Davide Ariu

1.2k total citations
19 papers, 763 citations indexed

About

Davide Ariu is a scholar working on Signal Processing, Computer Networks and Communications and Information Systems. According to data from OpenAlex, Davide Ariu has authored 19 papers receiving a total of 763 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Signal Processing, 13 papers in Computer Networks and Communications and 12 papers in Information Systems. Recurrent topics in Davide Ariu's work include Advanced Malware Detection Techniques (14 papers), Network Security and Intrusion Detection (13 papers) and Spam and Phishing Detection (7 papers). Davide Ariu is often cited by papers focused on Advanced Malware Detection Techniques (14 papers), Network Security and Intrusion Detection (13 papers) and Spam and Phishing Detection (7 papers). Davide Ariu collaborates with scholars based in Italy, United States and Japan. Davide Ariu's co-authors include Giorgio Giacinto, Igino Corona, Roberto Perdisci, Davide Maiorca, Prahlad Fogla, Wenke Lee, Fabio Roli, Roberto Tronci, Battista Biggio and Samuel Rota Bulò and has published in prestigious journals such as IEEE Transactions on Information Forensics and Security, Computer Networks and Computers & Security.

In The Last Decade

Davide Ariu

18 papers receiving 716 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Davide Ariu Italy 13 570 516 440 262 81 19 763
Igino Corona Italy 11 643 1.1× 579 1.1× 477 1.1× 317 1.2× 68 0.8× 16 834
Kangkook Jee United States 13 626 1.1× 569 1.1× 410 0.9× 414 1.6× 66 0.8× 25 905
Yonghwi Kwon United States 16 273 0.5× 324 0.6× 299 0.7× 271 1.0× 110 1.4× 50 591
Jonathon Giffin United States 14 510 0.9× 818 1.6× 683 1.6× 468 1.8× 136 1.7× 21 999
Thomas H. Austin United States 16 686 1.2× 860 1.7× 574 1.3× 502 1.9× 145 1.8× 41 1.0k
Paolo Milani Comparetti Austria 8 470 0.8× 601 1.2× 272 0.6× 353 1.3× 214 2.6× 9 722
Purui Su China 11 228 0.4× 286 0.6× 319 0.7× 217 0.8× 160 2.0× 54 577
Fredrik Valeur United States 9 320 0.6× 354 0.7× 335 0.8× 197 0.8× 83 1.0× 11 531
Xabier Ugarte-Pedrero Spain 13 561 1.0× 677 1.3× 284 0.6× 399 1.5× 158 2.0× 26 788
Blake Anderson United States 9 623 1.1× 536 1.0× 488 1.1× 193 0.7× 71 0.9× 20 739

Countries citing papers authored by Davide Ariu

Since Specialization
Citations

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

Fields of papers citing papers by Davide Ariu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Davide Ariu

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

All Works

19 of 19 papers shown
1.
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.
2.
Ariu, Davide, et al.. (2017). Social Engineering 2.0. UNICA IRIS Institutional Research Information System (University of Cagliari). 319–325. 9 indexed citations
3.
Ahmadi, Mansour, Battista Biggio, Steven Arzt, Davide Ariu, & Giorgio Giacinto. (2016). Detecting Misuse of Google Cloud Messaging in Android Badware. UNICA IRIS Institutional Research Information System (University of Cagliari). 103–112. 13 indexed citations
4.
Maiorca, Davide, et al.. (2015). Stealth attacks: An extended insight into the obfuscation effects on Android malware. Computers & Security. 51. 16–31. 115 indexed citations
5.
Ariu, Davide, Igino Corona, Roberto Tronci, & Giorgio Giacinto. (2015). Machine Learning in Security Applications. UNICA IRIS Institutional Research Information System (University of Cagliari). 8(1). 3–39. 2 indexed citations
6.
Ariu, Davide, et al.. (2015). Clustering android malware families by http traffic. UNICA IRIS Institutional Research Information System (University of Cagliari). 128–135. 30 indexed citations
7.
Ariu, Davide, et al.. (2015). 2020 Cybercrime Economic Costs: No Measure No Solution. Figshare. 701–710. 22 indexed citations
8.
Maiorca, Davide, Davide Ariu, Igino Corona, & Giorgio Giacinto. (2015). A Structural and Content-based Approach for a Precise and Robust Detection of Malicious PDF Files. UNICA IRIS Institutional Research Information System (University of Cagliari). 27–36. 26 indexed citations
9.
Corona, Igino, et al.. (2015). PharmaGuard: Automatic identification of illegal search-indexed online pharmacies. UNICA IRIS Institutional Research Information System (University of Cagliari). 7. 324–329. 5 indexed citations
10.
Corona, Igino, Davide Maiorca, Davide Ariu, & Giorgio Giacinto. (2014). Lux0R. UNICA IRIS Institutional Research Information System (University of Cagliari). 47–57. 42 indexed citations
11.
Ariu, Davide, et al.. (2014). Security of the Digital Natives. SSRN Electronic Journal. 6 indexed citations
12.
Biggio, Battista, Konrad Rieck, Davide Ariu, et al.. (2014). Poisoning behavioral malware clustering. UNICA IRIS Institutional Research Information System (University of Cagliari). 27–36. 75 indexed citations
13.
Biggio, Battista, Ignazio Pillai, Samuel Rota Bulò, et al.. (2013). Is data clustering in adversarial settings secure?. UNICA IRIS Institutional Research Information System (University of Cagliari). 87–98. 67 indexed citations
14.
Perdisci, Roberto, Davide Ariu, & Giorgio Giacinto. (2012). Scalable fine-grained behavioral clustering of HTTP-based malware. Computer Networks. 57(2). 487–500. 43 indexed citations
15.
Ariu, Davide, Roberto Tronci, & Giorgio Giacinto. (2011). HMMPayl: An intrusion detection system based on Hidden Markov Models. Computers & Security. 30(4). 221–241. 79 indexed citations
16.
Ariu, Davide, Giorgio Giacinto, & Fabio Roli. (2011). Machine learning in computer forensics (and the lessons learned from machine learning in computer security). UNICA IRIS Institutional Research Information System (University of Cagliari). 99–104. 14 indexed citations
17.
Ariu, Davide & Giorgio Giacinto. (2010). HMMPayl: an application of HMM to the analysis of the HTTP Payload. UNICA IRIS Institutional Research Information System (University of Cagliari). 11. 81–87. 6 indexed citations
18.
Corona, Igino, Davide Ariu, & Giorgio Giacinto. (2009). HMM-Web: A Framework for the Detection of Attacks Against Web Applications. UNICA IRIS Institutional Research Information System (University of Cagliari). 1–6. 29 indexed citations
19.
Perdisci, Roberto, Davide Ariu, Prahlad Fogla, Giorgio Giacinto, & Wenke Lee. (2008). McPAD: A multiple classifier system for accurate payload-based anomaly detection. Computer Networks. 53(6). 864–881. 180 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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