Research impact

Summary

Over the past decade, our research has impacted academia, industry, and technology globally. The 950+ documented citations on Google Scholar cover a spectrum from high-impact journals and authoritative books to doctoral dissertations at leading universities and patents by multinational corporations.

Our work on behavioral biometrics, continuous authentication, adversarial modeling and countermeasures, and plagiarism detection is cited in flagship venues such as IEEE Symposium on Security & Privacy, USENIX Security Symposium, ACM Conference on Computer and Communications Security (CCS), Network and Distributed System Security Symposium (NDSS), ACM Transactions on Privacy and Security (TOPS) (formerly TISSEC), IEEE Transactions on Information Forensics and Security (TIFS), IEEE Transactions on Dependable and Secure Computing (TDSC), International Joint Conference on Biometrics (IJCB), IEEE Transactions on Biometrics, Behavior, and Identity Science, IEEE Transactions on Mobile Computing, IEEE Communications Surveys & Tutorials, ACM Computing Surveys, and Computer Science Review.  

Besides, our work has been cited in ten patent filings from organizations such as EMC / Dartmouth College, OneSpan, and Assured Information Security, translating academic innovation into applied technologies for mobile, IoT, and biometric security.

Educationally, our work and methods are extended through 40+ graduate theses and taught via 10+ scholarly books, integrating our ideas into global research training and instructional literature.

Quantitative Summary of Scholarly Impact

The citations span multiple domains and publication types, underscoring both academic and applied influence:

• Patents: 10 citing patent filings, demonstrating industrial and technological adoption.

• Theses: 40+ graduate and master’s theses, reflecting global academic use in graduate research.

• Reviews/Surveys: 25+ review and survey articles, marking widespread scholarly influence and methodological adoption.

• Books/Monographs: 10+ academic books/chapters, showing integration into education and advanced reference materials.

Additional categories include 449 journal citations, 62 conference papers, 71 preprints, and 336 entries classified as other.

Industrial and Technological Impact

Our research has directly influenced the design of modern authentication technologies, as evidenced by seven distinct patent families (ten total filings) between 2018 and 2024 that explicitly cite our published work. These patents span innovations in continuous authentication, contextual biometrics, and privacy-preserving verification methods, demonstrating strong industrial adoption of his academic contributions.

Patents Citing Dr. Kumar’s Work

1. Stavrou, A., Murmuria, R., Johnson, R., & Barbara, D. (2019). Active authentication of users (U.S. Patent No. 10,289,819). U.S. Patent and Trademark Office. Cites: CVPRW 2014.

2. Stavrou, A., Murmuria, R., Johnson, R., & Barbara, D. (2020). Active authentication of users (U.S. Patent No. 10,776,463). U.S. Patent and Trademark Office. Cites: CVPRW 2014.

3. Mainali, P. (2024). System, apparatus and method for privacy-preserving contextual authentication (U.S. Patent No. 11,886,558). U.S. Patent and Trademark Office. Cites: CVPRW 2014.

4. Molina-Markham, A. D., Mare, S., Peterson, R., & Kotz, D. (2018). Continuous seamless mobile device authentication using a separate electronic wearable apparatus (U.S. Patent No. 9,961,547). U.S. Patent and Trademark Office. Cites: ACM CCS 2014.

5. Sikder, A. K., Aksu, H., & Uluagac, A. S. (2019). Context-aware intrusion detection method for smart devices with sensors (U.S. Patent No. 10,417,413). U.S. Patent and Trademark Office. Cites: ACM CCS 2014.

6. Baldwin, Jacob; Burnham, Ryan; Dora, Robert; Meyer, Andrew; & Wright, Robert. (2020). Behavioral biometric feature extraction and verification (U.S. Patent No. 10,769,259). U.S. Patent and Trademark Office. Cites: IEEE BTAS 2016, IEEE ISBA 2018.

