Aaisha Makkar

936 total citations
34 papers, 549 citations indexed

About

Aaisha Makkar is a scholar working on Information Systems, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Aaisha Makkar has authored 34 papers receiving a total of 549 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Information Systems, 15 papers in Computer Networks and Communications and 14 papers in Artificial Intelligence. Recurrent topics in Aaisha Makkar's work include Spam and Phishing Detection (11 papers), Network Security and Intrusion Detection (8 papers) and Blockchain Technology Applications and Security (6 papers). Aaisha Makkar is often cited by papers focused on Spam and Phishing Detection (11 papers), Network Security and Intrusion Detection (8 papers) and Blockchain Technology Applications and Security (6 papers). Aaisha Makkar collaborates with scholars based in India, United Kingdom and United States. Aaisha Makkar's co-authors include Neeraj Kumar, Jemal Abawajy, Uttam Ghosh, Sahil Garg, Ahmed Ghoneim, M. Shamim Hossain, Ashutosh Kumar Singh, Mubarak Alrashoud, KC Santosh and Asma A. Alhashmi and has published in prestigious journals such as Information Sciences, IEEE Transactions on Industrial Informatics and IEEE Internet of Things Journal.

In The Last Decade

Aaisha Makkar

32 papers receiving 531 citations

Peers

Aaisha Makkar
Xiangyun Tang China
Vineet Kansal India
Yinhao Xiao China
R. K. Pateriya India
Pedro Miguel Sánchez Sánchez Spain
Zhusong Liu China
Ferdous Ahmed Barbhuiya India
Hisham Alasmary Saudi Arabia
Xiangyun Tang China
Aaisha Makkar
Citations per year, relative to Aaisha Makkar Aaisha Makkar (= 1×) peers Xiangyun Tang

Countries citing papers authored by Aaisha Makkar

Since Specialization
Citations

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

Fields of papers citing papers by Aaisha Makkar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aaisha Makkar

This figure shows the co-authorship network connecting the top 25 collaborators of Aaisha Makkar. A scholar is included among the top collaborators of Aaisha Makkar 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 Aaisha Makkar. Aaisha Makkar 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
1.
Makkar, Aaisha, et al.. (2025). A Comprehensive Review of Open-Source Federated Learning Frameworks. Procedia Computer Science. 260. 540–551. 3 indexed citations
2.
Saxena, Deepika, et al.. (2025). Evolutionary learning driven load forecasting and demand response management model for smart grid. Applied Soft Computing. 177. 113169–113169. 3 indexed citations
3.
Wood, Paul, et al.. (2025). Enhancing Healthcare Assistance with a Self-Learning Robotics System: A Deep Imitation Learning-Based Solution. Electronics. 14(14). 2823–2823. 1 indexed citations
4.
Mishra, Vinaytosh, et al.. (2024). A Global Cybersecurity Standardization Framework for Healthcare Informatics. IEEE Journal of Biomedical and Health Informatics. PP. 1–8.
5.
Saxena, Deepika, et al.. (2024). An Intelligent Quantum Cyber-Security Framework for Healthcare Data Management. IEEE Transactions on Automation Science and Engineering. 22. 6884–6895. 5 indexed citations
6.
Makkar, Aaisha & KC Santosh. (2023). SecureFed: federated learning empowered medical imaging technique to analyze lung abnormalities in chest X-rays. International Journal of Machine Learning and Cybernetics. 14(8). 2659–2670. 20 indexed citations
7.
Srivastava, Durgesh, et al.. (2023). A framework for detection of cyber attacks by the classification of intrusion detection datasets. Microprocessors and Microsystems. 105. 104964–104964. 26 indexed citations
8.
Budhiraja, Ishan, et al.. (2023). Advancements in enhancing cyber-physical system security: Practical deep learning solutions for network traffic classification and integration with security technologies. Mathematical Biosciences & Engineering. 21(1). 1527–1553. 4 indexed citations
9.
Santosh, KC, Ayush Goyal, Djamila Aouada, et al.. (2023). Recent Trends in Image Processing and Pattern Recognition. Communications in computer and information science. 2 indexed citations
10.
Makkar, Aaisha. (2022). SecureEngine: Spammer classification in cyber defence for leveraging green computing in Sustainable city. Sustainable Cities and Society. 79. 103658–103658. 6 indexed citations
11.
Budhiraja, Ishan, et al.. (2022). Machine Learning for Detecting Security Attacks on Blockchain using Software Defined Networking. 2022 IEEE International Conference on Communications Workshops (ICC Workshops). 260–264. 16 indexed citations
12.
Makkar, Aaisha, Uttam Ghosh, Pradip Kumar Sharma, & Amir Javed. (2021). A Fuzzy-Based Approach to Enhance Cyber Defence Security for Next-Generation IoT. IEEE Internet of Things Journal. 10(3). 2079–2086. 16 indexed citations
13.
Makkar, Aaisha, Uttam Ghosh, Danda B. Rawat, & Jemal Abawajy. (2021). FedLearnSP: Preserving Privacy and Security Using Federated Learning and Edge Computing. IEEE Consumer Electronics Magazine. 11(2). 21–27. 28 indexed citations
14.
Makkar, Aaisha & Neeraj Kumar. (2021). PROTECTOR: An optimized deep learning-based framework for image spam detection and prevention. Future Generation Computer Systems. 125. 41–58. 16 indexed citations
15.
Makkar, Aaisha, Uttam Ghosh, & Pradip Kumar Sharma. (2021). Artificial Intelligence and Edge Computing-Enabled Web Spam Detection for Next Generation IoT Applications. IEEE Sensors Journal. 21(22). 25352–25361. 21 indexed citations
16.
Makkar, Aaisha, Sahil Garg, Neeraj Kumar, et al.. (2020). An Efficient Spam Detection Technique for IoT Devices Using Machine Learning. IEEE Transactions on Industrial Informatics. 17(2). 903–912. 99 indexed citations
17.
Makkar, Aaisha & Neeraj Kumar. (2020). An efficient deep learning-based scheme for web spam detection in IoT environment. Future Generation Computer Systems. 108. 467–487. 39 indexed citations
18.
Makkar, Aaisha, et al.. (2020). Machine Learning in Cognitive IoT. 11 indexed citations
19.
Makkar, Aaisha, et al.. (2020). SPAMI: A cognitive spam protector for advertisement malicious images. Information Sciences. 540. 17–37. 11 indexed citations
20.
Makkar, Aaisha, Neeraj Kumar, Mohammad S. Obaidat, & Kuei‐Fang Hsiao. (2018). QAIR: Quality Assessment Scheme for Information Retrieval in IoT Infrastructures. abs 1306 2597. 1–6. 7 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.

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