Deanonymizing Tor hidden service users through Bitcoin transactions analysis

被引:35
|
作者
Al Jawaheri, Husam [1 ]
Al Sabah, Mashael [2 ]
Boshmaf, Yazan [2 ]
Erbad, Aiman [3 ]
机构
[1] Univ Luxembourg, Luxembourg, Luxembourg
[2] HBKU, Qatar Comp Res Inst, Ar Rayyan, Qatar
[3] Qatar Univ, Doha, Qatar
关键词
Bitcoin; Tor hidden services; Privacy; Deanonymization; Attack;
D O I
10.1016/j.cose.2019.101684
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the rapid increase of threats on the Internet, people are continuously seeking privacy and anonymity. Services such as Bitcoin and Tor were introduced to provide anonymity for online transactions and Web browsing. Due to its pseudonymity model, Bitcoin lacks retroactive operational security, which means historical pieces of information could be used to identify a certain user. By exploiting publicly available information, we show how relying on Bitcoin for payments on Tor hidden services could lead to deanonymization of these services' users. Such linking is possible by finding at least one past transaction in the Blockchain that involves their publicly declared Bitcoin addresses. To demonstrate the consequences of this deanonymization approach, we carried out a real-world experiment simulating a passive, limited adversary. We crawled 1.5K hidden services and collected 88 unique and active Bitcoin addresses. We then crawled 5B tweets and 1M BitcoinTalk forum pages and collected 4.2K and 41K unique Bitcoin addresses, respectively. Each user address was associated with an online identity along with its public profile information. By analyzing the transactions in the Blockchain, we were able to link 125 unique users to 20 hidden services, including sensitive ones, such as The Pirate Bay and Silk Road. We also analyzed two case studies in detail to demonstrate the implications of the information leakage on users anonymity. In particular, we confirm that Bitcoin addresses should be considered exploitable, as they can be used to deanonymize users retroactively. This is especially important for Tor hidden service users who actively seek and expect privacy and anonymity. (C) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页数:11
相关论文
共 50 条
  • [41] A BIT LIKE CASH: UNDERSTANDING CASH-FOR-BITCOIN TRANSACTIONS THROUGH INDIVIDUAL VENDORS
    Robberson, Stephanie J.
    McCoy, Mark R.
    JOURNAL OF DIGITAL FORENSICS SECURITY AND LAW, 2018, 13 (02)
  • [42] Push and pull Tor users' guards through optimized resource portfolios
    Zhang, Guoqiang
    Xu, Mingwei
    Qinghua Daxue Xuebao/Journal of Tsinghua University, 2024, 64 (08): : 1293 - 1305
  • [43] Identification of High Yielding Investment Programs in Bitcoin via Transactions Pattern Analysis
    Toyoda, Kentaroh
    Ohtsuki, Tomoaki
    Mathiopoulos, P. Takis
    GLOBECOM 2017 - 2017 IEEE GLOBAL COMMUNICATIONS CONFERENCE, 2017,
  • [44] Analysis of multi-input multi-output transactions in the Bitcoin network
    Phetsouvanh, Silivanxay
    Datta, Anwitaman
    Oggier, Frederique
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2021, 33 (01):
  • [45] Dark web advertising: the dark magic system on tor hidden service search engines
    Gehl, Robert W.
    CONTINUUM-JOURNAL OF MEDIA & CULTURAL STUDIES, 2021, 35 (05): : 667 - 678
  • [46] A New Framework for Fraud Detection in Bitcoin Transactions Through Ensemble Stacking Model in Smart Cities
    Nayyer, Noor
    Javaid, Nadeem
    Akbar, Mariam
    Aldegheishem, Abdulaziz
    Alrajeh, Nabil
    Jamil, Mohsin
    IEEE ACCESS, 2023, 11 : 90916 - 90938
  • [47] Bitcoin Analysis and Forecasting through Fuzzy Transform
    Guerra, Maria Letizia
    Sorini, Laerte
    Stefanini, Luciano
    AXIOMS, 2020, 9 (04) : 1 - 32
  • [48] An Analysis of Bitcoin Dust Through Authenticated Queries
    Loporchio, Matteo
    Bernasconi, Anna
    Maesa, Damiano Di Francesco
    Ricci, Laura
    COMPLEX NETWORKS AND THEIR APPLICATIONS XI, COMPLEX NETWORKS 2022, VOL 2, 2023, 1078 : 495 - 508
  • [49] Data-driven analysis of Bitcoin properties: exploiting the users graph
    Maesa, Damiano Di Francesco
    Marino, Andrea
    Ricci, Laura
    INTERNATIONAL JOURNAL OF DATA SCIENCE AND ANALYTICS, 2018, 6 (01) : 63 - 80
  • [50] Enhancing Traffic Analysis Resistance for Tor Hidden Services with Multipath Routing
    Yang, Lei
    Li, Fengjun
    2015 IEEE CONFERENCE ON COMMUNICATIONS AND NETWORK SECURITY (CNS), 2015, : 745 - 746