The peer-to-peer (P2P) network of blockchain used to transport its transactions and blocks has a high impact on the efficiency and security of the system. The P2P network topologies of popular blockchains such as Bitcoin and Ethereum, therefore, deserve our highest attention. The current Ethereum blockchain explorers (e.g., Etherscan) focus on the tracking of block and transaction records but omit the characterization of the underlying P2P network. This work presents the Ethereum Network Analyzer (Ethna), a tool that probes and analyzes the P2P network of the Ethereum blockchain. Unlike Bitcoin that adopts an unstructured P2P network, Ethereum relies on the Kademlia DHT to manage its P2P network. Therefore, the existing analytical methods for Bitcoin-like P2P networks are not applicable to Ethereum. Ethna implements a novel method that accurately measures the degrees of Ethereum nodes. Furthermore, it incorporates an algorithm that derives the latency metrics of message propagation in the Ethereum P2P network. We ran Ethna on the Ethereum Mainnet and conducted extensive experiments to analyze the topological features of its P2P network. Our analysis shows that the Ethereum P2P network possesses a certain effect of small-world networks, and the degrees of nodes follow a power-law distribution that characterizes scale-free networks.

Ethna: Analyzing the Underlying Peer-to-Peer Network of Ethereum Blockchain

Proof of Work (PoW) powered blockchains currently account for more than 90% of the total market capitalization of existing digital cryptocurrencies. Although the security provisions of Bitcoin have been thoroughly analysed, the security guarantees of variant (forked) PoW blockchains (which were instantiated with different parameters) have not received much attention in the literature. This opens the question whether existing security analysis of Bitcoin's PoW applies to other implementations which have been instantiated with different consensus and/or network parameters. In this paper, we introduce a novel quantitative framework to analyse the security and performance implications of various consensus and network parameters of PoW blockchains. Based on our framework, we devise optimal adversarial strategies for double-spending and selfish mining while taking into account real world constraints such as network propagation, different block sizes, block generation intervals, information propagation mechanism, and the impact of eclipse attacks. Our framework therefore allows us to capture existing PoW-based deployments as well as PoW blockchain variants that are instantiated with different parameters, and to objectively compare the tradeoffs between their performance and security provisions.

/pdf/on-the-security-and-performance-of-proof-of-work-blockchains-799069isiy.pdf

On the Security and Performance of Proof of Work Blockchains

Filter gate network based on multi-head attention for aspect-level sentiment classification

Summary Ethereum is arguably the second most popular cryptocurrency‐based network after Bitcoin. Both use the distributed ledger technology known as the blockchain, which is considered secure. Howe...

Visualization of Ethereum P2P network topology and peer properties

Public blockchains, like Ethereum, rely on an underlying peer-to-peer (P2P) network to disseminate transactions and blocks between nodes. With the rise of blockchain applications and cryptocurrencies values, they have become critical infrastructures which still lack comprehensive studies. In this paper, we propose to investigate the reliability of the Ethereum P2P network. We developed our own dependable crawler to collect information about the peers composing the network. Our data analysis regarding the geographical distribution of peers and the churn rate shows good network properties while the network can exhibit a sudden and major increase in size and peers are highly concentrated on a few ASes. In a second time, we investigate suspicious patterns that can denote a Sybil attack. We find that many nodes hold numerous identities in the network and could become a threat. To mitigate future Sybil attacks, we propose an architecture to detect suspicious nodes and revoke them. It is based on a monitoring system, a smart contract to propagate the information and an external revocation tool to help clients remove their connections to suspicious peers. Our experiment on Ethereum’s Test network proved that our solution is effective. 

/pdf/ethereums-peer-to-peer-network-monitoring-and-sybil-attack-mmefgt0z.pdf

Ethereum’s Peer-to-Peer Network Monitoring and Sybil Attack Prevention

Ethereum, one of the most popular cryptocurrencies, has attracted increasing attention of people in various fields. As the backbone of Ethereum, its peer-to-peer network has an effect on almost every aspect of the ecosystem. Consequently, it’s necessary to understand the topological properties of Ethereum P2P network. In this paper, we conducted a measurement of Ethereum P2P network. Our result shows that the graphs of Ethereum network have a small average shortest path length and a large clustering coefficient, and the degree distribution of nodes does not follow a pure power-law distribution. These indicate that Ethereum network is very close to a small world network. Though there are a large number of stale nodes and useless nodes, Ethereum is still resilient to both random failures and targeted attacks. What’s more, we find that there are around one hundred abnormal nodes in the network. The IP addresses of nodes included in the neighbors messages they reply are replaced with their own IP addresses. Those nodes might have a bad influence on network routing.

