Antonio Pecchia

1.3k total citations
62 papers, 821 citations indexed

About

Antonio Pecchia is a scholar working on Computer Networks and Communications, Artificial Intelligence and Information Systems. According to data from OpenAlex, Antonio Pecchia has authored 62 papers receiving a total of 821 indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Computer Networks and Communications, 32 papers in Artificial Intelligence and 19 papers in Information Systems. Recurrent topics in Antonio Pecchia's work include Network Security and Intrusion Detection (33 papers), Software System Performance and Reliability (31 papers) and Software Reliability and Analysis Research (15 papers). Antonio Pecchia is often cited by papers focused on Network Security and Intrusion Detection (33 papers), Software System Performance and Reliability (31 papers) and Software Reliability and Analysis Research (15 papers). Antonio Pecchia collaborates with scholars based in Italy, Australia and United States. Antonio Pecchia's co-authors include Marcello Cinque, Domenico Cotroneo, Umberto Villano, Marta Catillo, Stefano Russo, Zbigniew Kalbarczyk, Ravishankar K. Iyer, Roberto Natella, Andrea Paudice and Santonu Sarkar and has published in prestigious journals such as Expert Systems with Applications, IEEE Transactions on Software Engineering and IEEE Transactions on Industrial Informatics.

In The Last Decade

Antonio Pecchia

56 papers receiving 785 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Antonio Pecchia Italy 17 694 385 317 159 155 62 821
Kenji Yoshihira United States 18 779 1.1× 317 0.8× 502 1.6× 78 0.5× 110 0.7× 45 936
Yosr Jarraya Canada 13 469 0.7× 207 0.5× 228 0.7× 44 0.3× 70 0.5× 47 673
Sagar Chaki United States 17 416 0.6× 580 1.5× 381 1.2× 230 1.4× 465 3.0× 69 1.2k
Antonio Filieri Germany 18 475 0.7× 532 1.4× 442 1.4× 45 0.3× 418 2.7× 47 943
Fabrizio Baiardi Italy 12 397 0.6× 221 0.6× 273 0.9× 171 1.1× 28 0.2× 74 620
Panagiotis Katsaros Greece 13 210 0.3× 195 0.5× 196 0.6× 40 0.3× 103 0.7× 65 461
René Rydhof Hansen Denmark 13 255 0.4× 224 0.6× 235 0.7× 157 1.0× 170 1.1× 66 641
Altair O. Santin Brazil 17 622 0.9× 469 1.2× 248 0.8× 343 2.2× 28 0.2× 85 875
Murali Chintalapati United States 11 693 1.0× 426 1.1× 287 0.9× 29 0.2× 131 0.8× 23 811
Fevzi Belli Germany 13 226 0.3× 142 0.4× 278 0.9× 73 0.5× 636 4.1× 99 733

Countries citing papers authored by Antonio Pecchia

Since Specialization
Citations

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

Fields of papers citing papers by Antonio Pecchia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Antonio Pecchia

This figure shows the co-authorship network connecting the top 25 collaborators of Antonio Pecchia. A scholar is included among the top collaborators of Antonio Pecchia 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 Antonio Pecchia. Antonio Pecchia 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.
Catillo, Marta, Antonio Pecchia, & Umberto Villano. (2025). MultiCIDS: Anomaly-based collective intrusion detection by deep learning on IoT/CPS multivariate time series. Internet of Things. 30. 101519–101519. 2 indexed citations
2.
Catillo, Marta, Antonio Pecchia, & Umberto Villano. (2025). USB-IDS-TC: A Flow-Based Intrusion Detection Dataset of DoS Attacks in Different Network Scenarios. 302–309.
3.
4.
Avella, Pasquale, et al.. (2025). Topic Modeling for Graph-Based Analysis of Fake News Diffusion. 1–6.
5.
6.
Catillo, Marta, Antonio Pecchia, & Umberto Villano. (2023). Machine Learning on Public Intrusion Datasets: Academic Hype or Concrete Advances in NIDS?. 132–136. 6 indexed citations
7.
Catillo, Marta, Antonio Pecchia, & Umberto Villano. (2023). A Deep Learning Method for Lightweight and Cross-Device IoT Botnet Detection. Applied Sciences. 13(2). 837–837. 28 indexed citations
8.
Catillo, Marta, et al.. (2022). Transferability of machine learning models learned from public intrusion detection datasets: the CICIDS2017 case study. Software Quality Journal. 30(4). 955–981. 26 indexed citations
9.
Catillo, Marta, Antonio Pecchia, & Umberto Villano. (2021). AutoLog: Anomaly detection by deep autoencoding of system logs. Expert Systems with Applications. 191. 116263–116263. 53 indexed citations
10.
Cotroneo, Domenico, Karthik Pattabiraman, & Antonio Pecchia. (2018). Guest Editors’ Introduction: Special Issue on Data-Driven Dependability and Security. IEEE Transactions on Dependable and Secure Computing. 15(6). 913–914. 1 indexed citations
11.
Cinque, Marcello, et al.. (2018). A framework for on-line timing error detection in software systems. Future Generation Computer Systems. 90. 521–538. 5 indexed citations
12.
Cinque, Marcello, Domenico Cotroneo, & Antonio Pecchia. (2018). Challenges and Directions in Security Information and Event Management (SIEM). 95–99. 33 indexed citations
13.
Cotroneo, Domenico, Andrea Paudice, & Antonio Pecchia. (2017). Empirical Analysis and Validation of Security Alerts Filtering Techniques. IEEE Transactions on Dependable and Secure Computing. 16(5). 856–870. 14 indexed citations
14.
Cinque, Marcello & Antonio Pecchia. (2017). On the injection of hardware faults in virtualized multicore systems. Journal of Parallel and Distributed Computing. 106. 50–61. 4 indexed citations
15.
Cinque, Marcello, Domenico Cotroneo, Antonio Pecchia, Roberto Pietrantuono, & Stefano Russo. (2017). Debugging‐workflow‐aware software reliability growth analysis. Software Testing Verification and Reliability. 27(7). 13 indexed citations
16.
Pietrantuono, Roberto, Pasqualina Potena, Antonio Pecchia, et al.. (2017). Multiobjective Testing Resource Allocation Under Uncertainty. IEEE Transactions on Evolutionary Computation. 22(3). 347–362. 13 indexed citations
17.
Pecchia, Antonio, et al.. (2015). Industry Practices and Event Logging: Assessment of a Critical Software Development Process. 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering. 169–178. 55 indexed citations
18.
Cinque, Marcello, et al.. (2014). Assessing Direct Monitoring Techniques to Analyze Failures of Critical Industrial Systems. 212–222. 16 indexed citations
19.
Cinque, Marcello, et al.. (2014). Event Logging in an Industrial Development Process: Practices and Reengineering Challenges. 10–13. 5 indexed citations
20.
Cinque, Marcello, Domenico Cotroneo, & Antonio Pecchia. (2012). Event Logs for the Analysis of Software Failures: A Rule-Based Approach. IEEE Transactions on Software Engineering. 39(6). 806–821. 84 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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