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The Dark Side(-Channel) of Mobile Devices: A Survey on Network Traffic Analysis
[article]
2018
arXiv
pre-print
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For this reason, the research community has been investigating security and privacy issues that are related to the network traffic generated by mobile devices, which could be analyzed to obtain information ...
useful for a variety of goals (ranging from device security and network optimization, to fine-grained user profiling). ...
., DNS, HTTP, IRC), which is not feasible if the analyzed app encrypts its network traffic. ...
arXiv:1708.03766v3
fatcat:ss6hqa7zsjcavkkwexftpowtku
Can't you hear me knocking: Identification of user actions on Android apps via traffic analysis
[article]
2014
arXiv
pre-print
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In this paper, we move a step forward: we investigate to which extent it is feasible to identify the specific actions that a user is doing on his mobile device, by simply eavesdropping the device's network ...
Work in this latter direction aimed, for example, at inferring the apps a user has installed on his device, or identifying the presence of a specific user within a network. ...
CONCLUSIONS We proposed a framework to analyze encrypted network traffic and to infer which particular actions the user executed on some apps installed on his mobile-phone. ...
arXiv:1407.7844v1
fatcat:suguskjxezabfk6nnq45obhzo4
POSTER
2015
Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security - CCS '15
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Smartphone users are facing serious threat of privacy leakage. This privacy leakage is caused not only by malicious applications (apps), but also by the most popular apps in one's pocket. ...
Our goal is to find what information is exposed by each popular app, and then to focus on the following three questions in order to explore the influence of this kind of information leakage: (1) to what ...
We analyze the network traffic data sent for collecting users' usage information to discover what information they leak. ...
doi:10.1145/2810103.2810127
dblp:conf/ccs/LiuWL15
fatcat:k2b7hzlcivdqrcp3mbr5bw62fi
Can't You Hear Me Knocking
2015
Proceedings of the 5th ACM Conference on Data and Application Security and Privacy - CODASPY '15
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In this thesis, we move a step forward: we investigate to which extent it is feasible to identify the specific actions that a user is doing on his mobile device, by simply eavesdropping the device's network ...
In particular, we aim at identifying user actions like browsing someone's profile on a social network, posting a message on a friend's wall, or sending an email. ...
Chapter 8
Conclusions In this thesis, we proposed a framework to analyze encrypted network traffic and to infer which particular actions the user executed on some apps installed on his mobile-phone. ...
doi:10.1145/2699026.2699119
dblp:conf/codaspy/ContiMSV15
fatcat:q5fglgz3ebeabdmzoagz2e42jq
Encrypted Network Traffic Analysis of Secure Instant Messaging Application: A Case Study of Signal Messenger App
2021
Applied Sciences
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This study aims to provide a network forensic strategy to identify the potential artifacts from the encrypted network traffic of the prominent social messenger app Signal (on Android version 9). ...
The analysis of the installed app was conducted over fully encrypted network traffic. ...
Conclusions In this paper, the encrypted network traffic of the Signal app was analyzed. ...
doi:10.3390/app11177789
fatcat:wfwp27ybyjdxrij5j7fla7dy4q
Hidden in Plain Sight: Exploring Encrypted Channels in Android apps
[article]
2022
arXiv
pre-print
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As privacy features in Android operating system improve, privacy-invasive apps may gradually shift their focus to non-standard and covert channels for leaking private user/device information. ...
Using ThirdEye, we analyzed 12,598 top-apps in various categories from Androidrank, and found that 2887/12,598 (22.92%) apps used custom encryption/decryption for network transmission and storing content ...
ACKNOWLEDGMENTS We are grateful to all anonymous CCS2022 reviewers for their insightful suggestions, comments, and guiding us in the final version of this paper. ...
arXiv:2209.15107v1
fatcat:lyagga54tjffrnofj6mopivyva
Experimental Analysis of Popular Smartphone Apps Offering Anonymity, Ephemerality, and End-to-End Encryption
[article]
2016
arXiv
pre-print
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As social networking takes to the mobile world, smartphone apps provide users with ever-changing ways to interact with each other. ...
Over the past couple of years, an increasing number of apps have entered the market offering end-to-end encryption, self-destructing messages, or some degree of anonymity. ...
We wish to thank Balachander Krishnamurthy for motivating our research and for numerous helpful discussions, Ruba Abu-Salma for feedback on an earlier version of the manuscript, and PRES-SID for supporting ...
arXiv:1510.04083v3
fatcat:ssoxjtovvzaozapxpu6ddlqxgu
A Survey on Analyzing Encrypted Network Traffic of Mobile Devices
[article]
2020
arXiv
pre-print
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This paper proposes a framework to categorize the research works on analyzing encrypted network traffic related to mobile devices. ...
