JaeSeung Song

96 papers receiving 2.2k citations

Hit Papers

A Survey on Emerging SDN and NFV Security Mechanisms for ...20182026202020232018100200300

Peers

JaeSeung Song
Comparison fields: 5 of 111
  • Computer Networks and Communications 1.5k
  • Electrical and Electronic Engineering 697
  • Information Systems 500
  • Computer Vision and Pattern Recognition 318
  • Artificial Intelligence 293
Replace Christos Stergiou with:
Christos Stergiou Greece
Wu Yang China
Muhammad Bilal South Korea
Claudio Savaglio Italy
Leonardo Mostarda Italy
Rasheed Hussain Russia
Li Zhu China
Stefan Schulte Austria
William G. Hatcher United States
Flávia C. Delicato Brazil
JaeSeung Song relative to Christos Stergiou Greece Christos Stergiou's profile →
Citations per field
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Christos Stergiou · 1×
Citations per year

Countries citing papers authored by JaeSeung Song

Since Specialization
Citations

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

Fields of papers citing papers by JaeSeung Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of JaeSeung Song

This figure shows the co-authorship network connecting the top 25 collaborators of JaeSeung Song. A scholar is included among the top collaborators of JaeSeung Song 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 JaeSeung Song. JaeSeung Song 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
#WorkIndexed citations
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2 10
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12 7
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14 39
15 42
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A Survey on Emerging SDN and NFV Security Mechanisms for IoT Systemsbreakdown →
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I've Got Your Number: - Harvesting Users' Personal Data via Contacts Sync for the KakaoTalk Messenger.
1

About JaeSeung Song

JaeSeung Song is a scholar working on Computer Networks and Communications, Software and Computer Vision and Pattern Recognition, having authored 103 papers that have together received 2.3k indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (59 papers), IoT Networks and Protocols (16 papers) and Software-Defined Networks and 5G (15 papers). The work is most often cited by research in Computer Networks and Communications (1.5k citations), Information Systems (500 citations) and Industrial and Manufacturing Engineering (181 citations). JaeSeung Song has collaborated with scholars based in South Korea, Finland and United Kingdom. Frequent co-authors include Tarik Taleb, Ivan Farris, Jae-Young Hwang, Guang Lu, Philip Jacobs, Hyoungshick Kim, Jaeho Kim, Konstantinos Samdanis, Nak-Myoung Sung and Martin Bauer. Their work appears in journals such as IEEE Communications Surveys & Tutorials, IEEE Access and IEEE Communications Magazine.

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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