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Sheng Gao

Publications
26
Citations
604
Publications by Year
20132024
Co-Authors:
Show All Co-Authors (68)
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Sheng Gao

Affiliation

School of Information
Central University of Finance and Economics
Beijing, China

Publication Topics

Biography

Sheng Gao received the B.S. degree in information and computation science from the Xi’an University of Posts and Telecommunications, Xi’an, China, in 2009, and the Ph.D. degree in computer science and technology from Xidian University, Xi’an, in 2014.,He is currently an Associate Professor with the School of Information, Central University of Finance and Economics, Beijing, China. He has authored or coauthored more than five books and more than 40 papers in refereed international journals and conferences. His current research interests include blockchain, federated learning, data security, and privacy computing.(Based on document published on 3 September 2021).
Publications
26
Citations
604
Publications by Year
20132024
Co-Authors:
Show All Co-Authors (68)
Author's Published Works

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Location Privacy Preservation Crowdsensing with Federated Reinforcement Learning

Zhichao You;Xuewen Dong;Ximeng Liu;Sheng Gao;Yongzhi Wang;Yulong Shen

IEEE Transactions on Dependable and Secure Computing
Year: 2024 | Early Access Article |
Cited by: Papers (1)
Crowdsensing has become a popular method of sensing data collection while facing the problem of protecting participants' location privacy. Existing location-privacy crowdsensing mechanisms focus on static tasks and participants without considering sensing tasks' time requirements and participants' mobility, which cannot achieve satisfactory collected data quality and task completion in crowdsensin...Show More

Location Privacy Preservation Crowdsensing with Federated Reinforcement Learning

Zhichao You;Xuewen Dong;Ximeng Liu;Sheng Gao;Yongzhi Wang;Yulong Shen

Year: 2024 | Early Access Article |

Optimal Hub Placement and Deadlock-Free Routing for Payment Channel Network Scalability

Lingxiao Yang;Xuewen Dong;Sheng Gao;Qiang Qu;Xiaodong Zhang;Wensheng Tian;Yulong Shen

2023 IEEE 43rd International Conference on Distributed Computing Systems (ICDCS)
Year: 2023 | Conference Paper |
Cited by: Papers (4)
As a promising implementation model of payment channel network (PCN), payment channel hub (PCH) could achieve high throughput by providing stable off-chain transactions through powerful hubs. However, existing PCH schemes assume hubs are preplaced in advance, not considering payment requests' distribution and may affect network scalability, especially network load balancing. In addition, current s...Show More

Optimal Hub Placement and Deadlock-Free Routing for Payment Channel Network Scalability

Lingxiao Yang;Xuewen Dong;Sheng Gao;Qiang Qu;Xiaodong Zhang;Wensheng Tian;Yulong Shen

Year: 2023 | Conference Paper |

Ownership Tokenization and Incentive Design for Learning-based User-Generated Content

Qinnan Zhang;Zehui Xiong;Jianming Zhu;Sheng Gao;Wanting Yang;Dusit Niyato

2023 IEEE International Conference on Metaverse Computing, Networking and Applications (MetaCom)
Year: 2023 | Conference Paper |
The Metaverse is established by twining a practical world in a virtual form, where users could become creators of learning-based user-generated content (UGC). However, the digital assets are not owned by the creators, which deviates from the decentralized Metaverse based on blockchain in Web 3.0. The contribution incentive design for UGC still faces the challenges of ownership verification and pri...Show More

Ownership Tokenization and Incentive Design for Learning-based User-Generated Content

Qinnan Zhang;Zehui Xiong;Jianming Zhu;Sheng Gao;Wanting Yang;Dusit Niyato

Year: 2023 | Conference Paper |

VulHunter: Hunting Vulnerable Smart Contracts at EVM Bytecode-Level via Multiple Instance Learning

Zhaoxuan Li;Siqi Lu;Rui Zhang;Ziming Zhao;Rujin Liang;Rui Xue;Wenhao Li;Fan Zhang;Sheng Gao