7. Baldwin, Jacob; Burnham, Ryan; Dora, Robert; Meyer, Andrew; & Wright, Robert. (2020). Behavioral biometric feature extraction and verification (U.S. Patent No. 10,769,260). U.S. Patent and Trademark Office. Cites: IEEE BTAS 2016, IEEE ISBA 2018.

8. Baldwin, Jacob; Burnham, Ryan; Dora, Robert; Meyer, Andrew; & Wright, Robert. (2022). Behavioral biometric feature extraction and verification (U.S. Patent No. 11,449,746). U.S. Patent and Trademark Office. Cites: IEEE BTAS 2016, IEEE ISBA 2018.

9. Lee, Ryan; & Hu, Guangyi. (2024). Devices and methods for smartphone impostor detection using behavioral and environmental data (U.S. Patent No. 12,111,898). U.S. Patent and Trademark Office. Cites: IEEE ISBA 2018.

10. Shchur, Oleksandr; Peteichuk, Andrii; & Oliynyk, Andrii. (2021). Electronic device and operation method thereof (U.S. Patent No. 10,956,604). U.S. Patent and Trademark Office. Cites: ACM TISSEC 2016.

Selected Citing Review and Survey Articles 

Our publications are cited across top-tier survey venues. Below are the citations: 

IEEE Communications Surveys & Tutorials

1.  R. Spreitzer, V. Moonsamy, T. Korak and S. Mangard, "Systematic Classification of Side-Channel Attacks: A Case Study for Mobile Devices," in IEEE Communications Surveys & Tutorials, vol. 20, no. 1, pp. 465-488, Firstquarter 2018, doi: 10.1109/COMST.2017.2779824. Cites ACM CCS 2014

2. Amit Kumar Sikder, Giuseppe Petracca, Hidayet Aksu, Trent Jaeger, and A. Selcuk Uluagac, “A survey on sensor-based threats and attacks to smart devices and applications,” IEEE Communications Surveys & Tutorials, vol. 23, no. 2, pp. 1120–1163, Second quarter 2021, doi: 10.1109/COMST.2021.3051999. Cites ACM CCS 2014

ACM Computing Surveys

1. P. Shrestha and N. Saxena, “An Offensive and Defensive Exposition of Wearable Computing,” ACM Computing Surveys, vol. 50, no. 6, art. no. 92, pp. 1–39, Nov. 2018, doi: 10.1145/3133837. Cites ACM CCS 2014

2. P. Arias-Cabarcos, C. Krupitzer, and C. Becker, “A Survey on Adaptive Authentication,” ACM Computing Surveys, vol. 52, no. 4, art. no. 80, pp. 1–30, 2019, doi: 10.1145/3336117. Cites IEEE CVPRW 2014

3.  L. Gonzalez-Manzano, J. M. De Fuentes, and A. Ribagorda, “Leveraging User-related Internet of Things for Continuous Authentication: A Survey,” ACM Computing Surveys, vol. 52, no. 3, art. no. 53, pp. 1–38, 2019, doi: 10.1145/3314023. Cites IEEE BTAS 2016

4.  C. Wan, L. Wang, and V. V. Phoha, “A Survey on Gait Recognition,” ACM Computing Surveys, vol. 51, no. 5, art. no. 89, pp. 1–35, Sept. 2019, doi: 10.1145/3230633.  Cites IEEE BTAS 2015

5.  R. Mayrhofer and S. Sigg, “Adversary Models for Mobile Device Authentication,” ACM Computing Surveys, vol. 54, no. 9, art. no. 198, pp. 1–35, Dec. 2022, doi: 10.1145/3477601. Cites IEEE BTAS 2015, and ACM TISSEC 2016

6. E. Ellavarason, R. Guest, F. Deravi, R. Sanchez-Riello, and B. Corsetti, “Touch-dynamics based Behavioural Biometrics on Mobile Devices – A Review from a Usability and Performance Perspective,” ACM Computing Surveys, vol. 53, no. 6, art. no. 120, pp. 1–36, Dec. 2021, doi: 10.1145/3394713. Cites  ACM TISSEC 2016