Topology Measurement and Analysis on Ethereum P2P Network

The invention discloses a website classification method based on the comprehensive characteristics of the dark net websites. The website classification method based on the comprehensive characteristics of the dark net websites comprises the following steps: 1) crawling a target dark net website and obtaining a dark net website training set with labels; 2) extracting the information of each website in the set and performing word separation to construct the spatial vector of the words of the website, and calculating the weight of each word; and using the spatial vector formed by multiplying the words with the corresponding weight as the textual characteristic of the website; 3) extracting the label of each website of the dark net website training set, constructing the spatial vector of the label of the website, and calculating the weight of each label; and using the spatial vector formed by multiplying the label with the corresponding weight as the structural characteristic of the website; 4) combining the textual characteristic and the structural characteristic of each website to obtain the comprehensive characteristics of the website; and 5) training the comprehensive characteristics of each website to obtain a classification model; and predicting the websites to be classified by means of the classification model to obtain the classes of the websites to be classified. By means of the website classification method based on the comprehensive characteristics of the dark net websites, the efficiency of website classification is improved.

Website classification method based on comprehensive characteristics of dark net websites

Aspect-level sentiment classification aims at inferring the sentiment polarities of opinion targets for a given sentence. As a sentence might contain multiple sentiment-target pairs, extracting relevant information concerning the given target entity is the main challenge of this task. We try to overcome the challenge from two aspects. First, the attention mechanism is able to focus on the relevant part of the given entity and is well suited for this task. However, previous attention-based models still suffer from the problem of paying too much attention to some sentiment words that are irrelevant to the target. We call this as attention bias problem. To alleviate the biases, in this work, we introduce an adversarial training method to get unbiased attention. Second, we try to enhance the impact of the target from the perspective of word representations. Thus we propose an Embedding-Preserving Gating (EPGating) Mechanism. The mechanism dynamically incorporates target-related features into word representations as well as retains original word information. The experimental results on SemEval datasets demonstrate the effectiveness of our model.

https://dl.acm.org/doi/pdf/10.1145/3341105.3373869

Aspect level sentiment classification with unbiased attention and target enhanced representations

In this paper, we propose the SignalCookie attack which can reveal guard relays of multiple hidden services in parallel. The key insight of our method is utilizing Rendezvous Cookie and circuit watermark to deliver the hidden services’ identifiers to our controlled relays. By conducting the attack in parallel, the speed of our method increases about 11.6 times compared with the previous work, so that we can continually monitor the guard relays of 13604 hidden services for 7 months. And we have an interesting finding by analyzing the distribution of hidden services binding on each guard relays. The distribution is quite uneven, that only 20% of guard relays serve about 89.32% hidden services. These guard relays would bind all hidden services at least one time in about 17 months. At last, we analyze several security problems aggravated by the uneven distribution, and find that just one corrupt guard relay may cause hundreds of hidden services being de-anonymized or eclipsed.

SignalCookie: Discovering Guard Relays of Hidden Services in Parallel

ZeroNet is a new decentralized web-like network of peer-to-peer users created in 2015. ZeroNet, called an open, free and robust network, has attracted a rising number of users. Most of P2P networks are applied into file-sharing systems or data-storage system and the characteristics of these networks are widely investigated. However, there are obvious differences between ZeroNet and conventional P2P networks. Existing researches rarely involve ZeroNet and the characteristics and robustness of ZeroNet are unknown. To tackle the aforementioned problem, the present study measures the ZeroNet peer resources and site resources separately, and at the same time, proposes collection methods for both. No like other simulation experiments, the experiments of this paper are set on real-world environment. This is also the first measurement study about ZeroNet. Experimental results show that the topology of the peer network in ZeroNet has scarce edges, short distances and low clustering coefficients, and its degree distribution exhibits a special distribution. These indicate that the peer network of ZeroNet has poor robustness and the experimental results of the ZeroNet resilience verify this issue. In addition, this paper represents an improved peer exchange method to enhance the robustness of the ZeroNet. We also measure the topology characteristics, languages, sizes and versions of the sites in ZeroNet. We find that the size of the sites and the client version are also the reasons for the low robustness of the ZeroNet.

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Zelin Yin

Papers

Topology Measurement and Analysis on Ethereum P2P Network

Website classification method based on comprehensive characteristics of dark net websites

Aspect level sentiment classification with unbiased attention and target enhanced representations

SignalCookie: Discovering Guard Relays of Hidden Services in Parallel

Look Deep into the New Deep Network: A Measurement Study on the ZeroNet