Dr. Shruti Bhilare is an assistant professor in Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar since July 2019. She received her Ph.D. degree in Computer Science and Engineering from Indian Institute of Technology Indore, India. Her research interests include pattern recognition and image processing with focus on biometric applications. She received her B.E. and M.E. (with specialization in Software Engineering) degrees in Computer Engineering from Institute of Engineering and Technology, Devi Ahilya university Indore, India, in 2009 and 2011, respectively.

Biometrics, Pattern Recognition, Image Processing

Journals:

• S. Sharma, R. Joshi, S. Bhilare, M.V. Joshi, “Robust Adversarial Defense: An Analysis on Use of Auto-Inpainting”, SN Computer Science 6 (1), pp. 17, 2024.
• U. Patel, S Bhilare, A Hati, “Enhancing cross-domain transferability of black-box adversarial attacks on speaker recognition systems using linearized backpropagation”, Pattern Analysis and Applications, 27(2), pp. 60, 2024.
• S. Bhilare, V. Kanhangad, N. Chaudhari, “A study on vulnerability and presentation attack detection in palmprint verification system”, Pattern Analysis And Applications (PAAA), 21(3), pp. 769-782, 2018.
• S. Bhilare, G. Jaswal, V. Kanhangad, A. Nigam, “Single sensor hand-vein multimodal biometric recognition using multiscale deep pyramidal approach”, Machine Vision and Applications, 29(8), pp. 1269-1286, 2018.
• S. Bhilare, V. Kanhangad, “Securing palm-vein sensors against presentation attacks using image noise residuals”, SPIE Journal of Electronic Imaging, 27(5), pp. 053028, 2018.

Conferences:

• U.Patel, A. Hati and S. Bhilare, "Black-box adversarial defense for enhancing robustness in speaker recognition systems with multimodel consensus", Proc. 17th International Conference on Machine Vision (ICMV), Edinburgh, UK, October 2024.
• S. Bhilare and A. Hati, "Fooling Face Recognition Systems through Physical Adversarial Attack", Proc. 9th IAPR International Conference on Computer Vision & Image Processing (CVIP), Communications in Computer and Information Science, Kancheepuram, India, Dec 2024.
• U. Patel, A. Hati and S. Bhilare, "Black-box Adversarial Defense for Enhancing Robustness in Speaker Recognition Systems with Multi-model Consensus", Proc. 17th International Conference on Machine Vision (ICMV), Edinburgh, UK, Oct 2024.
• U. Patel, S. Bhilare, A. Hati, “Enhancing transferability of adversarial audio in speaker recognition systems”, Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA), Alicante, Spain, June, 2023, pp. 617-628.
• S. Sharma, R. Joshi, S. Bhilare, M.V. Joshi, “Robust Adversarial Defence: Use of Auto-inpainting”, International Conference on Computer Analysis of Images and Patterns (CAIP), Limassol, Cyprus, Sept. 2023, pp. 110-119.
• M. Shah, S. Mandal, S. Bhilare, A. Hati, “Increasing Transferability by Imposing Linearity and Perturbation in Intermediate Layer with Diverse Input Patterns”, In Proc. International conference on Signal processing and Communications (SPCOM), Bangalore, July 2022, pp. 1-5.
• S. Gajjar , A. Hati , S. Bhilare, S. Mandal, “Generating Targeted Adversarial Attacks and Assessing their Effectiveness in Fooling Deep Neural Networks”, In Proc. International conference on Signal processing and Communications, (SPCOM) Bangalore, July 2022, pp. 1-5.
• V. Kanhangad, S. Bhilare, P. Garg, P. Singh and N. Chaudhari, "Anti-spoofing for display and print attacks on palmprint verification systems" in proc. Society of Photo-optical Instrument Engineers (SPIE) Defense + Security, Baltimore, MD, U.S.A, May 2015, pp. 94570E-94570E.
• I. Patil, S. Bhilare and V. Kanhangad, "Assessing vulnerability of dorsal hand-vein verification system to spoofing attacks using smartphone camera" in proc. IEEE international conference on Identity, Security and Behaviour Analysis (ISBA), Sendai, Japan, March 2016, pp. 1-6.
• S. Bhilare, V. Kanhangad and N. Chaudhari, “Histogram of oriented gradients based presentation attack detection in dorsal hand-vein biometric system” in proc. IAPR Machine Vision and Applications (MVA), Nagoya, Japan, May 2017, pp. 39-42
• Z. Boulkenafet, J. Komulainen, Z. Akhtar, A. Benlamoudi, S. Bekhouche, A. Ouafi, F. Dornaika, A. Taleb-Ahmed ,L. Qin, F. Peng, L.B. Zhang, M. Long, S. Bhilare, V. Kanhangad, Costa-Pazo, E. Vazquez-Fernandez, D.P´erez-Cabo, J. J. Moreira-P´erez, D. Gonz´alez- Jim´enez , A. Mohammadi, S.Bhattacharjee, S.Marcel, S.Volkova, Y. Tang, N. Abe, L. Li, X. Feng, Z. Xia, X. Jiang, S. Liu, R. Shao, P. C. Yuen, W. Almeida, F.Andal´o, R. Padilha, G. Bertocco, W. Dias, J. Wainer, R. Torres, A. Rocha, M. A. Angeloni, G. Folego, A.Godoy and A. Hadid, “A competition on generalized software-based face presentation attack detection in mobile scenarios”, in proc. IEEE international joint conference on biometrics (IJCB), Denver, Colorado, U.S.A., October 2017, pp. 688-696
• S.Garg, S. Bhilare, V.Kanhangad, “Subband Analysis for Performance Improvement of Replay Attack Detection in Speaker Verification Systems,”, in proc. IEEE international conference on Identity, Security and Behaviour Analysis (ISBA), 2019, pp. 1-7

Workshops:

• Anchor institute program (AIP) on Introduction to Machine Learning with Python for faculties, professionals and students weekly during January 5 – April 26, 2024.
• Workshop on Machine Learning and Deep Learning was organized for faculties, ISRO scientists, other professionals and students during September 14 - 18, 2020 in online mode.

• Machine Learning
• Biometric Security
• Web Programming
• Systems Programming
• Computer Organization and Programming
• C Programming