Keke Gai

10.6k total citations · 7 hit papers
189 papers, 6.8k citations indexed

About

Keke Gai is a scholar working on Information Systems, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Keke Gai has authored 189 papers receiving a total of 6.8k indexed citations (citations by other indexed papers that have themselves been cited), including 125 papers in Information Systems, 78 papers in Computer Networks and Communications and 73 papers in Artificial Intelligence. Recurrent topics in Keke Gai's work include Blockchain Technology Applications and Security (64 papers), Big Data and Digital Economy (52 papers) and IoT and Edge/Fog Computing (51 papers). Keke Gai is often cited by papers focused on Blockchain Technology Applications and Security (64 papers), Big Data and Digital Economy (52 papers) and IoT and Edge/Fog Computing (51 papers). Keke Gai collaborates with scholars based in China, United States and New Zealand. Keke Gai's co-authors include Meikang Qiu, Liehuang Zhu, Hui Zhao, Yulu Wu, Kim‐Kwang Raymond Choo, Xiaotong Sun, Lixin Tao, Ziliang Zong, Longfei Qiu and Meng Shen and has published in prestigious journals such as IEEE Communications Surveys & Tutorials, IEEE Access and IEEE Journal on Selected Areas in Communications.

In The Last Decade

Keke Gai

174 papers receiving 6.6k citations

Hit Papers

Privacy-Preserving Energy Trading Using Consortium Bloc... 2015 2026 2018 2022 2019 2015 2017 2019 2015 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Privacy-Preserving Energy Trading Using Consortium Blockchain in Smart Grid
    2019 418 citations Keke Gai, Liehuang Zhu et al. IEEE Transactions on Industrial Informatics profile →
  2. Dynamic energy-aware cloudlet-based mobile cloud computing model for green computing
    2015 364 citations Keke Gai et al. profile →
  3. A survey on FinTech
    2017 322 citations Keke Gai et al. profile →
  4. Permissioned Blockchain and Edge Computing Empowered Privacy-Preserving Smart Grid Networks
    2019 288 citations Keke Gai, Liehuang Zhu et al. IEEE Internet of Things Journal profile →
  5. Phase-Change Memory Optimization for Green Cloud with Genetic Algorithm
    2015 267 citations Keke Gai et al. profile →
  6. Blockchain Meets Cloud Computing: A Survey
    2020 245 citations Keke Gai, Liehuang Zhu et al. profile →
  7. Controllable and trustworthy blockchain-based cloud data management
    2018 207 citations Liehuang Zhu, Keke Gai et al. profile →

Peers

Keke Gai
Changjun Jiang China
Hans‐Arno Jacobsen Canada
Mohammad Wazid India
Jemal Abawajy Australia
Shancang Li United Kingdom
Wanchun Dou China
Antonio Puliafito Italy
Yaser Jararweh Jordan
Jong Hyuk Park South Korea
Elaine Shi United States
Changjun Jiang China
Keke Gai
Citations per year, relative to Keke Gai Keke Gai (= 1×) peers Changjun Jiang

Countries citing papers authored by Keke Gai

Since Specialization
Citations

This map shows the geographic impact of Keke Gai's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Keke Gai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Keke Gai more than expected).

Fields of papers citing papers by Keke Gai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Keke Gai. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Keke Gai. The network helps show where Keke Gai may publish in the future.

Co-authorship network of co-authors of Keke Gai

This figure shows the co-authorship network connecting the top 25 collaborators of Keke Gai. A scholar is included among the top collaborators of Keke Gai based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Keke Gai. Keke Gai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Gai, Keke, et al.. (2025). Blockchain-Assisted Searchable Integrity Auditing for Large-Scale Similarity Data With Arbitration. IEEE Transactions on Dependable and Secure Computing. 22(6). 6012–6027. 1 indexed citations
2.
Gai, Keke, et al.. (2025). Blockchain-Based Privacy-Enhancing Federated Learning in Smart Healthcare: A Survey. 3(1). 1–1. 6 indexed citations
3.
Ding, Kai, Keke Gai, Chi‐Un Lei, et al.. (2025). Verifiable decentralized identity-based meta-computing in Industrial Internet of Things (IIoT). Journal of Systems Architecture. 162. 103391–103391.
4.
Gai, Keke, et al.. (2025). MUFTI: Multi-Domain Distillation-Based Heterogeneous Federated Continuous Learning. IEEE Transactions on Information Forensics and Security. 20. 2721–2733. 4 indexed citations
5.
Dai, Xiaohai, et al.. (2025). Lasagne: A Suite of High-Profit Arbitrage Strategies for Blockchain-Based Decentralized Exchanges. IEEE Transactions on Computational Social Systems. 12(6). 4456–4468.
6.
Gai, Keke, et al.. (2025). Blockchain-Assisted Self-Sovereign Identities on Education: A Survey. 3(1). 3–3. 4 indexed citations
7.
Gai, Keke, et al.. (2025). A Scheme of Robust Privacy-Preserving Multi-Party Computation via Public Verification. IEEE Transactions on Dependable and Secure Computing. 22(5). 4896–4910. 2 indexed citations
8.
Gai, Keke, et al.. (2025). CAPE: Commitment-Based Privacy-Preserving Payment Channel Scheme in Blockchain. IEEE Transactions on Dependable and Secure Computing. 22(4). 3977–3992. 3 indexed citations
9.
Zhu, Liehuang, et al.. (2024). Zk-SNARKs-Based Anonymous Payment Channel in Blockchain. 2(1). 20–39. 3 indexed citations
10.
Gai, Keke, et al.. (2024). Decision Tree-Based Federated Learning: A Survey. 2(1). 40–60. 4 indexed citations
11.
Gai, Keke, et al.. (2024). Blockchain-Empowered Keyword Searchable Provable Data Possession for Large Similar Data. IEEE Transactions on Information Forensics and Security. 20. 1374–1389. 8 indexed citations
12.
Zhu, Jun, et al.. (2024). Lightweight Privacy-Preserving Mechanisms for Cross-Chain Transactions. 59–64. 2 indexed citations
13.
14.
Gao, Shang, et al.. (2024). SAMCU: Secure and Anonymous Multi-Channel Updates in Payment Channel Networks. IEEE Transactions on Information Forensics and Security. 19. 9115–9128. 2 indexed citations
15.
Wang, Shuo, et al.. (2024). LRPAFL: Layer-Wise Relevance Propagation-Based Adaptive Federated Learning. 174–179. 1 indexed citations
16.
17.
Wang, Shuo, Keke Gai, Jing Yu, et al.. (2024). RAFLS: RDP-Based Adaptive Federated Learning With Shuffle Model. IEEE Transactions on Dependable and Secure Computing. 22(2). 1181–1194. 6 indexed citations
18.
Gai, Keke, et al.. (2024). Trustworthy Access Control for Multiaccess Edge Computing in Blockchain-Assisted 6G Systems. IEEE Transactions on Industrial Informatics. 20(5). 7732–7743. 8 indexed citations
19.
Wu, Tong, Weijie Wang, Chuan Zhang, et al.. (2022). Blockchain-Based Anonymous Data Sharing With Accountability for Internet of Things. IEEE Internet of Things Journal. 10(6). 5461–5475. 25 indexed citations
20.
Liang, Kun, et al.. (2017). Cloud-Based Adaptive Particle Swarm Optimization for Waveband Selection in Big Data. Journal of Signal Processing Systems. 90(8-9). 1105–1113. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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