Others

1. N. Sae-Bae, J. Wu, N. Memon, J. Konrad and P. Ishwar, "Emerging NUI-Based Methods for User Authentication: A New Taxonomy and Survey," in IEEE Transactions on Biometrics, Behavior, and Identity Science, vol. 1, no. 1, pp. 5-31, Jan. 2019, doi: 10.1109/TBIOM.2019.2893297.  Cites ACM CCS 2014

2. I. Stylios, S. Kokolakis, O. Thanou, and S. P. Chatzis, “Behavioral biometrics & continuous user authentication on mobile devices: A survey,” Information Fusion, vol. 66, pp. 76–99, Feb. 2021, doi: 10.1016/j.inffus.2020.08.021.  Cites IEEE BTAS 2016

3. A. Ray-Dowling, D. Hou, and S. Schuckers, “Stationary mobile behavioral biometrics: A survey,” Computers & Security, vol. 128, p. 103184, 2023, doi: 10.1016/j.cose.2023.103184. Cites IEEE BTAS 2016, IEEE BTAS 2015, PRL 2022, ISBA 2018, 

4. F. H. Al-Naji and R. Zagrouba, “A survey on continuous authentication methods in Internet of Things environment,” Computer Communications, vol. 163, pp. 109–133, Nov. 2020, doi: 10.1016/j.comcom.2020.09.009. Cites IEEE BTAS 2016

Selected Citing Books 

1. Alloghani, M., Baker, T., Al-Jumeily, D., Hussain, A., Mustafina, J., Aljaaf, A.J. (2020). A Systematic Review on Security and Privacy Issues in Mobile Devices and Systems. In: Gupta, B., Perez, G., Agrawal, D., Gupta, D. (eds) Handbook of Computer Networks and Cyber Security. Springer, Cham. https://doi.org/10.1007/978-3-030-22277-2_23 Cites ACM CCS 2014

2. D. Dasgupta, A. Roy, and A. Nag, Advances in User Authentication, Cham, Switzerland: Springer International Publishing, 2017. DOI: 10.1007/978-3-319-58808-7, Cites IEEE CVPRW2014

3. L. Beinborn and N. Hollenstein, “Cognitive Signals of Language Processing,” in Cognitive Plausibility in Natural Language Processing, Cham, Switzerland: Springer, 2023, pp. 31–60. doi: 10.1007/978-3-031-43260-6_3. Cites EACL 2023

4.  H. M. Ammari and A. J. Chen, “Sensor localization in three-dimensional space: A survey,” in Handbook of Research on Wireless Sensor Network Trends, Technologies, and Applications, IGI Global, 2020, pp. 79–113. Cites WPC Springer 2014

5. P. Singh, S. Kumar, S. K. Gupta, A. K. Rai, and A. Saif, Eds., Wireless Ad-hoc and Sensor Networks: Architecture, Protocols, and Applications, 1st ed. Boca Raton, FL, USA: CRC Press, 2024. doi: 10.1201/9781003528982. Cites WPC Springer 2014

6. M. Stamp, C. A. Visaggio, F. Mercaldo, and F. Di Troia, Eds., Artificial Intelligence for Cybersecurity. Cham, Switzerland: Springer, 2022. doi: 10.1007/978-3-031-04257-7. Cites IEEE IJCB 2021

7. M. Smith-Creasey, Continuous Biometric Authentication Systems: An Overview, SpringerBriefs in Computer Science. Cham, Switzerland: Springer, 2024. doi: 10.1007/978-3-031-49071-2 Cites ACM TISSEC 2016, IEEE ISBA 2018

8. D. Mishra, R. Buyya, P. Mohapatra, and S. Patnaik, Eds., Intelligent and Cloud Computing: Proceedings of ICICC 2019, Volume 1. Cham, Switzerland: Springer, 2021. doi: 10.1007/978-981-15-5971-6 Cites IEEE ISBA 2018

