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.
This map shows the geographic impact of Daniel Gruss'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 Daniel Gruss with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Gruss more than expected).
This network shows the impact of papers produced by Daniel Gruss. 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 Daniel Gruss. The network helps show where Daniel Gruss may publish in the future.
Co-authorship network of co-authors of Daniel Gruss
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Gruss.
A scholar is included among the top collaborators of Daniel Gruss 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 Daniel Gruss. Daniel Gruss is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Werner, Mario, Thomas Unterluggauer, Lukas Giner, et al.. (2019). SCATTERCACHE: thwarting cache attacks via cache set randomization. USENIX Security Symposium. 675–692.56 indexed citations
15.
Weiser, Samuel, et al.. (2019). SGXJail: Defeating Enclave Malware via Confinement. 353–366.2 indexed citations
16.
Canella, Claudio, Jo Van Bulck, Michael Schwarz, et al.. (2019). A Systematic Evaluation of Transient Execution Attacks and Defenses. Lirias (KU Leuven). 249–266.67 indexed citations
Gruss, Daniel, et al.. (2018). Use-After-FreeMail. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 297–311.7 indexed citations
19.
Gruss, Daniel, et al.. (2017). Strong and efficient cache side-channel protection using hardware transactional memory. USENIX Security Symposium. 217–233.77 indexed citations
20.
Lipp, Moritz, Daniel Gruss, Raphael Spreitzer, & Stefan Mangard. (2015). ARMageddon: Last-Level Cache Attacks on Mobile Devices. arXiv (Cornell University). 549–564.11 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.