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Federated Learning, a model-sharing method, and Data Collaboration, a non-model-sharing method, are recognized as data analysis methods for distributed data. In Federated Learning, clients send only the parameters of a machine learning model to the central server. In Data Collaboration, clients send data that has undergone irreversibly transformed through dimensionality reduction to the central server. Both methods are designed with privacy concerns, but privacy is not guaranteed. Differential Privacy, a theoretical and quantitative privacy criterion, has been applied to Federated Learning to achieve rigorous privacy preservation. In this paper, we introduce a novel method using PCA (Principal Component Analysis) that finds low-rank approximation of a matrix preserving the variance, aiming to apply Differential Privacy to Data Collaboration. Experimental evaluation using the proposed method show that differentially-private Data Collaboration achieves comparable performance to differentially-private Federated Learning.

The research area of cybersecurity covers a wide range of fields from networking, software, and hardware to cryptography, authentication, and cyberattack countermeasures. Meanwhile, few cybersecurity experts are familiar with all areas of cybersecurity research. So, an evidence-based analysis covering all fields is very important to understand research trends in cybersecurity without bias. Such a field of study is called scientometrics, and there are many studies of scientometrics in the area of cybersecurity. However, in the analysis of these existing studies, the overall structure of the cybersecurity research is not clarified, and it is difficult to grasp the overall picture of cybersecurity research. In this study, we focus on cybersecurity as a research area covered by scientometrics analysis and conduct a detailed analysis of research trends in cybersecurity using e-CSTI (evidence data platform constructed by Council for Science, Technology and Innovation), and Dimensions bibliographic data for the 10 years from 2010 to 2019. Especially, we identify four representative research clusters (cyberattack, cryptography, authentication, and blockchain) and 55 research sub-clusters in the area of cybersecurity. We analyze the research trends in each country and the trends of the research topics of interest at the cluster level. For example, our results show that there are differences in research topics of emphasis between the U.S. and China. e-CSTI assists policymakers and researchers in getting a comprehensive understanding of global research trends and topics of interest in cybersecurity research.

In recent years, the convenience and potential use of crypto-assets such as Bitcoin and Ethereum have attracted increasing attention. On the other hand, there have been reports of attacks on the blockchain networks that support crypto-assets in an attempt to steal other users’ assets. In the past, research on attack observation against blockchains has used techniques such as holding real crypto-assets to lure attackers into honeypots or falsifying balances to attackers. However, these methods risk losing crypto-assets to attackers or being exposed as honeypots to attackers. To solve these problems, we propose a new RPC (Remote Procedure Call) honeypot method that returns the wallet address of another party holding a high balance in response to an attacker’s request, thereby luring the attacker without having the real crypto-assets. Our experimental evaluation shows that this method can attract more attackers than the method with zero-balance wallets and can observe more sophisticated attacks. Furthermore, we proposed a risk reduction strategy for crypto-asset theft by applying the idea of our method. In the log analysis process, we devised a new clustering method using the number of times an attacker executes a specific method as a feature. By applying this method, we successfully classified attackers based on their objectives, demonstrating the efficient analysis of vast amounts of log data.

With the rapid development of Non-Fungible Token (NFT) market, various types of digital artwork are published via NFT in recent years for sale. In the current NFT system, owner’s address of each NFT is stored in plaintext. This leads to a severe privacy problem: once a person’s blockchain address is known, all his NFT assets are viewable, which may further cause problems related to the privacy of holding sensitive NFT or premeditated scams to high-value NFT owners. However, due to the limitation of Ethereum and smart contract, it is hard to prevent others from tracking the owner of NFT. Meanwhile, current state-of-the-art NFT research usually assumes the relation between blockchain address and owner’s identity is unknown, thus creating the so-called anonymity. In this paper, based on the most popular NFT marketplace OpenSea’s system, we propose a new exchange scheme to hides the address of NFT owner during trading. To achieve our goal, a proof of commitment scheme is exploited to bind the owner to an NFT while hiding the identity. Moreover, An anonymous payment method is designed to prevent attackers from tracing the Ether flow in NFT trading. Our scheme is proven to be secure against curious users and malicious active attackers. Implementation on testnet also shows that the increased gas cost is acceptable, meaning it is suitable for application.

