13 citations · 31 across the 24 of their papers we have counts for
25 papers
UNBIND: UNlearning By INference-time Directional Steering for Code LLMs
Zhengyang Shan, Jiayun Xin, Yanjun Lin +7
Code large language models acquire programming capabilities from large code corpora, but can also memorize implementations that later require removal. Code unlearning is needed to…
Low Rank Comes with Low Security: Gradient Assembly Poisoning Attacks against Distributed LoRA-based LLM Systems
Yueyan Dong, Minghui Xu, Qin Hu +5
Low-Rank Adaptation (LoRA) has become a popular solution for fine-tuning large language models (LLMs) in federated settings, dramatically reducing update costs by introducing train…
Unveiling Malware Patterns: A Self-analysis Perspective
Fangtian Zhong, Qin Hu, Yili Jiang +2
The widespread usage of Microsoft Windows has unfortunately led to a surge in malware, posing a serious threat to the security and privacy of millions of users. In response, the re…
FileDES: A Secure Scalable and Succinct Decentralized Encrypted Storage Network
Minghui Xu, Jiahao Zhang, Hechuan Guo +5
Decentralized Storage Network (DSN) is an emerging technology that challenges traditional cloud-based storage systems by consolidating storage capacities from independent providers…
An Adaptive and Modular Blockchain Enabled Architecture for a Decentralized Metaverse
Ye Cheng, Yihao Guo, Minghui Xu +3
A metaverse breaks the boundaries of time and space between people, realizing a more realistic virtual experience, improving work efficiency, and creating a new business model. Blo…
Exploring Blockchain Technology through a Modular Lens: A Survey
Minghui Xu, Yihao Guo, Chunchi Liu +5
Blockchain has attracted significant attention in recent years due to its potential to revolutionize various industries by providing trustlessness. To comprehensively examine block…
Proof of User Similarity: the Spatial Measurer of Blockchain
Shengling Wang, Lina Shi, Hongwei Shi +3
Although proof of work (PoW) consensus dominates the current blockchain-based systems mostly, it has always been criticized for the uneconomic brute-force calculation. As alternati…
A Trustless Architecture of Blockchain-enabled Metaverse
Minghui Xu, Yihao Guo, Qin Hu +3
Metaverse has rekindled human beings' desire to further break space-time barriers by fusing the virtual and real worlds. However, security and privacy threats hinder us from buildi…
Active Defense Analysis of Blockchain Forking through the Spatial-Temporal Lens
Shengling Wang, Ying Wang, Hongwei Shi +1
Forking breaches the security and performance of blockchain as it is symptomatic of distributed consensus, spurring wide interest in analyzing and resolving it. The state-of-the-ar…
zk-PCN: A Privacy-Preserving Payment Channel Network Using zk-SNARKs
Wenxuan Yu, Minghui Xu, Dongxiao Yu +3
Payment channel network (PCN) is a layer-two scaling solution that enables fast off-chain transactions but does not involve on-chain transaction settlement. PCNs raise new privacy…
Sync or Fork: Node-Level Synchronization Analysis of Blockchain
Qin Hu, Minghui Xu, Shengling Wang +1
As the cornerstone of blockchain, block synchronization plays a vital role in maintaining the security. Without full blockchain synchronization, unexpected forks will emerge and th…
Solving the Federated Edge Learning Participation Dilemma: A Truthful and Correlated Perspective
Qin Hu, Feng Li, Xukai Zou +1
An emerging computational paradigm, named federated edge learning (FEL), enables intelligent computing at the network edge with the feature of preserving data privacy for edge devi…
Online Learning for Failure-aware Edge Backup of Service Function Chains with the Minimum Latency
Chen Wang, Qin Hu, Dongxiao Yu +1
Virtual network functions (VNFs) have been widely deployed in mobile edge computing (MEC) to flexibly and efficiently serve end users running resource-intensive applications, which…
SPDL: Blockchain-secured and Privacy-preserving Decentralized Learning
Minghui Xu, Zongrui Zou, Ye Cheng +3
Decentralized learning involves training machine learning models over remote mobile devices, edge servers, or cloud servers while keeping data localized. Even though many studies h…
Blockchain and Federated Edge Learning for Privacy-Preserving Mobile Crowdsensing
Qin Hu, Zhilin Wang, Minghui Xu +1
Mobile crowdsensing (MCS) counting on the mobility of massive workers helps the requestor accomplish various sensing tasks with more flexibility and lower cost. However, for the co…
Nothing Wasted: Full Contribution Enforcement in Federated Edge Learning
Qin Hu, Shengling Wang, Zeihui Xiong +1
The explosive amount of data generated at the network edge makes mobile edge computing an essential technology to support real-time applications, calling for powerful data processi…
Machine Learning Enhanced Blockchain Consensus with Transaction Prioritization for Smart Cities
S. Valli Sanghami, John J. Lee, Qin Hu
In the given technology-driven era, smart cities are the next frontier of technology, aiming at improving the quality of people's lives. Many research works focus on future smart c…
Micro Analysis of Natural Forking in Blockchain Based on Large Deviation Theory
Hongwei Shi, Shengling Wang, Qin Hu +1
Natural forking in blockchain refers to a phenomenon that there are a set of blocks at one block height at the same time, implying that various nodes have different perspectives of…
Cap the Gap: Solving the Egoistic Dilemma under the Transaction Fee-Incentive Bitcoin
Hongwei Shi, Shengling Wang, Qin Hu +2
Bitcoin has witnessed a prevailing transition that employing transaction fees paid by users rather than subsidy assigned by the system as the main incentive for mining.
Privacy-aware Data Trading
Shengling Wang, Lina Shi, Junshan Zhang +2
The growing threat of personal data breach in data trading pinpoints an urgent need to develop countermeasures for preserving individual privacy. The state-of-the-art work either e…
A Misreport- and Collusion-Proof Crowdsourcing Mechanism without Quality Verification
Kun Li, Shengling Wang, Xiuzhen Cheng +1
Quality control plays a critical role in crowdsourcing. The state-of-the-art work is not suitable for large-scale crowdsourcing applications, since it is a long haul for the reques…
Egoistic Incentives Based on Zero-Determinant Alliances for Large-Scale Systems
Shengling Wang, Peizi Ma, Qin Hu +2
Social dilemmas exist in various fields and give rise to the so-called free-riding problem, leading to collective fiascos. The difficulty of tracking individual behaviors makes ego…
Proof of Federated Learning: A Novel Energy-recycling Consensus Algorithm
Xidi Qu, Shengling Wang, Qin Hu +1
Proof of work (PoW), the most popular consensus mechanism for Blockchain, requires ridiculously large amounts of energy but without any useful outcome beyond determining accounting…
An Uncertainty- and Collusion-Proof Voting Consensus Mechanism in Blockchain
Shengling Wang, Xidi Qu, Qin Hu +1
Though voting-based consensus algorithms in Blockchain outperform proof-based ones in energy- and transaction-efficiency, they are prone to incur wrong elections and bribery electi…