IEEE Transactions on Software Engineering
Year: 2023 | Volume: 49, Issue: 11 | Journal Article |
Cited by: Papers (4)
With the economic development of Ethereum, the frequent security incidents involving smart contracts running on this platform have caused billions of dollars in losses. Consequently, there is a pressing need to identify the vulnerabilities in contracts, while the state-of-the-art (SOTA) detection methods have been limited in this regard as they cannot overcome three challenges at the same time. (i...Show More

VulHunter: Hunting Vulnerable Smart Contracts at EVM Bytecode-Level via Multiple Instance Learning

Zhaoxuan Li;Siqi Lu;Rui Zhang;Ziming Zhao;Rujin Liang;Rui Xue;Wenhao Li;Fan Zhang;Sheng Gao

Year: 2023 | Volume: 49, Issue: 11 | Journal Article |

VCD-FL: Verifiable, Collusion-Resistant, and Dynamic Federated Learning

Sheng Gao;Jingjie Luo;Jianming Zhu;Xuewen Dong;Weisong Shi

IEEE Transactions on Information Forensics and Security
Year: 2023 | Volume: 18 | Journal Article |
Cited by: Papers (6)
Federated learning (FL) is essentially a distributed machine learning paradigm that enables the joint training of a global model by aggregating gradients from participating clients without exchanging raw data. However, a malicious aggregation server may deliberately return designed results without any operation to save computation overhead, or even launch privacy inference attacks using crafted gr...Show More

VCD-FL: Verifiable, Collusion-Resistant, and Dynamic Federated Learning

Sheng Gao;Jingjie Luo;Jianming Zhu;Xuewen Dong;Weisong Shi

Year: 2023 | Volume: 18 | Journal Article |

Distributed Attribute-Based Signature With Attribute Dynamic Update for Smart Grid

Qianqian Su;Rui Zhang;Rui Xue;You Sun;Sheng Gao

IEEE Transactions on Industrial Informatics
Year: 2023 | Volume: 19, Issue: 9 | Journal Article |
Cited by: Papers (16)
Smart grid is gaining more and more attention as one of the typical applications of Internet of Things. However, in a distributed environment, how to guarantee the privacy of users in electricity trading while ensuring the efficiency of the transactions is one of the urgent issues to be solved. In this article, we propose a distributed attribute-based signature (DABS) scheme for distributed electr...Show More

Distributed Attribute-Based Signature With Attribute Dynamic Update for Smart Grid

Qianqian Su;Rui Zhang;Rui Xue;You Sun;Sheng Gao

Year: 2023 | Volume: 19, Issue: 9 | Journal Article |

BPMS: Blockchain-Based Privacy-Preserving Multi-Keyword Search in Multi-Owner Setting

Sheng Gao;Yuqi Chen;Jianming Zhu;Zhiyuan Sui;Rui Zhang;Xindi Ma

IEEE Transactions on Cloud Computing
Year: 2023 | Volume: 11, Issue: 3 | Journal Article |
Cited by: Papers (9)
Searchable encryption (SE) has emerged as a cryptographic primitive that allows data users to search on encrypted data. Most existing SE schemes usually delegate search operations to an intermediary such as a cloud server, which would inevitably result in single-point failure, privacy leakage, and even untrustworthy results. Several blockchain-based SE schemes have been proposed to alleviate these...Show More

BPMS: Blockchain-Based Privacy-Preserving Multi-Keyword Search in Multi-Owner Setting