To that end, researchers are trying to develop techniques to classify encrypted mobile traffic at different levels of granularity, with the objectives of performing mobile user profiling, network performance ...
[56] investigates that at what extend, an eavesdropper can identify the actions performed on a mobile application by mobile users, by analyzing the encrypted traffic. ...
arXiv:2006.12352v1
fatcat:cysjaqpqdfbxjn7b2gsy6gyelu
Network and device forensic analysis of Android social-messaging applications
2015
Digital Investigation. The International Journal of Digital Forensics and Incident Response
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In this research we forensically acquire and analyze the device-stored data and network traffic of 20 popular instant messaging applications for Android. ...
This work shows which features of these instant messaging applications leave evidentiary traces allowing for suspect data to be reconstructed or partially reconstructed, and whether network forensics or ...
In our research group, we have been working on a project to analyze the activity of applications installed on a device to determine network traffic encryption and what services the applications are communicating ...
doi:10.1016/j.diin.2015.05.009
fatcat:jyn6mssaircdpdxx2vqru5vdfu
Mobile Social Service User Identification Framework Based on Action-Characteristic Data Retention
2020
IEEE Access
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SUMMARY This study found that, although the traffic is encrypted, some characteristics can be used to identify the MSSs used, the actions, and the communication party of the user. ...
Thus, more characteristics need to be considered to identify the action the user performed. ...
doi:10.1109/access.2020.3009010
fatcat:t4h3wzft4vemtmeryoyn6xovpe
Eavesdropping on Fine-Grained User Activities Within Smartphone Apps Over Encrypted Network Traffic
2016
Workshop on Offensive Technologies
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In this paper we will demonstrate that a passive eavesdropper is capable of identifying finegrained user activities within the wireless network traffic generated by apps. ...
By learning the subtle traffic behavioral differences between activities (e.g., "browsing" versus "chatting" in a dating app), NetScope is able to perform robust inference of users' activities, for both ...
Besides website fingerprinting there are many other works which analyze encrypted network traffic to uncover numerous other information leakages. ...
dblp:conf/woot/SaltaformaggioC16
fatcat:gkgbvsxhz5bpxj2xdw2zjfrf6a
Security Concerns in Android mHealth Apps
2014
AMIA Annual Symposium Proceedings
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However, mHealth apps, particularly those in the app stores for iOS and Android, are increasingly handling sensitive data for both professionals and patients. ...
Mobile Health (mHealth) applications lie outside of regulatory protection such as HIPAA, which requires a baseline of privacy and security protections appropriate to sensitive medical data. ...
we installed and ran each of the apps while capturing network traffic using the "Shark for Root" Android app, and used WireShark to see if the traffic is encrypted. ...
pmid:25954370
pmcid:PMC4419898
fatcat:rx7eodml25g7zi25nyud4q4f4m
Android OS Privacy Under the Loupe – A Tale from the East
[article]
2023
arXiv
pre-print
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network-related identifiers), user profile (phone number, app usage) and social relationships (e.g., call history), without consent or even notification. ...
Through traffic analysis, we find these packages transmit to many third-party domains privacy sensitive information related to the user's device (persistent identifiers), geolocation (GPS coordinates, ...
preinstalled applications and system services. 3) We only collect and analyze the network traffic generated by system apps and by basic applications such as the dialer and messages apps. ...
arXiv:2302.01890v1
fatcat:i4z7xxhrozcjze2o2lcpcbeuii
Towards automated privacy compliance checking of applications in Cloud and Fog environments
2021
2021 8th International Conference on Future Internet of Things and Cloud (FiCloud)
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We present a procedure based on machinelearning techniques to identify the type of data being shared by applications with external third-parties even if the application uses encrypted communications. ...
Our classifiers identify traffic samples of applications with 86% accuracy. ...
With the proliferation of applications which encrypt their network traffic and users who utilize Virtual Private Networks, it becomes necessary to analyze and classify encrypted data rather than plain ...
doi:10.1109/ficloud49777.2021.00010
fatcat:3z3pxpgrpzhxjbi6x5qqupxslm
ProfileDroid
2012
Proceedings of the 18th annual international conference on Mobile computing and networking - Mobicom '12
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than their paid counterparts, due to an order of magnitude increase in traffic, (c) most network traffic is not encrypted, (d) apps communicate with many more sources than users might expect-as many as ...
Our approach is arguably the first to profile apps at four layers: (a) static, or app specification, (b) user interaction, (c) operating system, and (d) network. ...
Acknowledgements We would like to thank the anonymous reviewers and our shepherd Srdjan Capkun for their feedback. ...
doi:10.1145/2348543.2348563
dblp:conf/mobicom/WeiGNF12
fatcat:c46tx5sb55ebfna4ehd7bw6ob4
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