TY - GEN
T1 - Analyzing HtTPS encrypted traffic to identify user's operating system, browser and application
AU - Muehlstein, Jonathan
AU - Zion, Yehonatan
AU - Bahumi, Maor
AU - Kirshenboim, Itay
AU - Dubin, Ran
AU - Dvir, Amit
AU - Pele, Ofir
N1 - Publisher Copyright:
© 2019 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.
PY - 2017/7/17
Y1 - 2017/7/17
N2 - Desktops and laptops can be maliciously exploited to violate privacy. There are two main types of attack scenarios: active and passive. In this paper, we consider the passive scenario where the adversary does not interact actively with the device, but he is able to eavesdrop on the network traffic of the device from the network side. Most of the internet traffic is encrypted and thus passive attacks are challenging. In this paper, we show that an external attacker can identify the operating system, browser and application of HTTP encrypted traffic (HTTPS). To the best of our knowledge, this is the first work that shows this. We provide a large data set of more than 20000 examples for this task. Additionally, we suggest new features for this task. We run a through a set of experiments, which shows that our classification accuracy is 96.06%.
AB - Desktops and laptops can be maliciously exploited to violate privacy. There are two main types of attack scenarios: active and passive. In this paper, we consider the passive scenario where the adversary does not interact actively with the device, but he is able to eavesdrop on the network traffic of the device from the network side. Most of the internet traffic is encrypted and thus passive attacks are challenging. In this paper, we show that an external attacker can identify the operating system, browser and application of HTTP encrypted traffic (HTTPS). To the best of our knowledge, this is the first work that shows this. We provide a large data set of more than 20000 examples for this task. Additionally, we suggest new features for this task. We run a through a set of experiments, which shows that our classification accuracy is 96.06%.
KW - Application
KW - Browser
KW - Encrypted traffic
KW - HTTPS
KW - Operating system
UR - http://www.scopus.com/inward/record.url?scp=85087199147&partnerID=8YFLogxK
U2 - 10.1109/CCNC.2017.8013420
DO - 10.1109/CCNC.2017.8013420
M3 - Conference contribution
AN - SCOPUS:85087199147
T3 - 2017 14th IEEE Annual Consumer Communications and Networking Conference, CCNC 2017
BT - 2017 14th IEEE Annual Consumer Communications and Networking Conference, CCNC 2017
PB - Institute of Electrical and Electronics Engineers
T2 - 14th IEEE Annual Consumer Communications and Networking Conference, CCNC 2017
Y2 - 8 January 2017 through 11 January 2017
ER -