Battista Biggio

8.8k total citations · 3 hit papers
97 papers, 3.3k citations indexed

About

Battista Biggio is a scholar working on Artificial Intelligence, Signal Processing and Information Systems. According to data from OpenAlex, Battista Biggio has authored 97 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 67 papers in Artificial Intelligence, 49 papers in Signal Processing and 26 papers in Information Systems. Recurrent topics in Battista Biggio's work include Adversarial Robustness in Machine Learning (59 papers), Advanced Malware Detection Techniques (41 papers) and Anomaly Detection Techniques and Applications (27 papers). Battista Biggio is often cited by papers focused on Adversarial Robustness in Machine Learning (59 papers), Advanced Malware Detection Techniques (41 papers) and Anomaly Detection Techniques and Applications (27 papers). Battista Biggio collaborates with scholars based in Italy, Germany and Switzerland. Battista Biggio's co-authors include Fabio Roli, Giorgio Fumera, Alina Oprea, Ambra Demontis, Blaine Nelson, Cristina Nita-Rotaru, Bo Li, Chang Liu, Matthew Jagielski and Giorgio Giacinto and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, ACM Computing Surveys and Pattern Recognition.

In The Last Decade

Battista Biggio

85 papers receiving 3.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning

2018 456 citations Battista Biggio et al. UNICA IRIS Institutional Research Information System (University of Cagliari) profile →
Towards poisoning of deep learning algorithms with back-gradient optimization

2017 287 citations Battista Biggio, Ambra Demontis et al. UNICA IRIS Institutional Research Information System (University of Cagliari) profile →
Security Evaluation of Pattern Classifiers under Attack

2013 249 citations Battista Biggio, Giorgio Fumera et al. profile →

Peers

Countries citing papers authored by Battista Biggio

Since Specialization

Citations

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

Fields of papers citing papers by Battista Biggio

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Battista Biggio

This figure shows the co-authorship network connecting the top 25 collaborators of Battista Biggio. A scholar is included among the top collaborators of Battista Biggio 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 Battista Biggio. Battista Biggio is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Energy-latency attacks via sponge poisoning 2025 ·Information Sciences ·(unknown), Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo	0
2	Robustness-Congruent Adversarial Training for Secure Machine Learning Model Updates 2025 ·IEEE Transactions on Pattern Analysis and Machine Intelligence ·(unknown), Luca Demetrio, Maura Pintor, Luca Oneto, Davide Anguita, Battista Biggio, Fabio Roli	2
3	On the robustness of adversarial training against uncertainty attacks 2025 ·Pattern Recognition ·(unknown), (unknown), (unknown), (unknown), (unknown), Giorgio Fumera, Battista Biggio, Fabio Roli	0
4	When Your AI Becomes a Target: AI Security Incidents and Best Practices 2024 ·Proceedings of the AAAI Conference on Artificial Intelligence ·Kathrin Grosse, (unknown), Tarek R. Besold, Battista Biggio, Alexandre Alahi	2
5	Nebula: Self-Attention for Dynamic Malware Analysis 2024 ·IEEE Transactions on Information Forensics and Security ·(unknown), Luca Demetrio, Battista Biggio, Fabio Roli	12
6	Machine Learning Security Against Data Poisoning: Are We There Yet? 2024 ·Computer ·(unknown), Kathrin Grosse, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo	12
7	Toward Effective Traffic Sign Detection via Two-Stage Fusion Neural Networks 2024 ·IEEE Transactions on Intelligent Transportation Systems ·Zhishan Li, Hongxu Chen, Battista Biggio, Yifan He, (unknown), Fabio Roli, Lei Xie	15
8	SLIFER: Investigating performance and robustness of malware detection pipelines 2024 ·Computers & Security ·(unknown), (unknown), Luca Demetrio, Battista Biggio, (unknown), Fabio Roli	0
9	Stateful detection of adversarial reprogramming 2023 ·Information Sciences ·Yang Zheng, Xiaoyi Feng, Zhaoqiang Xia, Zetao Jiang, Maura Pintor, Ambra Demontis, Battista Biggio, Fabio Roli	2
10	Rethinking data augmentation for adversarial robustness 2023 ·Information Sciences ·Hamid Eghbal-zadeh, Werner Zellinger, Maura Pintor, Kathrin Grosse, (unknown), Bernhard Moser, Battista Biggio, Gerhard Widmer	4
11	Machine Learning Security in Industry: A Quantitative Survey 2023 ·IEEE Transactions on Information Forensics and Security ·Kathrin Grosse, (unknown), Tarek R. Besold, Battista Biggio, Katharina Krombholz	22
12	Hardening RGB-D object recognition systems against adversarial patch attacks 2023 ·Information Sciences ·Yang Zheng, Luca Demetrio, (unknown), Xiaoyi Feng, Zhaoqiang Xia, Zetao Jiang, Ambra Demontis, Battista Biggio, Fabio Roli	1
13	FADER: Fast adversarial example rejection 2022 ·CINECA IRIS Institutial research information system (University of Pisa) ·(unknown), Marco Melis, (unknown), Davide Bacciu, Battista Biggio	9
14	secml: Secure and explainable machine learning in Python 2022 ·SoftwareX ·Maura Pintor, Luca Demetrio, (unknown), Marco Melis, Ambra Demontis, Battista Biggio	8
15	Backdoor smoothing: Demystifying backdoor attacks on deep neural networks 2022 ·Computers & Security ·Kathrin Grosse, Taesung Lee, Battista Biggio, Youngja Park, Michael Backes, Ian Molloy	9
16	The Hammer and the Nut: Is Bilevel Optimization Really Needed to Poison Linear Classifiers? 2021 ·UNICA IRIS Institutional Research Information System (University of Cagliari) ·(unknown), Sebastiano Vascon, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo	2
17	Do gradient-based explanations tell anything about adversarial robustness to android malware? 2021 ·UNICA IRIS Institutional Research Information System (University of Cagliari) ·Marco Melis, (unknown), Ambra Demontis, Davide Maiorca, Battista Biggio, Giorgio Giacinto, Fabio Roli	21
18	Adversarial Detection of Flash Malware: Limitations and Open Issues 2020 ·Computers & Security ·Davide Maiorca, Ambra Demontis, Battista Biggio, Fabio Roli, Giorgio Giacinto	11
19	Is Deep Learning Safe for Robot Vision? Adversarial Examples against the iCub Humanoid 2018 ·UNICA IRIS Institutional Research Information System (University of Cagliari) ·Marco Melis, Ambra Demontis, Battista Biggio, Gavin Brown, Giorgio Fumera, Fabio Roli	44
20	Randomized Prediction Games for Adversarial Machine Learning 2016 ·IEEE Transactions on Neural Networks and Learning Systems ·Samuel Rota Bulò, Battista Biggio, Ignazio Pillai, Marcello Pelillo, Fabio Roli	40

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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