Lokesh Sharma
- Computer Networks and Communications top 5%
- Artificial Intelligence top 5%
- Signal Processing top 5%
- Information Systems top 10%
- Control and Systems Engineering
- Co-authors
- Chhagan LalB.L. SharmaSatyabrata RoyJosé Antonio Marmolejo-SaucedoDeepak GuptaUtku KöseDurga Prasad SharmaSarada Prasad Gochhayat
- Topics
- Network Security and Intrusion Detection (5 papers)Advanced Malware Detection Techniques (4 papers)Anomaly Detection Techniques and Applications (3 papers)
- Partner nations
- IndiaNetherlandsUnited States
In The Last Decade
Lokesh Sharma
12 papers receiving 327 citations
Hit Papers
Peers
Comparison fields: 5 of 46
- Computer Networks and Communications 277
- Artificial Intelligence 202
- Signal Processing 135
- Information Systems 50
- Control and Systems Engineering 49
Countries citing papers authored by Lokesh Sharma
This map shows the geographic impact of Lokesh Sharma'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 Lokesh Sharma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lokesh Sharma more than expected).
Fields of papers citing papers by Lokesh Sharma
This network shows the impact of papers produced by Lokesh Sharma. 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 Lokesh Sharma. The network helps show where Lokesh Sharma may publish in the future.
Co-authorship network of co-authors of Lokesh Sharma
This figure shows the co-authorship network connecting the top 25 collaborators of Lokesh Sharma. A scholar is included among the top collaborators of Lokesh Sharma 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 Lokesh Sharma. Lokesh Sharma is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | Explainable artificial intelligence for intrusion detection in IoT networks: A deep learning based approachbreakdown → | 99 |
| 3 | Anomaly based network intrusion detection for IoT attacks using deep learning techniquebreakdown → | 132 |
| 4 | 0 | |
| 5 | 6 | |
| 6 | 3 | |
| 7 | 1 | |
| 8 | 9 | |
| 9 | 3 | |
| 10 | 29 | |
| 11 | 4 | |
| 12 | 5 | |
| 13 | 48 | |
| 14 | Routing Protocols Performance Evaluation based on FTP and CBR application agents for Wireless Networks | 0 |
| 15 | Implementation and Performance Evaluation of Link-Disjoint Multipath AODV Routing Protocol | 1 |
About Lokesh Sharma
Lokesh Sharma is a scholar working on Computer Networks and Communications, Signal Processing and Information Systems and Management, having authored 15 papers that have together received 342 indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (5 papers), Advanced Malware Detection Techniques (4 papers) and Anomaly Detection Techniques and Applications (3 papers). The work is most often cited by research in Signal Processing (135 citations), Computer Networks and Communications (277 citations) and Artificial Intelligence (202 citations). Lokesh Sharma has collaborated with scholars based in India, Netherlands and United States. Frequent co-authors include Chhagan Lal, B.L. Sharma, Satyabrata Roy, José Antonio Marmolejo-Saucedo, Deepak Gupta, Utku Köse, Durga Prasad Sharma, Sarada Prasad Gochhayat, Dinesh Yadav and Mauro Conti. Their work appears in journals such as Expert Systems with Applications, Sustainability and Wireless Networks.
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.