Jing Long

1.4k total citations
24 papers, 1.0k citations indexed

About

Jing Long is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Jing Long has authored 24 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 10 papers in Computer Networks and Communications and 9 papers in Artificial Intelligence. Recurrent topics in Jing Long's work include Advanced Steganography and Watermarking Techniques (7 papers), Network Security and Intrusion Detection (6 papers) and Physical Unclonable Functions (PUFs) and Hardware Security (5 papers). Jing Long is often cited by papers focused on Advanced Steganography and Watermarking Techniques (7 papers), Network Security and Intrusion Detection (6 papers) and Physical Unclonable Functions (PUFs) and Hardware Security (5 papers). Jing Long collaborates with scholars based in China, Taiwan and United States. Jing Long's co-authors include Kuan‐Ching Li, Wei Liang, Xinpeng Zhang, Hang Cheng, Zichi Wang, Dafang Zhang, Mingdong Tang, Albert Y. Zomaya, Xiaoyan Kui and Xin Peng and has published in prestigious journals such as IEEE Access, Information Sciences and IEEE Transactions on Industrial Informatics.

In The Last Decade

Jing Long

21 papers receiving 965 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jing Long China 10 410 373 332 307 136 24 1.0k
Ruhui Ma China 19 458 1.1× 446 1.2× 286 0.9× 540 1.8× 102 0.8× 104 1.3k
Bassam J. Mohd Jordan 19 492 1.2× 307 0.8× 343 1.0× 380 1.2× 176 1.3× 54 1.1k
Tongqing Zhou China 18 346 0.8× 208 0.6× 275 0.8× 391 1.3× 173 1.3× 74 1.0k
Zaid Ameen Abduljabbar Iraq 20 405 1.0× 401 1.1× 263 0.8× 359 1.2× 140 1.0× 95 1.0k
Kaiyuan Zhang China 14 545 1.3× 319 0.9× 245 0.7× 318 1.0× 261 1.9× 30 978
Muhammad Nadzir Marsono Malaysia 18 675 1.6× 258 0.7× 115 0.3× 409 1.3× 215 1.6× 129 1.1k
L.M. Patnaik India 13 405 1.0× 217 0.6× 126 0.4× 206 0.7× 160 1.2× 95 814
Étienne Rivière Switzerland 15 1.1k 2.7× 471 1.3× 205 0.6× 252 0.8× 168 1.2× 75 1.4k

Countries citing papers authored by Jing Long

Since Specialization
Citations

This map shows the geographic impact of Jing Long'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 Jing Long with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jing Long more than expected).

Fields of papers citing papers by Jing Long

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jing Long. 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 Jing Long. The network helps show where Jing Long may publish in the future.

Co-authorship network of co-authors of Jing Long

This figure shows the co-authorship network connecting the top 25 collaborators of Jing Long. A scholar is included among the top collaborators of Jing Long 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 Jing Long. Jing Long 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.
Long, Jing, et al.. (2025). Auxiliary Discrminator Sequence Generative Adversarial Networks for Few Sample Molecule Generation. Journal of Chemical Information and Modeling. 65(19). 10311–10322.
2.
Fu, Wei, W. C. Zhang, Jing Long, Gautam Srivastava, & Shuai Liu. (2025). Global context-aware attention model for weakly-supervised temporal action localization. Alexandria Engineering Journal. 127. 43–55.
3.
Liu, Y. J., Lijun Xiao, Dezhi Han, & Jing Long. (2023). Telematics Communication Based on Blockchain Technology. 27. 136–141. 1 indexed citations
4.
Long, Jing, Cuiting Luo, Ruxin Chen, Jianping Yu, & Kuan‐Ching Li. (2023). A cross-layered cluster embedding learning network with regularization for multivariate time series anomaly detection. The Journal of Supercomputing. 80(8). 10444–10468. 1 indexed citations
5.
Long, Jing, Cuiting Luo, & Ruxin Chen. (2023). Multivariate Time Series Anomaly Detection with Improved Encoder-Decoder Based Model. 36. 161–166. 1 indexed citations
6.
Long, Jing, et al.. (2022). A Regularized Cross-Layer Ladder Network for Intrusion Detection in Industrial Internet of Things. IEEE Transactions on Industrial Informatics. 19(2). 1747–1755. 52 indexed citations
7.
Long, Jing, Fei Fang, & Haibo Luo. (2021). A Survey of Machine Learning-based IoT Intrusion Detection Techniques. 7–12. 2 indexed citations
8.
Liang, Wei, Weihong Huang, Jing Long, et al.. (2020). Deep Reinforcement Learning for Resource Protection and Real-Time Detection in IoT Environment. IEEE Internet of Things Journal. 7(7). 6392–6401. 143 indexed citations
9.
Xiao, Lijun, et al.. (2020). Secure Digital Certificate-Based Data Access Control Scheme in Blockchain. IEEE Access. 8. 91751–91760. 24 indexed citations
10.
Liang, Wei, et al.. (2020). A Fast Defogging Image Recognition Algorithm Based on Bilateral Hybrid Filtering. ACM Transactions on Multimedia Computing Communications and Applications. 17(2). 1–16. 88 indexed citations
11.
Liang, Wei, Songyou Xie, Jing Long, et al.. (2019). A double PUF-based RFID identity authentication protocol in service-centric internet of things environments. Information Sciences. 503. 129–147. 81 indexed citations
12.
Liang, Wei, Kuan‐Ching Li, Jing Long, Xiaoyan Kui, & Albert Y. Zomaya. (2019). An Industrial Network Intrusion Detection Algorithm Based on Multifeature Data Clustering Optimization Model. IEEE Transactions on Industrial Informatics. 16(3). 2063–2071. 154 indexed citations
13.
Liang, Wei, Jing Long, Xia Lei, et al.. (2019). Efficient data packet transmission algorithm for IPV6 mobile vehicle network based on fast switching model with time difference. Future Generation Computer Systems. 100. 132–143. 10 indexed citations
14.
Long, Jing, Wei Liang, Kuan‐Ching Li, et al.. (2019). PUF-Based Anonymous Authentication Scheme for Hardware Devices and IPs in Edge Computing Environment. IEEE Access. 7. 124785–124796. 23 indexed citations
15.
Long, Jing, Dafang Zhang, Chen Zuo, Jiajun Duan, & Weihong Huang. (2016). A robust low-overhead watermarking for field authentication of intellectual property cores. Computer Science and Information Systems. 13(2). 609–622. 7 indexed citations
16.
Long, Jing, et al.. (2016). Rotation Based Reversible Data Hiding for JPEG Images. IETE Technical Review. 33(6). 607–614. 7 indexed citations
17.
Zhang, Xinpeng, Jing Long, Zichi Wang, & Hang Cheng. (2015). Lossless and Reversible Data Hiding in Encrypted Images With Public-Key Cryptography. IEEE Transactions on Circuits and Systems for Video Technology. 26(9). 1622–1631. 217 indexed citations
18.
Liang, Wei, Jianbo Xu, & Jing Long. (2011). A High-capacity Lossless Algorithm for Watermarking Binary Images. 3(4). 229–236. 1 indexed citations
19.
Liang, Wei & Jing Long. (2010). A cryptographic algorithm based on Linear Feedback Shift Register. 6. V15–526. 2 indexed citations
20.
Xu, Jianbo, et al.. (2010). Mobile Sink-Based Data Gathering Protocol. 427–430. 4 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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