Data availability is a security factor in a blockchain that is challenging to understand and explain because it cannot be described cryptographically or mathematically because of its behavior-dependent properties on the volunteers who maintain the distributed ledger in the network. Most previous approaches have frequently used successful projects with empirically effective availability, such as Bitcoin and Ethereum, to analyze more active blockchain networks. Therefore, even if much of the Altcoin forked from Bitcoin had nodes in the network, contrary to intuition because they were unpopular and failed projects, they were not the focus of much attention in the analysis. However, it is interesting to note that both can maintain availability. Considering the network structure that supports availability, it is possible to investigate Altcoin’s features as a minimal component because it is a failed project, whereas it is challenging to do so with Bitcoin and Ethereum because of their complex components. Thus, we specifically selected Altcoin in decline based on our user role model. We investigated the features of the network that maintain availability and the user structure underlying Altcoin, focusing on factors associated with continuity, such as initial node survivability, interest in software updates, and nodes with security risks. We discovered that compared with a stand-alone organization, the actions of early users and few community-friendly users provide greater availability. We also discuss the motivations of these users based on the cost of installing the nodes.

In recent years, the spread of information and communication technology has led to the emergence of e-government, which is the electronic replacement of government services. E-government is said to be compatible with blockchain technology, which has led to various studies on the possibility. Notarization, one of the functions of the government, has particularly been examined for the potential adoption of blockchain technology. However, because the notary public must authenticate the document’s contents during the notarization process, they have been difficult to replace with smart contracts. In this study, we focus only on fixed date notarizations and propose a fully automated notarization system by combining a national eID card with Public Key Infrastructure and smart contracts. A fixed date is a notarization that allows a notary public to guarantee that a document existed, regardless of the authenticity of the document’s content. Therefore, it can be replaced by a smart contract. Specifically, our proposed system automatically authenticates the creator and the document for electronic documents signed with a national eID card and uses the transaction receipt generated when the information is stored on the blockchain as a certificate of notarization. Verification of the signed data is done inside the blockchain by smart contracts, which eliminates the need for a verification authority. We further demonstrate the effectiveness of the proposed method in a Japanese use case as proof of concept.

During the Coincheck incident, which recorded the largest damages in cryptocurrency history in 2018, it was demonstrated that using Mosaic token can have a certain effect. Although it seems attractive to employ tokens as countermeasures for cryptocurrency leakage, Mosaic is a specific token for the New Economy Movement (NEM) cryptocurrency and is not employed for other blockchain systems or cryptocurrencies. Moreover, although some volunteers tracked leaked NEM using Mosaic in the CoinCheck incident, it would be better to verify that the volunteers can be trusted. Simultaneously, if someone (e.g., who stole cryptocurrencies) can identify the volunteers, then that person or organization may be targets of them. In this paper, we propose an anonymous trust-marking scheme on blockchain systems that is universally applicable to any cryptocurrency. In our scheme, entities called token admitters are allowed to generate tokens adding trustworthiness or untrustworthiness to addresses. Anyone can anonymously verify whether these tokens were issued by a token admitter. Simultaneously, only the designated auditor and no one else, including nondesignated auditors, can identify the token admitters. Our scheme is based on accountable ring signatures and commitment, and is implemented on an elliptic curve called Curve25519, and we confirm that both cryptographic tools are efficient. Moreover, we also confirm that our scheme is applicable to Bitcoin, Ethereum, and NEM.

When data owners publish their data to a cloud storage, data integrity and availability become typical problems because the cloud servers are never trusted. To address these problems, researchers proposed the Proof of Retrievability (POR) protocol which allows a verifier to check and repair the data stored in the cloud servers. Based on the POR protocol, the network coding technique is commonly applied to increase the efficiency in data transmission and data repair. However, most previous schemes neither consider a practical scenario nor use the network coding efficiently. In this paper, a lightweight network coding-based POR scheme, called MD-POR (Multisource and Direct Repair for Proof of Retrievability) is proposed. Unlike previous schemes, the proposed MD-POR scheme allows multiple clients who have different secret keys to participate in the scheme. Moreover, the MD-POR scheme supports the direct repair feature in which a corrupted data can be recovered by the servers without burdening the clients. The MD-POR scheme also supports public authentication feature in which a third party auditor is employed to check the servers, and the client is thus free of the responsibility of periodically checking the servers. Furthermore, the MD-POR scheme is constructed based on a symmetric key setting.

If there are many displaced workers in a company, then a person who goes for job hunting might not select this company. That is, the number of members who quit is quite negative information. Similarly, in revocable group signature schemes, if one knows (or guesses) the number of revoked users (say r), then one may guess the reason behind such circumstances, and it may lead to harmful rumors. However, no previous revocation procedure can achieve hiding r. In this paper, we propose the first revocable group signature scheme, where r is kept hidden, which we call r-hiding revocable group signature. To handle this property, we newly define the security notion called anonymity with respect to the revocation which guarantees the unlinkability of revoked users.