9. B. B. Gupta, G. Martinez Perez, D. P. Agrawal, and D. Gupta, Eds., Handbook of Computer Networks and Cyber Security: Principles and Paradigms. Cham, Switzerland: Springer, 2020. doi: 10.1007/978-3-030-22277-2. Cites ACM CCS 2014

10. R. Chaki, A. Cortesi, K. Saeed, and N. Chaki, Eds., Advanced Computing and Systems for Security: Volume Five. Singapore: Springer, 2018. doi: 10.1007/978-981-13-1232-8. Cites Arxiv 2016 (NDSS Reject)

11. Perera, P., Patel, V.M. (2019). Active Authentication on Mobile Devices. In: Rattani, A., Derakhshani, R., Ross, A. (eds) Selfie Biometrics. Advances in Computer Vision and Pattern Recognition. Springer, Cham. https://doi.org/10.1007/978-3-030-26972-2_12 Cites CVPRW2014

12. Rasnayaka, S., Sim, T. (2020). Towards Wider Adoption of Continuous Authentication on Mobile Devices. In: Bourlai, T., Karampelas, P., Patel, V.M. (eds) Securing Social Identity in Mobile Platforms. Advanced Sciences and Technologies for Security Applications. Springer, Cham. https://doi.org/10.1007/978-3-030-39489-9_13 Cites IEEE BTAS 2016

13. Meng, Y., Zhu, H., Shen, X.(. (2023). Literature Review of Security in Smart Home Network. In: Security in Smart Home Networks. Wireless Networks. Springer, Cham. https://doi.org/10.1007/978-3-031-24185-7_2 Cites ACM CCS 2014

14. Meng, Y., Zhu, H., Shen, X.(. (2023). Privacy Breaches and Countermeasures at Terminal Device Layer. In: Security in Smart Home Networks. Wireless Networks. Springer, Cham. https://doi.org/10.1007/978-3-031-24185-7_3 Cites ACM CCS 2014

Selected Citing Doctoral Theses 

1.  A. Alharbi, “An Authentication Framework for Wearable Devices,” Ph.D. dissertation, Dept. of Computer Engineering and Sciences, Florida Institute of Technology, Melbourne, FL, USA, 2018. Cites IEEE CVPRW2014, 

2. A. Fallahi, “Adversarial Activity Detection and Prediction Using Behavioral Biometrics,” Ph.D. dissertation, Dept. of Electrical Engineering and Computer Science, Syracuse Univ., Syracuse, NY, USA, 2022. Cites IEEE IJCB 2017, IEEE BTAS 2016, 

3. A. Ray-Dowling, “Evaluating Multi-Modality Mobile Behavioral Biometric Fusion Using Public Datasets,” Ph.D. dissertation, Dept. of Electrical and Computer Engineering, Clarkson Univ., Potsdam, NY, USA, 2023. Cites IEEE BTAS 2015, 2016, IEEE ISBA 2018, PRL 2022, 

4. A. P. Nguyen, “Enabling Immersive Experience in 360 Video Streaming with Deep Learning,” Ph.D. dissertation, Dept. of Information Technology, George Mason Univ., Fairfax, VA, USA, 2024. Cites ACM CCS 2014

5. B. Li, “Wrist in Motion: Continuous Authentication via Hand Motions While Clicking and Typing,” Ph.D. dissertation, State Univ. of New York at Binghamton, Binghamton, NY, USA, 2020. Cites IEEE IJCB 2017

6. B. Z. H. Zhao, “Security and Privacy Attacks With and Against Machine Learning,” Ph.D. dissertation, Univ. of New South Wales, Sydney, Australia, 2021. Cites IEEE BTAS 2016

7. C. Wang, “Threats and Opportunities of Mobile Sensing Technology in Personal Privacy and Public Security,” Ph.D. dissertation, Rutgers The State Univ. of New Jersey, School of Graduate Studies, New Brunswick, NJ, USA, 2019. Cites ACM CCS 2014

