Follow blockchain research across journals, conferences, and preprint repositories.
96,811 results · page 288 of 4,034
Reo Fukuda, Naoki Akamatsu, Satoko Suzuki
No abstract is available for this record.
Suman Kumar Das, Soumyabrata Saha, Suparna DasGupta, Sudarshan Nath
No abstract is available for this record.
Prof. Abhijeet More, Tejashree B. Patil, Deep Kharate, M P Akhil · 5 authors
As the multi-chain digital assets, decentralized finance (DeFi) and non-fungible tokens (NFTs) seeing rapid development, cryptocurrency portfolio management is causing strong pain among users.With the growing number of blockchain networks like Ethereum and a variety of chains, users commonly have assets across multiple wallets, protocols and dApps.Classic portfolio tracking services often require the constant relationship between client and server, with centralized servers, offering heavy privacy issues and security implications.Manual and account based access Many of these systems require data to be manually entered or employees to sign in with their accounts, which opens up the possibility for data leaks, inaccurate reporting, and divulgence of sensitive financial information.More centralized trackers unfortunately have a very poor understanding of more advanced DeFi functions such as staking, joining liquidity pools, and yield farming positions, total or just plain token approval permissions leading to either incomplete or worse yet misleading asset summaries.To solve the above issues, this system suggests a completely decentralized cryptocurrency portfolio tracker on client-side.The code utilizes APIs like Alchemy, Zapper and CoinGecko to read real-time token balances, NFTs creatures or positions (for DeFi), and allowances from the current network directly offchain.Being exclusively client side, the tracker does not rely on centralized databases and it is designed to minimize privacy compromises.The built-in on-chain security module is its most noticeable feature, as it detects any potentially malicious or extremely large token approvals given to smart contracts.Suspicious approvals can be detected, and then revoked in a timely manner through signed wallet transactions without needing to reveal any private keys.The results show that this decentralized tracker would provide significantly better user privacy, data accuracy and overall security.As a serverless applications service, that bypasses central authentication, as well as database storage, it offers a transparency, user-centric and scalable way to manage digital assets securely.
Ke Ding, Xiaoyan Hu, Zhuozhuo Shu, Guang Cheng · 6 authors
Non-Fungible Tokens (NFTs) have completely changed digital ownership and the decentralized economy. However, their anonymity and encrypted communication, conducted over encrypted tunnels, pose a significant obstacle to regulating illegal activities. Despite advances in encrypted traffic analysis, fine-grained identification of NFT behaviors over encrypted tunnels faces two critical challenges: 1) inexact segmentation of continuous behavioral traffic, and 2) feature homogeneity due to encryption-induced pattern obfuscation. In this paper, we propose NFTracker, a novel framework to identify fine-grained NFT behavioral traffic over encrypted tunnels. We design a traffic segmentation method to isolate behavioral units by leveraging traffic bursts and distribution discrepancies. To combat feature homogeneity, we introduce a sliding-window-based spatio-temporal feature extraction mechanism that captures localized action fingerprints. Furthermore, we utilize a hybrid CNN-Transformer model to integrate spatial patterns and temporal dependencies for robust behavior identification. We evaluate NFTracker on real-world datasets covering five NFT behaviors (browsing, wallet login, purchasing, selling, and minting). Experimental results demonstrate that NFTracker achieves an average F1-score of 0.9212 on identifying NFT behavioral traffic, outperforming state-of-the-art methods in encrypted tunnel scenarios.
Beomjoong Kim, Hyoung Joong Kim, Junghee Lee
No abstract is available for this record.
Michael Adjedj, Constantin Blokh, Geoffroy Couteau, Arik Galansky · 6 authors
We present a novel protocol for two-party ECDSA that achieves two rounds (a single back-and-forth communication) at the cost of a single oblivious linear function evaluation (OLE). In comparison, the previous work of Boneh, Haitner, Lindell, and Segev (EUROCRYPT 2025) achieves two rounds but requires expensive zero-knowledge proofs on top of the OLE. We demonstrate this by proving that in the generic group model, any adversary capable of generating forgeries for our protocol can be transformed into an adversary that finds preimages for the ECDSA message digest function (e.g., the SHA family). Interestingly, our analysis is closely related to, and has ramifications for, the ‘presignatures’ mode of operation—Canetti, Gennaro, Goldfeder, Makriyannis, and Peled (CCS 2020), Groth and Shoup (EUROCRYPT 2022).Motivated by applications to embedded cryptocurrency wallets, where a single server maintains distinct, shared public keys with separate clients (i.e., a star-shaped topology), and with the goal of minimizing communication, we instantiate our protocol using Paillier encryption and suitable zero-knowledge proofs. To reduce computational overhead, we thoroughly optimize all components of our protocol under sound cryptographic assumptions, specifically small-exponent variants of RSA-style assumptions.Finally, we implement our protocol and provide benchmarks. At the 128-bit security level, the signing phase requires approximately 50 ms of computation time on a standard linux machine, and 2 KB of bandwidth.
Mehmuna Haque, Samana Dahal, Indranil Roy, Reshmi Mitra · 5 authors
No abstract is available for this record.
Rowena Gan, Rong Li
No abstract is available for this record.
Katrin Schuler
No abstract is available for this record.
Lixue Liu, Wei Ke, Haiyang Chi
No abstract is available for this record.
