Massimo Guarascio

1.3k total citations
70 papers, 574 citations indexed

About

Massimo Guarascio is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Massimo Guarascio has authored 70 papers receiving a total of 574 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Artificial Intelligence, 22 papers in Information Systems and 18 papers in Computer Networks and Communications. Recurrent topics in Massimo Guarascio's work include Network Security and Intrusion Detection (11 papers), Business Process Modeling and Analysis (11 papers) and Advanced Malware Detection Techniques (10 papers). Massimo Guarascio is often cited by papers focused on Network Security and Intrusion Detection (11 papers), Business Process Modeling and Analysis (11 papers) and Advanced Malware Detection Techniques (10 papers). Massimo Guarascio collaborates with scholars based in Italy, India and Canada. Massimo Guarascio's co-authors include Luigi Pontieri, Francesco Folino, Gianluigi Folino, Geoffrey S. Watson, Michel David, Giuseppe Manco, Alfredo Cuzzocrea, Mara Lombardi, Giulio Sciarra and Francesco Chiaravalloti and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Massimo Guarascio

57 papers receiving 525 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Massimo Guarascio Italy 13 189 151 109 80 76 70 574
Abderrazak Sebaa Algeria 7 175 0.9× 83 0.5× 77 0.7× 66 0.8× 25 0.3× 18 639
Basil Papadopoulos Greece 17 214 1.1× 125 0.8× 100 0.9× 35 0.4× 99 1.3× 124 1.1k
Wayne Read Australia 16 115 0.6× 133 0.9× 68 0.6× 90 1.1× 222 2.9× 79 939
Wei Jie China 15 211 1.1× 104 0.7× 259 2.4× 191 2.4× 27 0.4× 79 1.1k
Roberto Corizzo United States 18 446 2.4× 159 1.1× 101 0.9× 48 0.6× 17 0.2× 64 990
Liguo Weng China 19 286 1.5× 123 0.8× 62 0.6× 32 0.4× 16 0.2× 73 979
Alexandre G. Evsukoff Brazil 17 287 1.5× 68 0.5× 28 0.3× 54 0.7× 54 0.7× 66 1.2k
Xiaodao Chen China 17 157 0.8× 86 0.6× 173 1.6× 144 1.8× 25 0.3× 42 926
Yufeng Kou China 14 389 2.1× 57 0.4× 103 0.9× 105 1.3× 75 1.0× 55 855

Countries citing papers authored by Massimo Guarascio

Since Specialization
Citations

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

Fields of papers citing papers by Massimo Guarascio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Massimo Guarascio

This figure shows the co-authorship network connecting the top 25 collaborators of Massimo Guarascio. A scholar is included among the top collaborators of Massimo Guarascio 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 Massimo Guarascio. Massimo Guarascio 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.
Guarascio, Massimo, et al.. (2025). A deep learning-based approach for stegomalware sanitization in digital images. Journal of Intelligent Information Systems. 64(1). 121–144.
2.
Comito, Carmela, et al.. (2025). M3DUSA: A Modular Multi-Modal Deep fUSion Architecture for fake news detection on social media. Social Network Analysis and Mining. 15(1).
3.
Folino, Gianluigi, Massimo Guarascio, Luigi Pontieri, & Paolo Zicari. (2025). Discovering ensembles of small language models out of scarcely labelled data for fake news detection. Applied Soft Computing. 171. 112794–112794.
4.
Guarascio, Massimo, et al.. (2024). No Country for Leaking Containers: Detecting Exfiltration of Secrets Through AI and Syscalls. 1–8. 1 indexed citations
5.
Folino, Francesco, Gianluigi Folino, Massimo Guarascio, & Luigi Pontieri. (2024). Data- & compute-efficient deviance mining via active learning and fast ensembles. Journal of Intelligent Information Systems. 62(4). 995–1019. 5 indexed citations
6.
Guarascio, Massimo, et al.. (2023). Generative Methods for Out-of-distribution Prediction and Applications for Threat Detection and Analysis: A Short Review. Communications in computer and information science. 65–79.
7.
Caviglione, Luca, et al.. (2023). A federated approach for detecting data hidden in icons of mobile applications delivered via web and multiple stores. Social Network Analysis and Mining. 13(1). 2 indexed citations
8.
Zicari, Paolo, Massimo Guarascio, Luigi Pontieri, & Gianluigi Folino. (2023). Learning Deep Fake-News Detectors from Scarcely-Labelled News Corpora. 344–353. 1 indexed citations
9.
Guarascio, Massimo, et al.. (2023). Juridical Side of ALARP: The Monte Bianco Tunnel. IRIS Research product catalog (Sapienza University of Rome). 2007–2014. 1 indexed citations
10.
Guarascio, Massimo, et al.. (2023). Neuro-Symbolic AI for Compliance Checking of Electrical Control Panels. Theory and Practice of Logic Programming. 23(4). 748–764.
11.
Guarascio, Massimo, et al.. (2023). ALARP in Engineering: Risk Based Design and CBA. IRIS Research product catalog (Sapienza University of Rome). 61–68. 2 indexed citations
12.
Caviglione, Luca, et al.. (2023). Learning autoencoder ensembles for detecting malware hidden communications in IoT ecosystems. Journal of Intelligent Information Systems. 62(4). 925–949. 3 indexed citations
13.
Guarascio, Massimo, et al.. (2023). Assessing Risk Acceptability and Tolerability in Italian Tunnels with the Quantum Gu@larp Model. Entropy. 26(1). 40–40. 1 indexed citations
14.
Guarascio, Massimo, et al.. (2023). A Deep Anomaly Detection System for IoT-Based Smart Buildings. Sensors. 23(23). 9331–9331. 3 indexed citations
15.
Guarascio, Massimo, et al.. (2022). Revealing MageCart-like Threats in Favicons via Artificial Intelligence. 1–7. 3 indexed citations
16.
Folino, Francesco, Gianluigi Folino, Massimo Guarascio, & Luigi Pontieri. (2019). Learning Effective Neural Nets for Outcome Prediction from Partially Labelled Log Data. 1396–1400. 5 indexed citations
17.
Cuzzocrea, Alfredo, Francesco Folino, Massimo Guarascio, & Luigi Pontieri. (2017). Deviance-Aware Discovery of High Quality Process Models. 724–731. 1 indexed citations
18.
Folino, Francesco, et al.. (2013). Adaptive Trace Abstraction Approach for Predicting Business Process Performances.. SEBD. 437–444. 1 indexed citations
19.
Guarascio, Massimo, et al.. (2013). Assessment of a vulnerability model against post-earthquake damage data: the case study of the historic city centre of L’Aquila in Italy. WIT transactions on the built environment. 1. 393–404. 16 indexed citations
20.
Cafaro, Emilio & Massimo Guarascio. (2006). Linee guida per la progettazione della sicurezza nelle gallerie stradali. PORTO Publications Open Repository TOrino (Politecnico di Torino). 6 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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