8. D. Shukla, “Inferences from Interactions with Smart Devices: Security Leaks and Defenses,” Ph.D. dissertation, Syracuse Univ., Syracuse, NY, USA, 2019. Cites ACM CCS 2014, IEEE CVPRW2014, IEEE IJCB 2017

9. E. Ellavarason, “Touch-Screen Behavioural Biometrics on Mobile Devices,” Ph.D. dissertation, Univ. of Kent, Canterbury, United Kingdom, 2020. doi: 10.22024/UniKent/01.02.89861. Cites ACM TISSEC 2016

10. G. Hu, “Secure Cache and Processor Architectures Against Side-Channel, Speculative Execution and Impostor Attacks,” Ph.D. dissertation, Princeton Univ., Princeton, NJ, USA, 2024. Cites IEEE ISBA 2018

11. J. Li, “AI-Based RFID System Security and Privacy: Challenges and Solutions,” Ph.D. dissertation, Arizona State Univ., Tempe, AZ, USA, 2025. Cites ACM CCS 2014

12. J. Shang, “Security and Privacy Issues of Mobile Cyber-Physical Systems,” Ph.D. dissertation, Temple Univ., Philadelphia, PA, USA, 2020. Cites ACM CCS 2014

13. M. Boakes, “A Performance Assessment Framework for Mobile Biometrics,” Ph.D. dissertation, Univ. of Kent, Canterbury, United Kingdom, 2022. doi: 10.22024/UniKent/01.02.97792. Cites IEEE BTAS 2016

14. M.-C. Lee, “A Deep Learning-Based Lightweight Approach for User Identity Recognition on Mobile Devices,” Ph.D. dissertation, National Yang Ming Chiao Tung Univ., Hsinchu, Taiwan, 2020. Cites IEEE CVPR 2014

15. M. E. Fathy, “Sparse Representations and Feature Learning for Image Set Classification and Correspondence Estimation,” Ph.D. dissertation, Univ. of Maryland, College Park, MD, USA, 2018. Cites IEEE CVPR 2014

16. N. Aljohani, “Authentication Based on Disposable Password and Touch Pattern Data,” Ph.D. dissertation, North Carolina Agricultural and Technical State Univ., Greensboro, NC, USA, 2017. Cites IEEE CVPR 2014

17. N. Saleheen, “Behavioral Privacy Risks and Mitigation Approaches in Sharing of Wearable Inertial Sensor Data,” Ph.D. dissertation, The Univ. of Memphis, Memphis, TN, USA, 2020. Cites IEEE CVPR 2014

18. P. Aaby, “Advancing Touch-based Continuous Authentication by Automatically Extracting User Behaviours,” Ph.D. dissertation, Edinburgh Napier Univ., Edinburgh, United Kingdom, 2023. Cites ACM TISSEC 2016, IEEE IJCB 2021

19. P. B. Oza, “Learning from Incomplete and Heterogeneous Data,” Ph.D. dissertation, Johns Hopkins Univ., Baltimore, MD, USA, 2021. Cites IEEE BTAS 2016

20. P. Samangouei, “Machine Learning of Facial Attributes Using Explainable, Secure, and Generative Adversarial Networks,” Ph.D. dissertation, Univ. of Maryland, College Park, MD, USA, 2018. Cites IEEE CVPRW2014

21. P. Shrestha, “New Authentication and Privacy Paradigms in Mobile and Wearable Computing,” Ph.D. dissertation, The Univ. of Alabama at Birmingham, Birmingham, AL, USA, 2019. Cites ACM CCS 2014

22. P. D. de Santos, “Mobile Device Background Sensors: Authentication vs Privacy,” Ph.D. dissertation, Univ. of Kent, Canterbury, United Kingdom, 2024. doi: 10.22024/UniKent/01.02.104800. Cites IEEE BTAS 2016

23. R. Murmuria, “Modeling User Behavior on Smartphones,” Ph.D. dissertation, George Mason Univ., Fairfax, VA, USA, 2017. Cites IEEE CVPRW 2014