Nabeel Mahdialthabhawi, Ra’ed Fawzi Aburoub, Motiur Rahman, Faris Kamil Hasan Mihna · 5 authors
This study delves into the integration of force majeure and exceptional events into smart contracts. As much as smart contracts simplify the process and guarantee efficiency, the rigidity of these contracts inherently cannot handle unexpected eventualities that might be provided for in a traditional contract with a force majeure clause. This paper explores the impacts of such rigidity and uncovers both practical and theoretical implications for the legal and technological frameworks governing smart contracts through a qualitative analysis of interviews with legal experts, including (attorneys, judges, and academics). The findings show that the immutability of smart contracts leads all too often to disputes, financial risks, and a lack of legal clarity in an unexpected event. Rather than advocating full automation of legal judgment, the study proposes a governance-oriented and legally-grounded framework in which predefined contractual clauses, oracle-based event verification, AI, conditional execution logic, and escalation mechanisms enable controlled and proportionate responses to exceptional events while preserving contractual consent and human oversight. These mechanisms are presented as conceptual and illustrative design strategies through which legal effects can be technically implemented (e.g., suspension, adjustment, termination) under clearly predefined conditions. By integrating empirical legal insights with conceptual technical models, such as a systematic taxonomy of exceptional events, a high-level governance-oriented framework and a procedural flowchart regarding regulatory alignment, the paper contributes to inter-disciplinary literature concerning adaptive governance of smart contracts; the analysis serves as an example how legal doctrines can influence automated contracting without undermining interpretative authority, or legal certainty in cross-border and volatile settings.
Michele Angelo Forlani
No abstract is available for this record.
Hojun Kang, Silvana Trimi, Sang Gun Lee
No abstract is available for this record.
Hatice Banu Yildirim
This paper examines whether social media sentiment derived from Twitter and Reddit improves the explanation and prediction of cryptocurrency volatility. Using Bitcoin and Ethereum as benchmark assets, we combine sentiment indicators with GARCH-type models and the HAR-RV framework. Results suggest that cryptocurrency volatility is primarily driven by internal market dynamics rather than social media sentiment.
MAHA AL-ZBOON, Mu'awya Al-Dala'ien
No abstract is available for this record.
Ricardo Teruel-Gutiérrez
No abstract is available for this record.
Wei Wang, Pengyu Guan, Tao Leng, Zhiyuan Peng · 10 authors
No abstract is available for this record.
Roger Welch
Rongorongo is an undeciphered script from Easter Island (Rapa Nui) surviving on fewer than 30 wooden artifacts. This paper proposes that the surviving corpus constitutes the kohau tau, a named class of annual record tablets documented in Rapanui oral tradition and assumed lost. Computational analysis of 146 parallel passages from the Horley (2021) corpus identifies eight independent structural findings supporting a distributed administrative ledger interpretation: a universal list format across nine passages on multiple artifacts; a lozenge-series quantity notation system with power-law frequency distribution consistent with real resource counts; a standardized subject-quantity-subject ledger entry format on three independent artifacts; a calendar section delimiter encoding the Miru clan chief, lunar official, and fishing activity as a recurring administrative header; directional binary encoding recording resource arrival and departure status; an unsupervised two-zone structural classification showing a 10x difference in list-format rate (18.4% administrative vs. 1.9% ceremonial), cross-validated at 94.5% accuracy; a directional invariance property of the subject-quantity-subject notation confirming it was designed for multiple readers regardless of boustrophedon orientation; and a 20/20 universality score for five compound rules confirmed across Chinese oracle bone script, Egyptian hieroglyphs, Sumerian cuneiform, and Mayan glyphs. A control test applying identical structural features to 58 Uruk-period Sumerian cuneiform tablets with known genre labels achieves 100% classification accuracy, externally validating the methodology. Thomson's (1891) tablet text explicitly listing five resource domains under chiefly control is identified as the administrative charter of the system. Ethnographic documentation from Metraux (1940) confirms the binary seasonal tapu/noa encoding predicted by the lozenge system. The most complete currently interpretable entry records one unit of turtle (honu) in Passage 123 on artifact Gr5, supported by Metoro's native speaker identification, corpus structural analysis, and quantity notation confirmation.
Ramesh Kumar, Joy Dutta, M. Vamsi, Uma Sankararao Varri · 5 authors
The integration of Artificial Intelligence (AI) into sixth-generation (6G) networks is a foundational requirement for achieving unprecedented performance, but it also introduces a sophisticated threat landscape that legacy security frameworks cannot address. This paper presents a comprehensive review of this dual role of AI, analyzing its potential to both compromise and safeguard future networks. Since AI has the ability to both protect and compromise security and privacy, its implementation with 6G technology may sometimes be a double-edged sword. The primary objective of this survey is to systematically analyze existing research that integrates AI techniques into 6G architectures, focusing on their implications for security and privacy. Among the concerns being investigated is the fundamental privacy and security risk associated with 6G technologies. Therefore, in order to incorporate and confirm this foundational research as a platform for future research, we have developed a review on the specifics of 6G security and privacy. The methodology involves reviewing recent academic and industrial studies related to AI-enabled 6G frameworks, threat models, and defense mechanisms, with an emphasis on how AI contributes to intrusion detection, authentication, and privacy preservation. This paper begins with a historical analysis of previous networking technologies and how they impacted contemporary 6G networking improvements. Therefore, this article discusses extensively the aspects that have rendered 6G technology relevant as well as the ongoing 6G-based projects. In addition, it identifies and critically evaluates key enabling technologies, including distributed ledger technology (DLT/blockchain), physical layer security (PLS), terahertz (THz) communication, quantum computing, visible light communication (VLC), and distributed AI/ML, that underpin secure 6G environments. The paper concludes by summarizing open challenges, future research opportunities, and potential pathways for building trustworthy AI-driven 6G systems.
David Bednorz, Knut Neumann
No abstract is available for this record.
John Linarelli
No abstract is available for this record.
Jie Gao, Gang Liu, Kun Zhou, Hongbing Cheng
No abstract is available for this record.
Adam Hatefi
No abstract is available for this record.
QIUYING CHEN, Nan Wang, Sang-Joon Lee
No abstract is available for this record.