Michele Ianni

807 total citations · 1 hit paper
36 papers, 420 citations indexed

About

Michele Ianni is a scholar working on Artificial Intelligence, Signal Processing and Computer Networks and Communications. According to data from OpenAlex, Michele Ianni has authored 36 papers receiving a total of 420 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 20 papers in Signal Processing and 11 papers in Computer Networks and Communications. Recurrent topics in Michele Ianni's work include Advanced Malware Detection Techniques (14 papers), Anomaly Detection Techniques and Applications (8 papers) and Network Security and Intrusion Detection (7 papers). Michele Ianni is often cited by papers focused on Advanced Malware Detection Techniques (14 papers), Anomaly Detection Techniques and Applications (8 papers) and Network Security and Intrusion Detection (7 papers). Michele Ianni collaborates with scholars based in Italy, United States and Saudi Arabia. Michele Ianni's co-authors include Giancarlo Fortino, Antonella Guzzo, Diletta Chiaro, Francesco Piccialli, Pian Qi, Elio Masciari, Carlo Zaniolo, Giancarlo Sperlí, Giuseppe M. Mazzeo and Mario Mezzanzanica and has published in prestigious journals such as Information Sciences, Information Fusion and Future Generation Computer Systems.

In The Last Decade

Michele Ianni

30 papers receiving 406 citations

Hit Papers

align trajectories sort by overperformance

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.

Model aggregation techniques in federated learning: A comprehensive survey

2023 167 citations Antonella Guzzo, Michele Ianni et al. Future Generation Computer Systems profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michele Ianni Italy	9	279	100	66	54	51	36	420
Ramazan Terzi Türkiye	7	146 0.5×	98 1.0×	89 1.3×	48 0.9×	38 0.7×	15	322
Wael Said Egypt	13	151 0.5×	88 0.9×	101 1.5×	41 0.8×	91 1.8×	37	426
Niranjan N. Chiplunkar India	10	170 0.6×	89 0.9×	114 1.7×	30 0.6×	86 1.7×	60	408
Keng‐Pei Lin Taiwan	13	228 0.8×	46 0.5×	99 1.5×	32 0.6×	75 1.5×	29	381
Abdullah Alabdulatif Saudi Arabia	9	140 0.5×	161 1.6×	123 1.9×	67 1.2×	41 0.8×	28	414
Saima Anwar Lashari Malaysia	10	135 0.5×	108 1.1×	66 1.0×	24 0.4×	76 1.5×	42	407
M. Govindarajan India	10	234 0.8×	154 1.5×	70 1.1×	86 1.6×	34 0.7×	45	353
Suriani Mohd Sam Malaysia	8	132 0.5×	120 1.2×	194 2.9×	23 0.4×	75 1.5×	34	444
Zhuotao Lian Japan	9	249 0.9×	145 1.4×	134 2.0×	28 0.5×	30 0.6×	23	428

Countries citing papers authored by Michele Ianni

Since Specialization

Citations

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

Fields of papers citing papers by Michele Ianni

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michele Ianni

This figure shows the co-authorship network connecting the top 25 collaborators of Michele Ianni. A scholar is included among the top collaborators of Michele Ianni 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 Michele Ianni. Michele Ianni 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

Ianni, Michele, et al.. (2025). A formal framework for LLM-assisted automated generation of Zeek signatures from binary artifacts. Future Generation Computer Systems. 175. 108086–108086.

Raza, Asaf, Antonella Guzzo, Michele Ianni, et al.. (2025). Federated Learning in radiomics: A comprehensive meta-survey on medical image analysis. Computer Methods and Programs in Biomedicine. 267. 108768–108768. 7 indexed citations

Ianni, Michele, et al.. (2025). A cross-architecture malware detection approach based on intermediate representation. Journal of Information Security and Applications. 93. 104117–104117. 2 indexed citations

Preda, Mila Dalla, et al.. (2024). Light sensor based covert channels on mobile devices. Information Sciences. 690. 121581–121581. 1 indexed citations

Ianni, Michele, et al.. (2024). Enabling Obfuscation Detection in Binary Software through eXplainable AI. IEEE Transactions on Emerging Topics in Computing. 1–12. 3 indexed citations

Ianni, Michele, et al.. (2024). A Forensic Framework for Screen Capture Validation in Legal Contexts. 23. 127–132.

Preda, Mila Dalla & Michele Ianni. (2023). Exploiting number theory for dynamic software watermarking. Journal of Computer Virology and Hacking Techniques. 20(1). 41–51. 2 indexed citations

Ianni, Michele, et al.. (2023). Deep Learning-Based Detection of CSRF Vulnerabilities in Web Applications. 916–920.

Ianni, Michele, et al.. (2023). Exploiting Bytecode Analysis for Reentrancy Vulnerability Detection in Ethereum Smart Contracts. 779–783.

10.

Khan, Sadia Afrin, et al.. (2023). An advanced data fabric architecture leveraging homomorphic encryption and federated learning. Information Fusion. 102. 102004–102004. 38 indexed citations

11.

Fortino, Giancarlo, et al.. (2022). Neural Network based Temporal Point Processes for Attack Detection in Industrial Control Systems. 221–226. 4 indexed citations

12.

Ianni, Michele & Elio Masciari. (2022). Some Experiments on High Performance Anomaly Detection. 226–229. 3 indexed citations

13.

Ianni, Michele, Aravind Machiry, Yanick Fratantonio, et al.. (2021). Tarnhelm: Isolated, Transparent & Confidential Execution of Arbitrary Code in ARM's TrustZone. 43–57. 3 indexed citations

14.

Ianni, Michele, Elio Masciari, & Giancarlo Sperlí. (2020). A survey of Big Data dimensions vs Social Networks analysis. Journal of Intelligent Information Systems. 57(1). 73–100. 25 indexed citations

15.

Fortino, Giancarlo, Antonella Guzzo, Michele Ianni, Francesco Leotta, & Massimo Mecella. (2020). Exploiting Marked Temporal Point Processes for Predicting Activities of Daily Living. IRIS Research product catalog (Sapienza University of Rome). 1–6. 8 indexed citations

16.

Ianni, Michele, Elio Masciari, Giuseppe M. Mazzeo, & Carlo Zaniolo. (2019). How to implement a big data clustering algorithm. 1073–1080. 1 indexed citations

17.

Ianni, Michele, Elio Masciari, & Domenico Saccà. (2019). An Overview of the Endless Battle between Virus Writers and Detectors: How Compilers Can Be Used as an Evasion Technique. 203–208. 2 indexed citations

18.

Flesca, Sergio, et al.. (2018). Distributed computing by leveraging and rewarding idling user resources from P2P networks. Journal of Parallel and Distributed Computing. 122. 81–94. 2 indexed citations

19.

Ianni, Michele, Elio Masciari, Giuseppe M. Mazzeo, & Carlo Zaniolo. (2018). Efficient Big Data Clustering. 103–109. 2 indexed citations

20.

Ianni, Michele, Elio Masciari, Giuseppe M. Mazzeo, & Carlo Zaniolo. (2018). Clustering Big Data. INFM-OAR (INFN Catania). 276–282.

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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