Sheng Gao;Yuqi Chen;Jianming Zhu;Zhiyuan Sui;Rui Zhang;Xindi Ma

Year: 2023 | Volume: 11, Issue: 3 | Journal Article |

Self-Anomaly-Detection Model Training via Initialized Meta Model

Xindi MA;Cunzhu SU;Jianfeng MA;Qi JIANG;Ning XI;Sheng Gao;Kang XIE

2022 International Conference on Networking and Network Applications (NaNA)
Year: 2022 | Conference Paper |
Cited by: Papers (1)
Anomaly detection has become a key challenge affecting the training accuracy of machine learning. Because the training data is usually collected from Internet, many noised samples will be captured and these samples can decrease the model training accuracy. However, because the abnormal samples are difficult to predict when the samples are collected, and the training samples collected may contain m...Show More

Self-Anomaly-Detection Model Training via Initialized Meta Model

Xindi MA;Cunzhu SU;Jianfeng MA;Qi JIANG;Ning XI;Sheng Gao;Kang XIE

Year: 2022 | Conference Paper |

NOSnoop: An Effective Collaborative Meta-Learning Scheme Against Property Inference Attack

Xindi Ma;Baopu Li;Qi Jiang;Yimin Chen;Sheng Gao;Jianfeng Ma

IEEE Internet of Things Journal
Year: 2022 | Volume: 9, Issue: 9 | Journal Article |
Cited by: Papers (9)
Collaborative learning has been used to train a joint model on geographically diverse data through periodically sharing knowledge. Although participants keep the data locally in collaborative learning, the adversary can still launch inference attacks through participants’ shared information. In this article, we focus on the property inference attack during model training and design a novel defense...Show More

NOSnoop: An Effective Collaborative Meta-Learning Scheme Against Property Inference Attack

Xindi Ma;Baopu Li;Qi Jiang;Yimin Chen;Sheng Gao;Jianfeng Ma

Year: 2022 | Volume: 9, Issue: 9 | Journal Article |

Optimizing Task Location Privacy in Mobile Crowdsensing Systems

Xuewen Dong;Wen Zhang;Yushu Zhang;Zhichao You;Sheng Gao;Yulong Shen;Chao Wang

IEEE Transactions on Industrial Informatics
Year: 2022 | Volume: 18, Issue: 4 | Journal Article |
Cited by: Papers (20)
The location information for tasks may expose sensitive information, which impedes the practical use of mobile crowdsensing in the industrial Internet. In this article, to our knowledge, we are the first to discuss the privacy protection of task locations and propose a codebook-based task allocation mechanism to protect it. Considering the cost of system utility caused by privacy protection techno...Show More

Optimizing Task Location Privacy in Mobile Crowdsensing Systems

Xuewen Dong;Wen Zhang;Yushu Zhang;Zhichao You;Sheng Gao;Yulong Shen;Chao Wang

Year: 2022 | Volume: 18, Issue: 4 | Journal Article |

TrustWorker: A Trustworthy and Privacy-Preserving Worker Selection Scheme for Blockchain-Based Crowdsensing

Sheng Gao;Xiuhua Chen;Jianming Zhu;Xuewen Dong;Jianfeng Ma

IEEE Transactions on Services Computing
Year: 2022 | Volume: 15, Issue: 6 | Journal Article |
Cited by: Papers (25)
Worker selection in crowdsensing plays an important role in the quality control of sensing services. The majority of existing studies on worker selection were largely dependent on a trusted centralized server, which might suffer from single point of failure, the lack of transparency and so on. Some works recently proposed blockchain-based crowdsensing, which utilized reputation values stored on bl...Show More

TrustWorker: A Trustworthy and Privacy-Preserving Worker Selection Scheme for Blockchain-Based Crowdsensing

Sheng Gao;Xiuhua Chen;Jianming Zhu;Xuewen Dong;Jianfeng Ma

Year: 2022 | Volume: 15, Issue: 6 | Journal Article |

PDLM: Privacy-Preserving Deep Learning Model on Cloud with Multiple Keys

Xindi Ma;Jianfeng Ma;Hui Li;Qi Jiang;Sheng Gao

IEEE Transactions on Services Computing
Year: 2021 | Volume: 14, Issue: 4 | Journal Article |
Cited by: Papers (48)
Deep learning has aroused a lot of attention and has been used successfully in many domains, such as accurate image recognition and medical diagnosis. Generally, the training of models requires large, representative datasets, which may be collected from a large number of users and contain sensitive information (e.g., users’ photos and medical information). The collected data would be stored and co...Show More

