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.
Deep Learning Approach for Intelligent Intrusion Detection System
20191.1k citationsR. Vinayakumar, Mamoun Alazab et al.IEEE Accessprofile →
Stock price prediction using LSTM, RNN and CNN-sliding window model
2017595 citationsR. Vinayakumar, K. P. Soman et al.profile →
Applying convolutional neural network for network intrusion detection
2017361 citationsR. Vinayakumar, K. P. Soman et al.profile →
Robust Intelligent Malware Detection Using Deep Learning
2019338 citationsR. Vinayakumar, Mamoun Alazab et al.IEEE Accessprofile →
A Visualized Botnet Detection System Based Deep Learning for the Internet of Things Networks of Smart Cities
2020222 citationsR. Vinayakumar, Mamoun Alazab et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
Countries citing papers authored by R. Vinayakumar
Since
Specialization
Citations
This map shows the geographic impact of R. Vinayakumar'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 R. Vinayakumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites R. Vinayakumar more than expected).
This network shows the impact of papers produced by R. Vinayakumar. 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 R. Vinayakumar. The network helps show where R. Vinayakumar may publish in the future.
Co-authorship network of co-authors of R. Vinayakumar
This figure shows the co-authorship network connecting the top 25 collaborators of R. Vinayakumar.
A scholar is included among the top collaborators of R. Vinayakumar 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 R. Vinayakumar. R. Vinayakumar is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Simon, Ann M., et al.. (2019). Shallow Cnn with Lstm layer for tuberculosis detection in microscopic image. International Journal of Recent Technology and Engineering (IJRTE). 7.5 indexed citations
Vinayakumar, R., et al.. (2019). Performance comparison of machine learning algorithms for malaria detection using microscopic images. 6(1).14 indexed citations
5.
Vinayakumar, R., Mamoun Alazab, K. P. Soman, Prabaharan Poornachandran, & Sitalakshmi Venkatraman. (2019). Robust Intelligent Malware Detection Using Deep Learning. IEEE Access. 7. 46717–46738.338 indexed citations breakdown →
Vinayakumar, R., et al.. (2018). DeepAnti-PhishNet: Applying deep neural networks for phishing email detection CEN-AISecurity@IWSPA-2018. CEUR Workshop Proceedings. 2124.7 indexed citations
8.
Vinayakumar, R., et al.. (2018). Distributed representation using target classes: Bag of tricks for security and privacy analytics Amrita-NLP@IWSPA-2018. CEUR Workshop Proceedings. 2124.2 indexed citations
9.
Vinayakumar, R., et al.. (2018). Detecting phishing E-mail using machine learning techniques CEN-SecureNLP. CEUR Workshop Proceedings. 2124.3 indexed citations
10.
Vinayakumar, R., et al.. (2018). PED-ML: Phishing email detection using classical machine learning techniques CENSec@Amrita. CEUR Workshop Proceedings. 2124.4 indexed citations
11.
Vinayakumar, R., et al.. (2018). A machine learning approach towards phishing email detection CEN-Security@IWSPA 2018. CEUR Workshop Proceedings. 2124.4 indexed citations
12.
Vinayakumar, R., et al.. (2018). Machine learning based phishing E-mail detection Security-CEN@Amrita. CEUR Workshop Proceedings. 2124.2 indexed citations
Vinayakumar, R., et al.. (2015). AMRITA-CEN@SAIL2015: Sentiment analysis in Indian languages. Lecture notes in computer science. 9468.2 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.