Maanak Gupta

3.6k total citations · 2 hit papers
76 papers, 1.8k citations indexed

About

Maanak Gupta is a scholar working on Computer Networks and Communications, Artificial Intelligence and Information Systems. According to data from OpenAlex, Maanak Gupta has authored 76 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Computer Networks and Communications, 31 papers in Artificial Intelligence and 27 papers in Information Systems. Recurrent topics in Maanak Gupta's work include Advanced Malware Detection Techniques (25 papers), Network Security and Intrusion Detection (21 papers) and Access Control and Trust (18 papers). Maanak Gupta is often cited by papers focused on Advanced Malware Detection Techniques (25 papers), Network Security and Intrusion Detection (21 papers) and Access Control and Trust (18 papers). Maanak Gupta collaborates with scholars based in United States, India and Australia. Maanak Gupta's co-authors include Mahmoud Abdelsalam, Ravi Sandhu, Sudip Mittal, Sajad Khorsandroo, Kshitiz Aryal, Lopamudra Praharaj, Farhan Patwa, James Benson, Sai Sree Laya Chukkapalli and Anupam Joshi and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and IEEE Journal on Selected Areas in Communications.

In The Last Decade

Maanak Gupta

67 papers receiving 1.7k citations

Hit Papers

align trajectories

What are hit papers?

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.

From ChatGPT to ThreatGPT: Impact of Generative AI in Cybersecurity and Privacy

2023 346 citations Maanak Gupta, Kshitiz Aryal et al. IEEE Access profile →
Security and Privacy in Smart Farming: Challenges and Opportunities

2020 330 citations Maanak Gupta, Mahmoud Abdelsalam et al. IEEE Access profile →

Peers

Maanak Gupta

AI

CNC

IS

SP

PS

Sudip Mittal United States

Saqib Hakak Canada

Shashank Gupta India

Sachin Sharma India

Mukesh Soni India

Ahmad Karim Pakistan

Othmane Friha Algeria

Randhir Kumar India

Liang Tan China

Konstantinos Demestichas Greece

Sudip Mittal United States

Maanak Gupta

503 ×0.8

AI

557 ×0.9

CNC

468 ×0.8

IS

241 ×0.8

SP

299 ×1.0

PS

Citations per year, relative to Maanak Gupta Maanak Gupta (= 1×) peers Sudip Mittal

Countries citing papers authored by Maanak Gupta

Since Specialization

Citations

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

Fields of papers citing papers by Maanak Gupta

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maanak Gupta

This figure shows the co-authorship network connecting the top 25 collaborators of Maanak Gupta. A scholar is included among the top collaborators of Maanak Gupta 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 Maanak Gupta. Maanak Gupta is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Aryal, Kshitiz, et al.. (2025). SoK: Leveraging Transformers for Malware Analysis. IEEE Transactions on Dependable and Secure Computing. 22(6). 5888–5905. 2 indexed citations

2.

Awaysheh, Feras M., et al.. (2025). SecureFedPROM: A Zero-Trust Federated Learning Approach With Multi-Criteria Client Selection. IEEE Journal on Selected Areas in Communications. 43(6). 2025–2041. 1 indexed citations

3.

Abdelsalam, Mahmoud, et al.. (2025). Explainable Artificial Intelligence (XAI) for Malware Analysis: A Survey of Techniques, Applications, and Open Challenges. IEEE Access. 13. 61611–61640. 3 indexed citations

4.

Gupta, Maanak, et al.. (2025). TT-LoRA MoE: Using Parameter-Efficient Fine-Tuning and Sparse Mixture-Of-Experts. ArXiv.org. 1332–1350.

5.

Gupta, Maanak, et al.. (2025). Enhancing the Security of SDN in 5G: A Hybrid Feature Selection Based Ensemble Machine Learning Framework for Classification of Cyber-Attacks. SN Computer Science. 6(3).

6.

Gupta, Maanak, et al.. (2024). The $$\mathrm {ACAC_{D}}$$ model for mutable activity control and chain of dependencies in smart and connected systems. International Journal of Information Security. 23(5). 3283–3310. 1 indexed citations

7.

Aryal, Kshitiz, et al.. (2024). Explainability Guided Adversarial Evasion Attacks on Malware Detectors. 1–9. 3 indexed citations

8.

Gupta, Maanak, et al.. (2024). Pore-to-Process Automated Production Enhancement Workflows.

9.

Aryal, Kshitiz, et al.. (2024). Explainability-Informed Targeted Malware Misclassification. 1–8. 2 indexed citations

10.

Praharaj, Lopamudra, Deepti Gupta, & Maanak Gupta. (2024). Efficient federated transfer learning-based network anomaly detection for cooperative smart farming infrastructure. SHILAP Revista de lepidopterología. 10. 100727–100727. 4 indexed citations

11.

Krishnan, Ram, et al.. (2023). Utilizing The DLBAC Approach Toward a ZT Score-based Authorization for IoT Systems. 283–285. 1 indexed citations

12.

Abdelsalam, Mahmoud, et al.. (2023). Analyzing and Explaining Black-Box Models for Online Malware Detection. IEEE Access. 11. 25237–25252. 9 indexed citations

13.

Panda, Subhrakanta, et al.. (2023). A Systematic Survey of Multi-Factor Authentication for Cloud Infrastructure. Future Internet. 15(4). 146–146. 15 indexed citations

14.

Tidwell, Michael, et al.. (2023). Wireless Communication of Buried IoT Sensors Utilizing Through the Soil Wireless Power Transfer for Precision Agriculture. 1–5.

15.

Vignesh, M., et al.. (2023). Effect of process parameter on wire cut EDM using RSM method. International Journal on Interactive Design and Manufacturing (IJIDeM). 18(5). 2957–2968. 10 indexed citations

16.

Anbuchezhiyan, G., et al.. (2023). Microstructure and mechanical properties of AZ91D/Si3N4 composites using squeeze casting method. Materials Today Proceedings. 16 indexed citations

17.

Anbuchezhiyan, G., et al.. (2023). Improving the mechanical properties of BN reinforced magnesium composites using vacuum sintering method. Materials Today Proceedings. 5 indexed citations

18.

Aghili, Seyed Farhad, et al.. (2022). MLS-ABAC: Efficient Multi-Level Security Attribute-Based Access Control scheme. Future Generation Computer Systems. 131. 75–90. 29 indexed citations

19.

Awaysheh, Feras M., Mamoun Alazab, Maanak Gupta, Tomás F. Pena, & José C. Cabaleiro. (2020). Next-generation big data federation access control: A reference model. Future Generation Computer Systems. 108. 726–741. 45 indexed citations

20.

Gupta, Maanak, Sai Sree Laya Chukkapalli, Mahmoud Abdelsalam, et al.. (2020). Cyber Attacks on Smart Farming Infrastructure. Maryland Shared Open Access Repository (USMAI Consortium). 135–143. 72 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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