PDLM: Privacy-Preserving Deep Learning Model on Cloud with Multiple Keys

Xindi Ma;Jianfeng Ma;Hui Li;Qi Jiang;Sheng Gao

Year: 2021 | Volume: 14, Issue: 4 | Journal Article |

Rational Delegation Learning Outsourcing Scheme Based on Game Theory

Kang Xiang;Youliang Tian;Sheng Gao;Changgen Peng;Weijie Tan

2020 International Conference on Networking and Network Applications (NaNA)
Year: 2020 | Conference Paper |
At present, many enterprises or individuals with a lot of data are limited by their own computing power, so can't mine useful information from the data. To address this problem, this paper proposes a rational delegation machine learning pattern. In the proposed pattern, we firstly construct a reliable game model, and then derive a formal model of rational delegation machine learning according to d...Show More

Rational Delegation Learning Outsourcing Scheme Based on Game Theory

Kang Xiang;Youliang Tian;Sheng Gao;Changgen Peng;Weijie Tan

Year: 2020 | Conference Paper |

Do Not Perturb Me: A Secure Byzantine-Robust Mechanism for Machine Learning in IoT

Xindi Ma;Junying Zhang;Jianfeng Ma;Qi Jiang;Sheng Gao;Kang Xie

2020 International Conference on Networking and Network Applications (NaNA)
Year: 2020 | Conference Paper |
Cited by: Papers (4)
With the development of Internet of Things (IoTs) and big data, collaborative machine learning has achieved many impressive successes in IoT to improve the system performance and provide more diversified services for people. Although one of the motivations for collaborative learning is privacy preservation, the adversary can still launch an inference attack through task nodes' shared information. ...Show More

Do Not Perturb Me: A Secure Byzantine-Robust Mechanism for Machine Learning in IoT

Xindi Ma;Junying Zhang;Jianfeng Ma;Qi Jiang;Sheng Gao;Kang Xie

Year: 2020 | Conference Paper |

Measurement and Analysis of Network Data Based on MQTT Protocol

Fu Chen;Yongfeng Huang;JianMing Zhu;Sheng Gao;Zhiyuan Sui;MeiJiao Duan

2020 IEEE 20th International Conference on Communication Technology (ICCT)
Year: 2020 | Conference Paper |
Cited by: Papers (1)
As a lightweight protocol, the Message Queuing Telemetry Transport (MQTT) is widely used in the scopes of Internet of Things on account of its quite low bandwidth requirements. We built a temperature and humidity monitoring system using the Raspberry Pi and NodeMcu to communicate with each other through the MQTT protocol. This work applies network analytics tools such as Wireshark to capture and a...Show More

Measurement and Analysis of Network Data Based on MQTT Protocol

Fu Chen;Yongfeng Huang;JianMing Zhu;Sheng Gao;Zhiyuan Sui;MeiJiao Duan

Year: 2020 | Conference Paper |

Cooperative Game Model of Delegation Computing: Verifier Separated from Calculators

Duo Zhang;Youliang Tian;Linjie Wang;Sheng Gao;Jianfeng Ma

IEEE INFOCOM 2020 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)
Year: 2020 | Conference Paper |
In cloud computing, the delegation computation service is required because end users usually are resource-constrained, and at the same time the correctness of computing results needs to be verified. However, all the existing and available technologies have a high cost to verify which is the main problem faced by the delegation computing under the cloud platform. In order to address this issue, bas...Show More

Cooperative Game Model of Delegation Computing: Verifier Separated from Calculators