24. R. Subramanian, “Orientation Invariance Methods for Inertial Gait,” Ph.D. dissertation, Univ. of South Florida, Tampa, FL, USA, 2018. Cites IEEE CVPRW 2014

25. R. Wijewickrama, “Friend or Foe? Evaluating Sensor-Based Information Side-Channels and Covert Communication Channels on Modern Wearable Devices,” Ph.D. dissertation, The Univ. of Texas at San Antonio, San Antonio, TX, USA, 2024.  Cites IEEE CVPRW 2014

26. S. Gupta, “User Attribution in Digital Forensics Through Modeling Keystroke and Mouse Usage Data Using XGBoost,” Ph.D. dissertation, Purdue Univ., West Lafayette, IN, USA, 2022. Cites IEEE BTAS 2016, IEEE ISBA 2018

27. S. Raponi, “AI-driven Detection of Cybersecurity-related Patterns,” Ph.D. dissertation, Hamad Bin Khalifa Univ., Doha, Qatar, 2021. Cites ACM CCS 2014

28. S. Rasnayaka, “Continuous Authentication for Modern Personal Devices,” Ph.D. dissertation, Dept. of Computer Science, National Univ. of Singapore, Singapore, 2021.  Cites IEEE CVPRW 2014, Cites IEEE BTAS 2016

29.  S. A. S. Lakshminarayan, “Context and Interpretability in Affective Computing Applications,” Ph.D. dissertation, Dept. of Computer Science and Engineering, Univ. of South Florida, Tampa, FL, USA, 2025. Cites IEEE IJCB 2021

30. S. R. K. Gopal, “Offensive and Defensive Analysis of Behavioral Biometrics on Computing Devices,” Ph.D. dissertation, Univ. of Wyoming, Laramie, WY, USA, 2025. Cites ACM CCS 2014

31. T. Chen, “Privacy Analysis of Online and Offline Systems,” Ph.D. dissertation, Oklahoma State Univ., Stillwater, OK, USA, 2019. Cites ACM CCS 2014

32. T. V. Nguyen, “User Identification and Authentication on Emerging Interfaces,” Ph.D. dissertation, New York Univ. Tandon School of Engineering, Brooklyn, NY, USA, 2018. Cites ACM CCS 2014

33. T. M. Wiles, “Establishing Age-Related Changes in Gait Dynamics, Human Movement Variability, and Person Identification,” Ph.D. dissertation, Univ. of Nebraska at Omaha, Omaha, NE, USA, 2025. Cites IEEE BTAS 2015

34. T. W. Peters, “Trustworthy Wireless Personal Area Networks,” Ph.D. dissertation, Dartmouth College, Hanover, NH, USA, 2020. Cites ACM CCS 2014

35. U. Mahbub, “Multi-Modal Active Authentication of Smartphone Users,” Ph.D. dissertation, Univ. of Maryland, College Park, MD, USA, 2018. Cites IEEE CVPRW 2014

36. Xiangyu Liu, “Exploration and Defense of New Privacy Threats on Mobile Devices,” Ph.D. dissertation, The Chinese Univ. of Hong Kong, Hong Kong, 2016. Cites ACM CCS 2014 

37. Ximing Liu, “When Keystroke Meets Password: Attacks and Defenses,” Ph.D. dissertation, Singapore Management University, Singapore, 2019. Cites ACM CCS 2014

38. Y. Chen, “Security and Privacy in Mobile Devices: Novel Attacks and Countermeasures,” Ph.D. dissertation, Arizona State Univ., Tempe, AZ, USA, 2018. Cites ACM CCS 2014

39. Y. Wu, “Neural Network Approach to Vibration Signal Analysis for Wearable Computing,” Ph.D. dissertation, Univ. of New South Wales, Sydney, Australia, 2023. Cites IEEE BTAS 2015

40. Y. Xu, “Toward Robust Video Event Detection and Retrieval Under Adversarial Constraints,” Ph.D. dissertation, The Univ. of North Carolina at Chapel Hill, Chapel Hill, NC, USA, 2016. Cites ACM CCS 2014 

References

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Published Journal Articles

1. [TBIOM’22] P. Mehrotra, M. Agrawal, R. Kumar, and R. R. Shah, “GANTouch: An Attack-Resilient Framework for Touch-based Continuous Authentication System,” IEEE Transactions on Biometrics, Behavior, and Identity Science (T-BIOM), Q1 Journal in Biometrics, Impact Factor: 5.0, 2022.

