Daniela S Oliveira

988 total citations
32 papers, 551 citations indexed

About

Daniela S Oliveira is a scholar working on Signal Processing, Information Systems and Artificial Intelligence. According to data from OpenAlex, Daniela S Oliveira has authored 32 papers receiving a total of 551 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Signal Processing, 20 papers in Information Systems and 17 papers in Artificial Intelligence. Recurrent topics in Daniela S Oliveira's work include Advanced Malware Detection Techniques (21 papers), Security and Verification in Computing (12 papers) and Network Security and Intrusion Detection (12 papers). Daniela S Oliveira is often cited by papers focused on Advanced Malware Detection Techniques (21 papers), Security and Verification in Computing (12 papers) and Network Security and Intrusion Detection (12 papers). Daniela S Oliveira collaborates with scholars based in United States, Brazil and United Kingdom. Daniela S Oliveira's co-authors include Tian Lin, Donovan M. Ellis, Harold A. Rocha, Natalie C. Ebner, André Grégio, Donald E. Porter, Marcus Botacin, Melis Muradoglu, Harry Kalodner and Vrushali Kulkarni and has published in prestigious journals such as Expert Systems with Applications, ACM Computing Surveys and IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Daniela S Oliveira

31 papers receiving 530 citations

Peers

Daniela S Oliveira
Comparison fields: 5 of 43
  • Information Systems 367
  • Signal Processing 216
  • Artificial Intelligence 199
  • Sociology and Political Science 158
  • Computer Networks and Communications 155
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Citations per field, relative to Daniela S Oliveira
Daniela S Oliveira · 1×
Citations per year, relative to Daniela S Oliveira
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Countries citing papers authored by Daniela S Oliveira

Since Specialization
Citations

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

Fields of papers citing papers by Daniela S Oliveira

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniela S Oliveira. 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 Daniela S Oliveira. The network helps show where Daniela S Oliveira may publish in the future.

Co-authorship network of co-authors of Daniela S Oliveira

This figure shows the co-authorship network connecting the top 25 collaborators of Daniela S Oliveira. A scholar is included among the top collaborators of Daniela S Oliveira 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 Daniela S Oliveira. Daniela S Oliveira 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
# Work Indexed citations
1 4
2 12
3 1
4 3
5 32
6 11
7 7
8 7
9 25
10 15
11 3
12 48
13 8
14 2
15 0
16
The Case for Unpredictability and Deception as OS Features
5
17
The case for less predictable operating system behavior
6
18 6
19 84
20 6

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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