Duo Zhang;Youliang Tian;Linjie Wang;Sheng Gao;Jianfeng Ma

Year: 2020 | Conference Paper |

A Truthful Online Incentive Mechanism for Nondeterministic Spectrum Allocation

Xuewen Dong;Zhichao You;Liangmin Wang;Sheng Gao;Yulong Shen;Jianfeng Ma

IEEE Transactions on Wireless Communications
Year: 2020 | Volume: 19, Issue: 7 | Journal Article |
Cited by: Papers (5)
Dynamic spectrum access (DSA) is a promising platform to solve the problem of spectrum shortage for which the most challenging issue is spectrum allocation under uncertain availability information, which is referred as a nondeterministic spectrum allocation problem. The nature of such a problem is due to inaccurate spectrum sensing results, which are induced by that power or energy based sensing c...Show More

A Truthful Online Incentive Mechanism for Nondeterministic Spectrum Allocation

Xuewen Dong;Zhichao You;Liangmin Wang;Sheng Gao;Yulong Shen;Jianfeng Ma

Year: 2020 | Volume: 19, Issue: 7 | Journal Article |

TrustAccess: A Trustworthy Secure Ciphertext-Policy and Attribute Hiding Access Control Scheme Based on Blockchain

Sheng Gao;Guirong Piao;Jianming Zhu;Xindi Ma;Jianfeng Ma

IEEE Transactions on Vehicular Technology
Year: 2020 | Volume: 69, Issue: 6 | Journal Article |
Cited by: Papers (98)
Ciphertext-policy attribute-based encryption (CP-ABE) is widely used in fine-grained access control to achieve the secure data sharing. However, most of the existing CP-ABE access control schemes involve intermediary entities, which might suffer from a high trust-building cost, single point of failure and so on. Due to the decentralization and transparency of blockchain, some blockchain-based acce...Show More

TrustAccess: A Trustworthy Secure Ciphertext-Policy and Attribute Hiding Access Control Scheme Based on Blockchain

Sheng Gao;Guirong Piao;Jianming Zhu;Xindi Ma;Jianfeng Ma

Year: 2020 | Volume: 69, Issue: 6 | Journal Article |

Permissioned Blockchain-Based Double-Layer Framework for Product Traceability System

Qingyang Ding;Sheng Gao;Jianming Zhu;Chongxuan Yuan

IEEE Access
Year: 2020 | Volume: 8 | Journal Article |
Cited by: Papers (48)
Blockchain-based product traceability systems are receiving increasing attention from both industry and academia. Existing systems make full use of the traceability and non-modification characteristics of blockchain technology and realize the openness and transparency of product traceability information in the entire supply chain. However, existing systems do not consider government regulation, ca...Show More

Permissioned Blockchain-Based Double-Layer Framework for Product Traceability System

Qingyang Ding;Sheng Gao;Jianming Zhu;Chongxuan Yuan

Year: 2020 | Volume: 8 | Journal Article |

EdgeToll: A Blockchain-based Toll Collection System for Public Sharing of Heterogeneous Edges

Bowen Xiao;Xiaoyi Fan;Sheng Gao;Wei Cai

IEEE INFOCOM 2019 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)
Year: 2019 | Conference Paper |
Cited by: Papers (1)
Edge computing is a novel paradigm designed to improve the quality of service for latency sensitive cloud applications. However, the state-of-the-art edge services are designed for specific applications, which are isolated from each other. To better improve the utilization level of edge nodes, public resource sharing among edges from distinct service providers should be encouraged economically. In...Show More

EdgeToll: A Blockchain-based Toll Collection System for Public Sharing of Heterogeneous Edges

Bowen Xiao;Xiaoyi Fan;Sheng Gao;Wei Cai

Year: 2019 | Conference Paper |

T-PBFT: An EigenTrust-based practical Byzantine fault tolerance consensus algorithm

