Sagnik Sarkar

579 citations
10 papers · 346 indexed · 1 hit paper · h-index 6

Sagnik Sarkar

9 papers receiving 336 citations

Hit Papers

Federated Learning for intrusion detection system: Concep...223202220262023202450100150200

Peers

Sagnik Sarkar
Comparison fields: 5 of 66
  • Computer Networks and Communications 187
  • Artificial Intelligence 229
  • Signal Processing 56
  • Health Informatics 7
  • Information Systems 51
Replace Shaashwat Agrawal with:
Shaashwat Agrawal India
Bimal Ghimire United States
Bong Jun Ko United States
Sathiya Keerthi United States
Ali Akbar Movassagh Iran
Tamara Živković Serbia
Yasser Alharbi Saudi Arabia
Khalid K. Almuzaini Saudi Arabia
Mehmet Demirci Türkiye
Mario Sanz Spain
Sagnik Sarkar relative to Shaashwat Agrawal India Shaashwat Agrawal's profile →
Citations per field
00.5×1.5×
Shaashwat Agrawal · 1×
Citations per year

Countries citing papers authored by Sagnik Sarkar

Since Specialization
Citations

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

Fields of papers citing papers by Sagnik Sarkar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 15 scholars most cited alongside Sagnik Sarkar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sagnik Sarkar Line = papers co-authored together Sagnik Sarkar links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1 20252
2 20231
3 20231
4 202212
5
Federated Learning for intrusion detection system: Concepts, challenges and future directionsbreakdown →
2022223
6 202146
7 202126
8 20218
9 202127
10 20170

About Sagnik Sarkar

Sagnik Sarkar is a scholar working on Safety, Risk, Reliability and Quality, Artificial Intelligence and Transportation, having authored 10 papers that have together received 346 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (4 papers), Recommender Systems and Techniques (2 papers), Internet Traffic Analysis and Secure E-voting (2 papers), Network Security and Intrusion Detection (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Dental Radiography and Imaging (1 paper), Machine Fault Diagnosis Techniques (1 paper) and Medical Imaging Techniques and Applications (1 paper). The work is most often cited by research in Computer Networks and Communications (187 citations), Artificial Intelligence (229 citations) and Signal Processing (56 citations). Sagnik Sarkar has collaborated with scholars based in India, Australia and United States. Frequent co-authors include Shaashwat Agrawal, Thippa Reddy Gadekallu, Praveen Kumar Reddy Maddikunta, Mamoun Alazab, Sweta Bhattacharya, Gokul Yenduri, Ons Aouedi, Kandaraj Piamrat, Quoc‐Viet Pham and Gautam Srivastava. Their work appears in journals such as SHILAP Revista de lepidopterología, Computer Communications and Applied Intelligence.

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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