Luca Demetrio

540 total citations
20 papers, 192 citations indexed

About

Luca Demetrio is a scholar working on Artificial Intelligence, Signal Processing and Computer Networks and Communications. According to data from OpenAlex, Luca Demetrio has authored 20 papers receiving a total of 192 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 9 papers in Signal Processing and 5 papers in Computer Networks and Communications. Recurrent topics in Luca Demetrio's work include Adversarial Robustness in Machine Learning (16 papers), Advanced Malware Detection Techniques (9 papers) and Anomaly Detection Techniques and Applications (8 papers). Luca Demetrio is often cited by papers focused on Adversarial Robustness in Machine Learning (16 papers), Advanced Malware Detection Techniques (9 papers) and Anomaly Detection Techniques and Applications (8 papers). Luca Demetrio collaborates with scholars based in Italy, France and Israel. Luca Demetrio's co-authors include Battista Biggio, Fabio Roli, Giovanni Lagorio, Scott E. Coull, Alessandro Armando, Maura Pintor, Ambra Demontis, Asaf Shabtai, Gabriele Costa and Luca Oneto and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition and Information Sciences.

In The Last Decade

Luca Demetrio

15 papers receiving 184 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Luca Demetrio Italy 7 137 108 64 32 16 20 192
Bao Gia Doan Australia 5 281 2.1× 112 1.0× 65 1.0× 16 0.5× 73 4.6× 8 316
Yufeng Li China 4 218 1.6× 103 1.0× 121 1.9× 30 0.9× 22 1.4× 7 263
Anand Handa India 6 64 0.5× 80 0.7× 95 1.5× 64 2.0× 16 1.0× 21 178
Rakyong Choi South Korea 5 202 1.5× 73 0.7× 155 2.4× 43 1.3× 32 2.0× 11 270
Khalid Chougdali Morocco 7 100 0.7× 66 0.6× 106 1.7× 31 1.0× 56 3.5× 59 198
Altaf Shaik Germany 6 99 0.7× 56 0.5× 172 2.7× 90 2.8× 7 0.4× 9 258
Idowu Dauda Oladipo Nigeria 7 82 0.6× 55 0.5× 91 1.4× 28 0.9× 14 0.9× 12 149
Donghai Tian China 9 135 1.0× 165 1.5× 129 2.0× 100 3.1× 10 0.6× 30 247
Aleksandra Mileva North Macedonia 8 136 1.0× 67 0.6× 107 1.7× 43 1.3× 88 5.5× 32 256
Cong Liao United States 5 117 0.9× 38 0.4× 47 0.7× 38 1.2× 32 2.0× 12 173

Countries citing papers authored by Luca Demetrio

Since Specialization
Citations

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

Fields of papers citing papers by Luca Demetrio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Luca Demetrio

This figure shows the co-authorship network connecting the top 25 collaborators of Luca Demetrio. A scholar is included among the top collaborators of Luca Demetrio 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 Luca Demetrio. Luca Demetrio 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.
Demetrio, Luca, Maura Pintor, Luca Oneto, et al.. (2025). Robustness-Congruent Adversarial Training for Secure Machine Learning Model Updates. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(9). 7457–7469. 2 indexed citations
2.
Demetrio, Luca, et al.. (2025). Updating Windows malware detectors: Balancing robustness and regression against adversarial EXEmples. Computers & Security. 155. 104466–104466.
3.
Demetrio, Luca, Luca Compagna, Davide Ariu, et al.. (2025). ModSec-AdvLearn: Countering Adversarial SQL Injections With Robust Machine Learning. IEEE Transactions on Information Forensics and Security. 20. 6693–6705.
4.
Rony, Jérôme, Maura Pintor, Luca Demetrio, et al.. (2025). AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples. Proceedings of the AAAI Conference on Artificial Intelligence. 39(3). 2600–2608. 5 indexed citations
5.
Demetrio, Luca, et al.. (2024). Nebula: Self-Attention for Dynamic Malware Analysis. IEEE Transactions on Information Forensics and Security. 19. 6155–6167. 12 indexed citations
6.
Demetrio, Luca, et al.. (2024). SLIFER: Investigating performance and robustness of malware detection pipelines. Computers & Security. 150. 104264–104264.
7.
Zheng, Yang, Luca Demetrio, Xiaoyi Feng, et al.. (2023). Hardening RGB-D object recognition systems against adversarial patch attacks. Information Sciences. 651. 119701–119701. 1 indexed citations
8.
Demetrio, Luca, et al.. (2023). Phantom Sponges: Exploiting Non-Maximum Suppression to Attack Deep Object Detectors. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 4560–4569. 15 indexed citations
9.
Pintor, Maura, et al.. (2023). Detecting Attacks Against Deep Reinforcement Learning for Autonomous Driving. UNICA IRIS Institutional Research Information System (University of Cagliari). 57–62.
10.
Pintor, Maura, et al.. (2022). secml: Secure and explainable machine learning in Python. SoftwareX. 18. 101095–101095. 8 indexed citations
11.
Pintor, Maura, et al.. (2022). ImageNet-Patch: A dataset for benchmarking machine learning robustness against adversarial patches. Pattern Recognition. 134. 109064–109064. 28 indexed citations
12.
Demetrio, Luca, Battista Biggio, & Fabio Roli. (2022). Practical Attacks on Machine Learning: A Case Study on Adversarial Windows Malware. IEEE Security & Privacy. 20(5). 77–85. 6 indexed citations
13.
Demetrio, Luca & Battista Biggio. (2022). Secml-Malware: Pentesting Windows Malware Classifiers with Adversarial Exemples in Python. SSRN Electronic Journal. 2 indexed citations
14.
Oneto, Luca, Nicolò Navarin, Battista Biggio, et al.. (2022). Towards learning trustworthily, automatically, and with guarantees on graphs: An overview. Neurocomputing. 493. 217–243. 19 indexed citations
15.
Kravchik, Moshe, Luca Demetrio, Battista Biggio, & Asaf Shabtai. (2022). Practical Evaluation of Poisoning Attacks on Online Anomaly Detectors in Industrial Control Systems. Computers & Security. 122. 102901–102901. 9 indexed citations
16.
Melis, Marco, et al.. (2022). Secml: Secure and Explainable Machine Learning in Python. SSRN Electronic Journal. 2 indexed citations
17.
Pintor, Maura, et al.. (2021). Slope: A First-order Approach for Measuring Gradient Obfuscation. UNICA IRIS Institutional Research Information System (University of Cagliari). 363–368.
18.
Demetrio, Luca, Scott E. Coull, Battista Biggio, et al.. (2021). Adversarial EXEmples. ACM Transactions on Privacy and Security. 24(4). 1–31. 71 indexed citations
19.
Demetrio, Luca, et al.. (2019). WAF-A-MoLE: An adversarial tool for assessing ML-based WAFs. SoftwareX. 11. 100367–100367. 6 indexed citations
20.
Demetrio, Luca, et al.. (2019). ZenHackAdemy: Ethical Hacking @ DIBRIS. CINECA IRIS Institutial Research Information System (University of Genoa). 405–413. 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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