al. Dissecting Android Malware: Characterization and Evolution , 2012, 2012 IEEE Symposium on Security and Privacy.
[3] Scott E. Coull,et al. Traffic Analysis of Encrypted Messaging Services: Apple iMessage and Beyond , 2014, CCRV.
[4] Marco Fiore,et al. Large-Scale Mobile Traffic Analysis: A Survey , 2016, IEEE Communications Surveys & Tutorials.
[5] Mauro Conti,et al. Deep and Broad Learning Based Detection of Android Malware via Network Traffic , 2018, 2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS).
[6] Songjie Wei,et al. Mining network traffic for application category recognition on Android platform , 2015, 2015 IEEE International Conference on Progress in Informatics and Computing (PIC).
[7] Giuseppe Aceto,et al. Mobile Encrypted Traffic Classification Using Deep Learning: Experimental Evaluation, Lessons Learned, and Challenges , 2019, IEEE Transactions on Network and Service Management.
[8] Mauro Conti,et al. Robust Smartphone App Identification via Encrypted Network Traffic Analysis , 2017, IEEE Transactions on Information Forensics and Security.
[9] William H. Robinson,et al. Network-based detection of mobile malware exhibiting obfuscated or silent network behavior , 2018, 2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC).
[10] Mauro Conti,et al. Detecting Android Malware Leveraging Text Semantics of Network Flows , 2017, IEEE Transactions on Information Forensics and Security.
[11] Hamid Reza Shahriari,et al. PodBot: A New Botnet Detection Method by Host and Network-Based Analysis , 2019, 2019 27th Iranian Conference on Electrical Engineering (ICEE).
[12] R. M. Sharma,et al. Android malicious application detection using permission vector and network traffic analysis , 2017, 2017 2nd International Conference for Convergence in Technology (I2CT).
[13] Lidong Zhai,et al. Research of android malware detection based on network traffic monitoring , 2014, 2014 9th IEEE Conference on Industrial Electronics and Applications.
[14] Bin Li,et al. Identification of VoIP Speech With Multiple Domain Deep Features , 2020, IEEE Transactions on Information Forensics and Security.
[15] Ashutosh Sabharwal,et al. Interactive app traffic: An action-based model and data-driven analysis , 2016, 2016 14th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt).
[16] Kensuke Fukuda,et al. Combining Communication Patterns & Traffic Patterns to Enhance Mobile Traffic Identification Performance , 2016, Journal of Information Processing.
[17] Claudia Díaz,et al. Leaky Birds: Exploiting Mobile Application Traffic for Surveillance , 2016, Financial Cryptography.
[18] Riccardo Bettati,et al. Smartphone reconnaissance: Operating system identification , 2016, 2016 13th IEEE Annual Consumer Communications & Networking Conference (CCNC).
[19] Stefan Mangard,et al. Exploiting Data-Usage Statistics for Website Fingerprinting Attacks on Android , 2016, WISEC.
[20] Lei Zhang,et al. A First Look at Android Malware Traffic in First Few Minutes , 2015, TrustCom 2015.
[21] Joerg Abendroth,et al. Mobile Guard Demo: Network Based Malware Detection , 2015, TrustCom 2015.
[22] Urs Hengartner,et al. PrivacyGuard: A VPN-based Platform to Detect Information Leakage on Android Devices , 2015, SPSM@CCS.
[23] Xiaomei Li,et al. Finding Android Malware Trace from Highly Imbalanced Network Traffic , 2017, 22017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC).
[24] Liang Liu,et al. Fuzzing the Android Applications With HTTP/HTTPS Network Data , 2019, IEEE Access.
[25] Anshul Arora,et al. NTPDroid: A Hybrid Android Malware Detector Using Network Traffic and System Permissions , 2018, 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE).
[26] Lior Rokach,et al. Mobile malware detection through analysis of deviations in application network behavior , 2014, Comput. Secur..
[27] Kensuke Fukuda,et al. Tracking the Evolution and Diversity in Network Usage of Smartphones , 2015, Internet Measurement Conference.
[28] M. Chuah,et al. Smartphone Dual Defense Protection Framework: Detecting Malicious Applications in Android Markets , 2012, 2012 8th International Conference on Mobile Ad-hoc and Sensor Networks (MSN).
[29] Ali Feizollah,et al. Evaluation of machine learning classifiers for mobile malware detection , 2014, Soft Computing.
[30] Yongzheng Zhang,et al. Detecting Information Theft Based on Mobile Network Flows for Android Users , 2017, 2017 International Conference on Networking, Architecture, and Storage (NAS).
[31] Ali Feizollah,et al. Comparative study of k-means and mini batch k-means clustering algorithms in android malware detection using network traffic analysis , 2014, 2014 International Symposium on Biometrics and Security Technologies (ISBAST).
[32] Yanick Fratantonio,et al. ANDRUBIS -- 1,000,000 Apps Later: A View on Current Android Malware Behaviors , 2014, 2014 Third International Workshop on Building Analysis Datasets and Gathering Experience Returns for Security (BADGERS).
[33] María-del-Mar Gallardo,et al. Performance Analysis of Spotify® for Android with Model-Based Testing , 2017, Mob. Inf. Syst..
[34] Pengfei Jiang,et al. Mobile Application Network Behavior Detection and Evaluation with WGAN and Bi-LSTM , 2018, TENCON 2018 - 2018 IEEE Region 10 Conference.
[35] Bo Yang,et al. TrafficAV: An effective and explainable detection of mobile malware behavior using network traffic , 2016, 2016 IEEE/ACM 24th International Symposium on Quality of Service (IWQoS).
[36] Anshul Arora,et al. Minimizing Network Traffic Features for Android Mobile Malware Detection , 2017, ICDCN.
[37] nbspKhushboo Hande,et al. A comparative study of static, dynamic and hybrid analysis techniques for android malware detection , 2017 .
[38] Ali A. Ghorbani,et al. Towards a Network-Based Framework for Android Malware Detection and Characterization , 2017, 2017 15th Annual Conference on Privacy, Security and Trust (PST).
[39] Md. Shohrab Hossain,et al. Malware detection in Android by network traffic analysis , 2015, 2015 International Conference on Networking Systems and Security (NSysS).
[40] Konrad Rieck,et al. DREBIN: Effective and Explainable Detection of Android Malware in Your Pocket , 2014, NDSS.
[41] Kunwadee Sripanidkulchai,et al. An analysis of mobile application network behavior , 2016, AINTEC.
[42] Anshul Arora,et al. Malware Detection Using Network Traffic Analysis in Android Based Mobile Devices , 2014, 2014 Eighth International Conference on Next Generation Mobile Apps, Services and Technologies.
[43] Nguyen Tan Cam,et al. NeSeDroid—Android Malware Detection Based on Network Traffic and Sensitive Resource Accessing , 2017 .
[44] William H. Robinson,et al. Using network traffic to verify mobile device forensic artifacts , 2017, CCNC.
[45] Isredza Rahmi A. Hamid,et al. Android Malware Detection Based on Network Traffic Using Decision Tree Algorithm , 2018, SCDM.