Luca Caviglione

2.5k citations
114 papers · 1.5k indexed · h-index 21

Luca Caviglione

109 papers receiving 1.4k citations

Peers

Luca Caviglione
Comparison fields: 5 of 79
  • Signal Processing 540
  • Computer Networks and Communications 854
  • Artificial Intelligence 598
  • Information Systems 417
  • Computer Vision and Pattern Recognition 368
Replace Giovanni Russello with:
Giovanni Russello New Zealand
Yanbin Sun China
Chunfu Jia China
Pavel Čeleda Czechia
Shingo Yamaguchi Japan
Mohammad Alizadeh United States
Arcangelo Castiglione Italy
Carol Fung United States
Deborah Frincke United States
Jorge Bernal Bernabé Spain
Luca Caviglione relative to Giovanni Russello New Zealand Giovanni Russello's profile →
Citations per field
00.5×1.5×2.1×
Giovanni Russello · 1×
Citations per year

Countries citing papers authored by Luca Caviglione

Since Specialization
Citations

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

Fields of papers citing papers by Luca Caviglione

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Luca Caviglione, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Luca Caviglione Line = papers co-authored together Luca Caviglione links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20241
4 20232
5 20230
6 20233
7 20234
8 20223
9 20219
10 202015
11 202082
12 202020
13 20186
14 201860
15 20186
16 20164
17 201124
18
Design and performance evaluation of a content distribution overlay optimized for streaming
20091
19 20096
20
Design and preliminary analysis of a framework for integrating real and virtual instrumentation within a grid infrastructure
20062

About Luca Caviglione

Luca Caviglione is a scholar working on Signal Processing, Computer Networks and Communications and Information Systems, having authored 114 papers that have together received 1.5k indexed citations. Recurring topics across this work include Advanced Malware Detection Techniques (42 papers), Internet Traffic Analysis and Secure E-voting (33 papers), Network Security and Intrusion Detection (25 papers), Caching and Content Delivery (22 papers), Peer-to-Peer Network Technologies (19 papers), Advanced Steganography and Watermarking Techniques (17 papers), Distributed and Parallel Computing Systems (11 papers) and Cloud Computing and Resource Management (9 papers). The work is most often cited by research in Signal Processing (540 citations), Computer Networks and Communications (854 citations) and Artificial Intelligence (598 citations). Luca Caviglione has collaborated with scholars based in Italy, Poland and Germany. Frequent co-authors include Wojciech Mazurczyk, Mauro Gaggero, Steffen Wendzel, Alessio Merlo, Mauro Migliardi, Mauro Coccoli, Jean-François Lalande, Alberto Gotta, Manlio Bacco and Andrea Berton. Their work appears in journals such as IEEE Security & Privacy, Computer Communications, IEEE Communications Letters, IEEE Access and International Journal of Satellite Communications and Networking.

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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