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.
An empirical study of cryptographic misuse in android applications
2013262 citationsYanick Fratantonio, Christopher Kruegel et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
Countries citing papers authored by Yanick Fratantonio
Since
Specialization
Citations
This map shows the geographic impact of Yanick Fratantonio'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 Yanick Fratantonio with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yanick Fratantonio more than expected).
Fields of papers citing papers by Yanick Fratantonio
This network shows the impact of papers produced by Yanick Fratantonio. 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 Yanick Fratantonio. The network helps show where Yanick Fratantonio may publish in the future.
Co-authorship network of co-authors of Yanick Fratantonio
This figure shows the co-authorship network connecting the top 25 collaborators of Yanick Fratantonio.
A scholar is included among the top collaborators of Yanick Fratantonio 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 Yanick Fratantonio. Yanick Fratantonio 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.
Fratantonio, Yanick, et al.. (2022). RE-Mind: a First Look Inside the Mind of a Reverse Engineer. SPIRE - Sciences Po Institutional REpository.
2.
Graziano, Mariano, et al.. (2022). How Machine Learning Is Solving the Binary Function Similarity Problem. SPIRE - Sciences Po Institutional REpository.16 indexed citations
Fratantonio, Yanick, et al.. (2020). Towards {HTTPS} Everywhere on Android: We Are Not There Yet. USENIX Security Symposium. 343–360.6 indexed citations
7.
Bianchi, Antonio, et al.. (2019). Exploring Syscall-Based Semantics Reconstruction of Android Applications. Graduate School and Research Center in Digital Science (EURECOM). 517–531.1 indexed citations
8.
Gustafson, Eric, Marius Muench, Chad Spensky, et al.. (2019). Toward the Analysis of Embedded Firmware through Automated Re-hosting. eScholarship (California Digital Library). 135–150.40 indexed citations
Redini, Nilo, Aravind Machiry, Dipanjan Das, et al.. (2017). Bootstomp: On the security of bootloaders in mobile devices. USENIX Security Symposium. 781–798.20 indexed citations
Vigna, Giovanni, Kevin Borgolte, Adam Doupé, et al.. (2014). Ten Years of iCTF: The Good, The Bad, and The Ugly. Genetics Selection Evolution.34 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.