Anand Mudgerikar

518 total citations
11 papers, 266 citations indexed

About

Anand Mudgerikar is a scholar working on Computer Networks and Communications, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Anand Mudgerikar has authored 11 papers receiving a total of 266 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Networks and Communications, 7 papers in Artificial Intelligence and 5 papers in Signal Processing. Recurrent topics in Anand Mudgerikar's work include Network Security and Intrusion Detection (7 papers), Advanced Malware Detection Techniques (5 papers) and Internet Traffic Analysis and Secure E-voting (4 papers). Anand Mudgerikar is often cited by papers focused on Network Security and Intrusion Detection (7 papers), Advanced Malware Detection Techniques (5 papers) and Internet Traffic Analysis and Secure E-voting (4 papers). Anand Mudgerikar collaborates with scholars based in United States, Italy and United Kingdom. Anand Mudgerikar's co-authors include Elisa Bertino, Daniele Midi, Antonino Rullo, Puneet Sharma, Ankush Singla, Ioannis Papapanagiotou, Attila A. Yavuz, Dinesh Verma, Jorge Lobo and J. R. Melrose and has published in prestigious journals such as IEEE Internet of Things Journal, IEEE Transactions on Information Forensics and Security and ACM Transactions on Management Information Systems.

In The Last Decade

Anand Mudgerikar

11 papers receiving 251 citations

Peers

Anand Mudgerikar

CNC

SP

AI

IS

CSE

K. Sundarakantham India

Ibbad Hafeez Finland

Daniele Midi United States

Tim Booij Netherlands

Tomáš Jirsík Czechia

Md. Alamgir Hossain Bangladesh

Ayyoob Hamza Australia

Mayank Swarnkar India

Muhamad Erza Aminanto Indonesia

Houda Jmila France

K. Sundarakantham India

Anand Mudgerikar

270 ×1.2

CNC

129 ×0.9

SP

178 ×1.3

AI

70 ×1.5

IS

29 ×0.7

CSE

Citations per year, relative to Anand Mudgerikar Anand Mudgerikar (= 1×) peers K. Sundarakantham

Countries citing papers authored by Anand Mudgerikar

Since Specialization

Citations

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

Fields of papers citing papers by Anand Mudgerikar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anand Mudgerikar

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

All Works

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11 of 11 papers shown

1.

Lee, Hyunwoo, Ashish Kundu, Xiaofeng Chen, et al.. (2024). ARIoTEDef: Adversarially Robust IoT Early Defense System Based on Self-Evolution against Multi-step Attacks. 5(3). 1–34. 3 indexed citations

2.

Mudgerikar, Anand & Elisa Bertino. (2023). Intelligent Security Aware Routing: Using Model-Free Reinforcement Learning. 1–10. 1 indexed citations

3.

Leung, Kin K., Anand Mudgerikar, Ankush Singla, et al.. (2021). Reinforcement and transfer learning for distributed analytics in fragmented software defined coalitions. Spiral (Imperial College London). 60–60. 1 indexed citations

4.

Mudgerikar, Anand, Elisa Bertino, Jorge Lobo, & Dinesh Verma. (2021). A Security-Constrained Reinforcement Learning Framework for Software Defined Networks. Repositori digital de la UPF (Universitat Pompeu Fabra). 1–6. 7 indexed citations

5.

Mudgerikar, Anand, Puneet Sharma, & Elisa Bertino. (2020). Edge-Based Intrusion Detection for IoT devices. ACM Transactions on Management Information Systems. 11(4). 1–21. 19 indexed citations

6.

Mudgerikar, Anand & Elisa Bertino. (2020). Jarvis: Moving Towards a Smarter Internet of Things. 122–134. 6 indexed citations

7.

Mudgerikar, Anand, Puneet Sharma, & Elisa Bertino. (2019). E-Spion. 493–500. 26 indexed citations

8.

Midi, Daniele, Antonino Rullo, Anand Mudgerikar, & Elisa Bertino. (2017). Kalis — A System for Knowledge-Driven Adaptable Intrusion Detection for the Internet of Things. 656–666. 105 indexed citations

9.

Midi, Daniele, et al.. (2017). Heimdall: Mitigating the Internet of Insecure Things. IEEE Internet of Things Journal. 4(4). 968–978. 57 indexed citations

10.

Yavuz, Attila A., Anand Mudgerikar, Ankush Singla, Ioannis Papapanagiotou, & Elisa Bertino. (2017). Real-Time Digital Signatures for Time-Critical Networks. IEEE Transactions on Information Forensics and Security. 12(11). 2627–2639. 25 indexed citations

11.

Singla, Ankush, Anand Mudgerikar, Ioannis Papapanagiotou, & Attila A. Yavuz. (2015). HAA: Hardware-Accelerated Authentication for internet of things in mission critical vehicular networks. 1298–1304. 16 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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