Xinyi Huang
6 أوراق في مجموعة PaperMetrix
أوراق هذا المؤلف
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Understanding Human-Chosen PINs
2017
Personal Identification Numbers (PINs) are ubiquitously used in embedded computing systems where user input interfaces are constrained. Yet, little attention has been paid to this important kind of authentication credentials, especially for 6-digit PINs which …
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Privacy-Preserving Collaborative Model Learning: The Case of Word Vector Training
2018 · IEEE Transactions on Knowledge and Data Engineering
Nowadays, machine learning is becoming a new paradigm for mining hidden knowledge in big data. The collection and manipulation of big data not only create considerable values, but also raise serious privacy concerns. To protect …
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A Lattice-Based Redactable Signature Scheme using Cryptographic Accumulators for Trees
2022 · The Computer Journal
Abstract Redactable signatures allow the signature holder to remove admissible data blocks in the signed data while generating valid signatures about different redacted data without communicating with the primary signer. Now, this sort of signature …
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AADEC: Anonymous and Auditable Distributed Access Control for Edge Computing Services
2022 · IEEE Transactions on Information Forensics and Security
Edge computing is an emerging distributed computing concept that allows edge servers to provide authorized consumers with various on-demand services. Due to highly dynamic and untrustworthy network environments, various potential security concerns (e.g., unauthorized access, …
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Anonymity-Enhancing Multi-Hop Locks for Monero-Enabled Payment Channel Networks
2023 · IEEE Transactions on Information Forensics and Security
Payment Channel Networks (PCNs) are innovative second-layer scaling technologies that aim to improve transaction rates, reduce on-chain storage costs, and enable efficient atomic swaps for blockchain-based cryptocurrencies. Despite offering features like relationship anonymity, scriptless script, …
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Rethinking and Benchmarking Large Language Models for Graph Reasoning
2025 · arXiv (Cornell University)
Large Language Models (LLMs) for Graph Reasoning have been extensively studied over the past two years, involving enabling LLMs to understand graph structures and reason on graphs to solve various graph problems, with graph algorithm …