2. [PRL’22] S. Gupta, R. Kumar, M. Kacimi, and B. Crispo, “IDeAuth: A Novel Behavioral Biometric-based Implicit DeAuthentication Scheme for Smartphones,” Pattern Recognition Letters, Elsevier, Q1, Impact Factor: 3.3, CiteScore: 12.4, 2022.

3. [DTRAP’21] R. Kumar, C. Isik, and V. V. Phoha, “Treadmill Assisted Gait Spoofing (TAGS): An Emerging Threat to Wearable Sensor-based Gait Authentication,” ACM Digital Threats: Research and Practice (DTRAP), Q1, 2021.

4. [TISSEC/TOPS’16] A. Serwadda, V. V. Phoha, Z. Wang, R. Kumar, and D. Shukla, “Toward Robotic Robbery on the Touch Screen,” ACM Transactions on Information and System Security (TISSEC/TOPS), 2016. Supported by DARPA Active Authentication contract FA 8750-13-2-0274 and NSF Award 1527795. In the top 5% of outputs on Altmetric (score: 76).

5. [WPC’14] R. Kumar, S. Kumar, D. Shukla, R. S. Raw, and O. Kaiwartya, “Geometrical Localization Algorithm for Three Dimensional Wireless Sensor Networks,” Springer Wireless Personal Communications, 2014.

Published Conference Articles

1. [IJCB’25] D. H. Roh, R. Kumar, and A. Ngo, “LLM-Assisted Cheating Detection in Korean Language via Keystrokes,” IEEE International Joint Conference on Biometrics (IJCB), 2025. Accept rate: 39.1%.

2. [ASONAM’25] A. Gulati, R. Kumar, V. Agarwal, and A. Sharma, “Weak Links in LinkedIn: Enhancing Fake Profile Detection in the Age of LLMs,” ASONAM, 2025. Accept rate: 25%.

3. [ICMLA’25] D. H. Roh and R. Kumar, “Active Authentication via Korean Keystrokes Under Varying LLM Assistance and Cognitive Contexts,” IEEE ICMLA, 2025. Accept rate: 25%.

4. [UEMCON’25] R. Jemama and R. Kumar, “How Well Do LLMs Imitate Human Writing Style?,” IEEE UEMCON, 2025. Rebira Jemama is a high school student author.

5. [SECRYPT’25] S. Gupta, R. Kumar, K. Raja, B. Chripo, and C. Maple, “Evaluating a Bimodal User Verification Robustness against Synthetic Data Attacks,” SECRYPT, 2025.

6. [IJCB’24a] A. Ngo, R. Kumar, and P. Cao, “Deep Generative Attacks and Countermeasures for Data-Driven Offline Signature Verification,” IEEE IJCB, 2024. Accept rate: 32.2%.

7. [IJCB’24b] D. Kundu, A. Mehta, R. Kumar, N. Lal, A. Anand, A. Singh, and R. R. Shah, “Keystroke Dynamics Against Academic Dishonesty in the Age of LLMs,” IEEE IJCB, 2024. Accept rate: 32.2%.

8. [CCNC’24] A. Kuruvilla, R. Daley, and R. Kumar, “Spotting Fake Profiles in Social Networks via Keystroke Dynamics,” IEEE CCNC, 2024. Accept rate: 24.4%.

