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区块链的隐写分析。

Steganographic Analysis of Blockchains.

机构信息

Department of Computer Science, Federal University of Technology-Parana (UTFPR), 85902-490 Toledo, PR, Brazil.

Graduate Program on Computer Science, Department of Informatics and Statistics, Federal University of Santa Catarina (UFSC), 88040-370 Florianópolis, SC, Brazil.

出版信息

Sensors (Basel). 2021 Jun 13;21(12):4078. doi: 10.3390/s21124078.

Abstract

Steganography is one of the ways to hide data between parties. Its use can be worrisome, e.g., to hide illegal communications. Researchers found that public blockchains can be an attractive place to hide communications; however, there is not much evidence of actual use in blockchains. Besides, previous work showed a lack of steganalysis methods for blockchains. In this context, we present a steganalysis approach for blockchains, evaluating it in Bitcoin and Ethereum, both popular cryptocurrencies. The main objective is to answer if one can find steganography in real case scenarios, focusing on LSB of addresses and nonces. Our sequential analysis included 253 GiB and 107 GiB of bitcoin and ethereum, respectively. We also analyzed up to 98 million bitcoin clusters. We found that bitcoin clusters could carry up to 360 KiB of hidden data if used for such a purpose. We have not found any concrete evidence of hidden data in the blockchains. The sequential analysis may not capture the perspective of the users of the blockchain network. In this case, we recommend clustering analysis, but it depends on the clustering method's accuracy. Steganalysis is an essential aspect of blockchain security.

摘要

隐写术是在双方之间隐藏数据的一种方式。它的使用可能令人担忧,例如,用于隐藏非法通信。研究人员发现,公共区块链可能是隐藏通信的一个有吸引力的地方;然而,区块链中实际使用的证据并不多。此外,以前的工作表明区块链缺乏隐写分析方法。在这种情况下,我们提出了一种区块链的隐写分析方法,并在比特币和以太坊这两种流行的加密货币中进行了评估。主要目标是回答在实际场景中是否可以找到隐写术,重点是地址和随机数的 LSB。我们的顺序分析分别包含了 253GB 和 107GB 的比特币和以太坊数据。我们还分析了多达 9800 万个比特币集群。我们发现,如果比特币集群用于这种目的,它们可以携带高达 360KB 的隐藏数据。我们没有在区块链中发现任何隐藏数据的确凿证据。顺序分析可能无法捕捉区块链网络用户的视角。在这种情况下,我们建议进行聚类分析,但这取决于聚类方法的准确性。隐写分析是区块链安全的一个重要方面。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1de4/8231769/c41dbb0a95d7/sensors-21-04078-g001.jpg

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