M.A.P. Chamikara
- Artificial Intelligence top 2%
- Privacy-Preserving Technologies in Data 13
- Adversarial Robustness in Machine Learning 5
- Cryptography and Data Security 3
- Health Informatics top 5%
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- Mobile Crowdsensing and Crowdsourcing 4
- Information Systems top 2%
- Information and Cyber Security 3
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- Network Security and Intrusion Detection 4
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- Privacy, Security, and Data Protection 4
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- Advanced Malware Detection Techniques 4
M.A.P. Chamikara
28 papers receiving 998 citations
Hit Papers
Peers
Comparison fields: 5 of 90
- Artificial Intelligence 673
- Health Informatics 28
- Computer Science Applications 96
- Information Systems 288
- Computer Networks and Communications 222
Countries citing papers authored by M.A.P. Chamikara
This map shows the geographic impact of M.A.P. Chamikara'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 M.A.P. Chamikara with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M.A.P. Chamikara more than expected).
Fields of papers citing papers by M.A.P. Chamikara
This network shows the impact of papers produced by M.A.P. Chamikara. 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 M.A.P. Chamikara. The network helps show where M.A.P. Chamikara may publish in the future.
Co-authorship network
The 25 scholars most cited alongside M.A.P. Chamikara, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 2 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2023 | 0 | |
| 5 | 2023 | 11 | |
| 6 | 2023 | 6 | |
| 7 | 2022 | 60 | |
| 8 | 2022 | 1 | |
| 9 | SplitFed: When Federated Learning Meets Split Learningbreakdown → | 2022 | 337 |
| 10 | 2021 | 10 | |
| 11 | 2021 | 4 | |
| 12 | 2021 | 13 | |
| 13 | 2020 | 175 | |
| 14 | 2020 | 81 | |
| 15 | 2019 | 65 | |
| 16 | 2019 | 2 | |
| 17 | 2018 | 53 | |
| 18 | 2015 | 1 | |
| 19 | An Efficient Algorithm To Detect The Nearest Location Of A Map For A Given Theme | 2013 | 1 |
| 20 | Generation of Strongly Regular Graphs from Normalized Hadamard Matrices | 2013 | 2 |
About M.A.P. Chamikara
M.A.P. Chamikara is a scholar working on Computer Science Applications, Health Informatics and Signal Processing, having authored 30 papers that have together received 1.0k indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (13 papers), Adversarial Robustness in Machine Learning (5 papers), Privacy, Security, and Data Protection (4 papers), Network Security and Intrusion Detection (4 papers), Mobile Crowdsensing and Crowdsourcing (4 papers), Advanced Malware Detection Techniques (4 papers), Cryptography and Data Security (3 papers) and Information and Cyber Security (3 papers). The work is most often cited by research in Artificial Intelligence (673 citations), Health Informatics (28 citations) and Computer Science Applications (96 citations). M.A.P. Chamikara has collaborated with scholars based in Australia, Sri Lanka and United States. Frequent co-authors include Seyit Camtepe, Ibrahim Khalil, Péter Bertök, Chandra Thapa, Lichao Sun, D. Liu, Mohammed Atiquzzaman, Dongxi Liu, Abdelaziz Bouras and Mohammad Saidur Rahman. Their work appears in journals such as Computer Communications, Computers & Security, Information Sciences, PeerJ Computer Science and Personal and Ubiquitous Computing.
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.