9. [PIICON’24] P. Bera, S. R. Pani, and R. Kumar, “Identification of High Impedance Faults Utilizing Recurrence Plots,” IEEE PIICON, 2024.

10. [TAPIA’24] H. Ngo and R. Kumar, “A Touchless Typing Approach Using Apple Augmented Reality Kit and Seq2Seq Learning,” ACM Richard Tapia Conference, 2024. Second Prize, ACM Student Research Competition.

11. [AISec/CCS’23] R. Kumar, C. Isik, and C. K. Mohan, “Dictionary Attack on IMU-based Gait Authentication,” AISec colocated with ACM CCS, 2023. Accept rate: 35.6%.

12. [EACL’23] V. Khurana, Y. Kumar, N. Hollenstein, R. Kumar, and B. Krishnamurthy, “Synthesizing Human Gaze Feedback for Improved NLP Performance,” EACL, 2023. Top-tier NLP venue. Accept rate: 24.1%.

13. [IJCB’22] J. Mo and R. Kumar, “iCTGAN–An Attack Mitigation Technique for Random-vector Attack on Accelerometer-based Gait Authentication Systems,” IEEE IJCB, 2022. Best-reviewed paper. Accept rate: 36.5%.

14. [IJCB’21] P. Mehrotra, M. Agrawal, R. Kumar, and R. R. Shah, “Defending Touch-based Continuous Authentication Systems from Active Adversaries Using Generative Adversarial Networks,” IEEE IJCB, 2021. Best-reviewed paper. Accept rate: 40.2%.

15. [BigMM’20a] S. Rustagi, A. Garg, P. R. Anand, R. Kumar, Y. Kumar, and R. R. Shah, “Touchless Typing using Head Movement-based Gestures,” IEEE BigMM, 2020. Accept rate: 30%.

16. [BigMM’20b] V. Udandarao, M. Agrawal, R. Kumar, and R. R. Shah, “On the Inference of Soft Biometrics from Typing Patterns Collected in a Multi-device Environment,” IEEE BigMM, 2020. Accept rate: 30%.

17. [ISSPIT’18] P. Bera, R. Kumar, and C. Isik, “Identification of Internal Faults in Indirect Symmetrical Phase Shift Transformers Using Ensemble Learning,” IEEE ISSPIT, 2018.

18. [ISBA’18] R. Kumar, P. P. Kundu, and V. V. Phoha, “Continuous Authentication Using One-class Classifiers and their Fusion,” IEEE ISBA, 2018. Supported by NSF Award SaTC 1527795.

19. [IJCB’17] R. Kumar, P. P. Kundu, D. Shukla, and V. V. Phoha, “Continuous User Authentication via Unlabeled Phone Movement Patterns,” IEEE IJCB, 2017. Supported by DARPA Active Authentication contract FA 8750-13-2-0274 and NSF Award SaTC 1527795.

20. [BTAS’16] R. Kumar, V. V. Phoha, and A. Serwadda, “Continuous Authentication of Smartphone Users by Fusing Typing, Swiping, and Phone Movement Patterns,” IEEE BTAS, 2016. Supported by DARPA contract FA 8750-13-2-0274 and NSF Award SaTE 1527795.

21. [BTAS’15] R. Kumar, V. V. Phoha, and A. Jain, “Treadmill Attack on Gait-based Authentication Systems,” IEEE BTAS, 2015. Partly supported by DARPA Active Authentication grant FA8750-13-2-0274.

22. [CVPRW’14] A. Primo, V. V. Phoha, R. Kumar, and A. Serwadda, “Context-aware Active Authentication Using Smartphone Accelerometer Measurements,” IEEE CVPR Workshops (CVPRW), 2014. Highest Impact Paper Award, CVPRW on Biometrics, 2018.

23. [CCS’14] D. Shukla, R. Kumar, A. Serwadda, and V. V. Phoha, “Beware, Your Hands Reveal Your Secrets!,” ACM CCS, 2014. Top security conference. Funded by DARPA. Accept rate: 19.5%, Altmetric Score: 28.