Sheng Gao;Tianyu Yu;Jianming Zhu;Wei Cai

China Communications
Year: 2019 | Volume: 16, Issue: 12 | Magazine Article |
Cited by: Papers (140)
Blockchain with these characteristics of decentralized structure, transparent and credible, time-series and immutability, has been considering as a promising technology. Consensus algorithm as one of the core techniques of blockchain directly affects the scalability of blockchain systems. Existing probabilistic finality blockchain consensus algorithms such as PoW, PoS, suffer from power consumptio...Show More

T-PBFT: An EigenTrust-based practical Byzantine fault tolerance consensus algorithm

Sheng Gao;Tianyu Yu;Jianming Zhu;Wei Cai

Year: 2019 | Volume: 16, Issue: 12 | Magazine Article |

CPS Information Security Risk Evaluation System Based on Petri Net

Yonggui Fu;Jianming Zhu;Sheng Gao

2017 IEEE Second International Conference on Data Science in Cyberspace (DSC)
Year: 2017 | Conference Paper |
Cited by: Papers (8)
Cyber Physical Systems(CPS) have achieved attention, research and applications from the governments, academic circles, industry circles of domestic and foreign, so, CPS have become an important content of China's two modernizations' deeply integration in future. Using Petri net model to describe CPS information security risk evaluation process. Colligating Petri net model analysis results and CPS ...Show More

CPS Information Security Risk Evaluation System Based on Petri Net

Yonggui Fu;Jianming Zhu;Sheng Gao

Year: 2017 | Conference Paper |

RTRC: a reputation-based incentive game model for trustworthy crowdsourcing service

Xindi Ma;Jianfeng Ma;Hui Li;Qi Jiang;Sheng Gao

China Communications
Year: 2016 | Volume: 13, Issue: 12 | Magazine Article |
Cited by: Papers (17)
The ubiquity of mobile devices have promoted the prosperity of mobile crowd systems, which recruit crowds to contribute their resources for performing tasks. Yet, due to the various resource consumption, the crowds may be reluctant to join and contribute information. Thus, the low participation level of crowds will be a hurdle that prevents the adoption of crowdsourcing. A critical challenge for t...Show More

RTRC: a reputation-based incentive game model for trustworthy crowdsourcing service

Xindi Ma;Jianfeng Ma;Hui Li;Qi Jiang;Sheng Gao

Year: 2016 | Volume: 13, Issue: 12 | Magazine Article |

Protection of location privacy in continuous LBSs against adversaries with background information

Ben Niu;Sheng Gao;Fenghua Li;Hui Li;Zongqing Lu

2016 International Conference on Computing, Networking and Communications (ICNC)
Year: 2016 | Conference Paper |
Cited by: Papers (18)
Privacy issues in continuous Location-Based Services (LBSs) have gained attractive attentions in literature over recent years. In this paper, we illustrate the limitations of existing work and define an entropy-based privacy metric to quantify the privacy degree based on a set of vital observations. To tackle the privacy issues, we propose an efficient privacy-preserving scheme, DUMMY-T, which aim...Show More

Protection of location privacy in continuous LBSs against adversaries with background information

Ben Niu;Sheng Gao;Fenghua Li;Hui Li;Zongqing Lu

Year: 2016 | Conference Paper |

A demand-aware location privacy protection scheme in continuous location-based services

Xinghua Li;Lingjuan Deng;Sheng Gao;Jianfeng Ma;Qingsong Yao

2014 International Conference on Connected Vehicles and Expo (ICCVE)
Year: 2014 | Conference Paper |
Cited by: Papers (1)
Location-based Services (LBSs) via mobile handled devices have been subject to major privacy concerns for users. Currently, most of the existing works concerning the continuous LBS queries mainly focus on users' privacy demands with little consideration of the service of quality (QoS). In this paper, we propose a Demand-Aware Location Protection scheme (DALP) for continuous LBS requests, allowing ...Show More

A demand-aware location privacy protection scheme in continuous location-based services

Xinghua Li;Lingjuan Deng;Sheng Gao;Jianfeng Ma;Qingsong Yao

Year: 2014 | Conference Paper |

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