Marco Barreno
- Artificial Intelligence top 1%
- Computer Networks and Communications top 2%
- Signal Processing top 1%
- Information Systems top 5%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- J. D. TygarBlaine NelsonAnthony D. JosephRussell SearsBenjamin I. P. RubinsteinKai XiaCharles SuttonKamalika Chaudhuri
- Topics
- Network Security and Intrusion Detection (5 papers)Advanced Malware Detection Techniques (3 papers)Spam and Phishing Detection (2 papers)
- Journals
- Machine LearningEdinburgh Research ExplorerNeural Information Processing Systems
- Partner nations
- United States
In The Last Decade
Marco Barreno
7 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 71
- Artificial Intelligence 936
- Computer Networks and Communications 558
- Signal Processing 505
- Information Systems 227
- Computer Vision and Pattern Recognition 80
Countries citing papers authored by Marco Barreno
This map shows the geographic impact of Marco Barreno'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 Marco Barreno with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marco Barreno more than expected).
Fields of papers citing papers by Marco Barreno
This network shows the impact of papers produced by Marco Barreno. 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 Marco Barreno. The network helps show where Marco Barreno may publish in the future.
Co-authorship network of co-authors of Marco Barreno
This figure shows the co-authorship network connecting the top 25 collaborators of Marco Barreno. A scholar is included among the top collaborators of Marco Barreno 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 Marco Barreno. Marco Barreno is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | The security of machine learningbreakdown → | 459 |
| 2 | Exploiting machine learning to subvert your spam filter | 173 |
| 3 | 23 | |
| 4 | Evaluating the security of machine learning algorithms | 5 |
| 5 | Optimal ROC Curve for a Combination of Classifiers | 33 |
| 6 | Can machine learning be secure?breakdown → | 481 |
| 7 | 95 |
About Marco Barreno
Marco Barreno is a scholar working on Signal Processing, Computer Networks and Communications and Health Information Management, having authored 7 papers that have together received 1.3k indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (5 papers), Advanced Malware Detection Techniques (3 papers) and Spam and Phishing Detection (2 papers). The work is most often cited by research in Signal Processing (505 citations), Artificial Intelligence (936 citations) and Computer Networks and Communications (558 citations). Marco Barreno has collaborated with scholars based in United States. Frequent co-authors include J. D. Tygar, Blaine Nelson, Anthony D. Joseph, Russell Sears, Benjamin I. P. Rubinstein, Kai Xia, Charles Sutton, Kamalika Chaudhuri, John Kubiatowicz and Byung-Gon Chun. Their work appears in journals such as Machine Learning, Edinburgh Research Explorer and Neural Information Processing Systems.
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.