Benjamin Tan

Research Assistant Professor | (he/him)

Department of Electrical and Computer Engineering - NYU Tandon School of Engineering

Ph.D., Computer Systems Engineering (University of Auckland)

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About: Dr. Benjamin Tan (he/him/his) is a Research Assistant Professor in the Department of Electrical and Computer Engineering, New York University (NYU), and works as part of the NYU Center for Cybersecurity. His research work at present focuses on improving the security of computer systems at the hardware level and understanding the implications of emerging machine learning techniques on the IC supply chain and life-cycle. His recent research efforts include projects in collaboration with Intel, and his work has been funded by the National Science Foundation. He earned his Ph.D. at the University of Auckland, New Zealand. At the University of Auckland, he worked as a Professional Teaching Fellow and received a Student’s Choice Top Teacher Award (Top 15 in the Faculty). He has served as a coordinator and adviser for competitions at CSAW (the most comprehensive student-run cybersecurity event in the world). He is a member of IEEE and ACM.

Latest News

  • April 2021 -- I'll be presenting thoughts about Explainable ML for IC Test at VTS 2021 as part of a special session on "Machine Learning for Semiconductor Test and Reliability"

  • January 2021 -- Well done Animesh, a journal paper accepted for IEEE TCAD!

  • December 2021 -- Our paper on Privacy-Preserving GANs is accepted for presentation at AAAI 2021! Well-done Kang! [preprint]

  • August 2020 -- I present an invited paper at MWSCAS 2020 on "Challenges and New Directions for AI and Hardware Security"

  • June 2020 -- I give a (virtual) talk at Intel, as part of their IPAS Tech Sharing Forum

  • March 2020 -- We stay at home

  • December 2019 -- I visit Disneyland (Not work related, but still cool)

  • November 2019 -- I present a talk at the first IEEE International Workshop on Robust and Trustworthy Machine Learning (RTML)

  • September 2019 -- I present a talk at the first ACM/IEEE Workshop on Machine Learning for CAD (MLCAD)

  • January 2019 -- I start working at NYU in the Center for Cybersecurity (with Prof. Ramesh Karri)

  • December 2018 -- I get married! It's the best.

  • November 2018 -- PhD Oral Examination completed successfully! Many thanks to my supervisors: Dr. Morteza Biglari-Abhari and Prof. Zoran Salcic

Writings (Peer Reviewed)

  • A. B. Chowdhury, B. Tan, S. Garg, and R. Karri, "Robust Deep Learning for IC Test Problems", IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (IEEE TCAD)

  • K. Liu, B. Tan, and S. Garg. "Subverting Privacy Preserving GANs: Hiding Secrets in Sanitized Images", 35th AAAI Conference on Artificial Intelligence (AAAI-21) (to appear)

  • H. Yang, S. Zhang, K. Liu, S. Liu, B. Tan, R. Karri, S. Garg, B. Yu, E. F. Y. Young, "Attacking a CNN-based Layout Hotspot Detector Using Group Gradient Method", 26th Asia and South Pacific Design Automation Conference (ASP-DAC), 2021 (to appear)

  • H. Pearce, B. Tan, and R. Karri "DAVE: Deriving Automatically Verilog from English". In Proceedings of the 2020 ACM/IEEE Workshop on Machine Learning for CAD (MLCAD '20). Association for Computing Machinery, New York, NY, USA, 27–32.

  • P. Krishnamurthy, A. B. Chowdhury, B. Tan, F. Khorrami, and R. Karri. "Explaining and Interpreting Machine Learning CAD Decisions: An IC Testing Case Study", In Proceedings of the 2020 ACM/IEEE Workshop on Machine Learning for CAD (MLCAD '20). Association for Computing Machinery, New York, NY, USA, 129–134.

  • K. Liu*, B. Tan*, G. R. Reddy, S. Garg, Y. Makris, R. Karri, "Bias Busters: Robustifying DL-based Lithographic Hotspot Detectors Against Backdooring Attacks," IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (IEEE TCAD) (accepted)

  • K. Liu*, B. Tan*, R. Karri, S. Garg, "Training Data Poisoning in ML-CAD: Backdooring DL-based Lithographic Hotspot Detectors”, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (IEEE TCAD) (accepted)

  • B. Tan, R. Elnaggar, J. Fung, R. Karri, K. Chakrabarty, "Towards Hardware-Based IP Vulnerability Detection and Post-Deployment Patching in Systems-on-Chip", IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (IEEE TCAD),

  • K. Liu, H. Yang, Y. Ma, B. Tan, B. Yu, E. F. Y. Young, R. Karri, S. Garg. 2020. Adversarial Perturbation Attacks on ML-based CAD: A Case Study on CNN-based Lithographic Hotspot Detection. ACM Trans. Des. Autom. Electron. Syst. (ACM TODAES) 25, 5, Article 48 (August 2020), 31 pages.

  • K. Liu*, B. Tan*, R. Karri, S. Garg, “Poisoning the (Data) Well in ML-Based CAD: A Case Study of Hiding Lithographic Hotspots ,” 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE), Grenoble, France, 2020, pp. 306-309

  • A. T. Chen, B. Tan, and K. I. Wang, “Mind the Gap: Insights into Student Perceptions During Peer Assessment of Writing,” in 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), 2018, pp. 161–168. (Outstanding Paper Award)

  • B. Tan, M. Biglari-Abhari, and Z. Salcic, “An Automated Security-Aware Approach for Design of Embedded Systems on MPSoC,” ACM Trans.Embed.Comput.Syst. (ACM TECS), vol. 16, no. 5s, p. 143:20, Sep. 2017.

  • B. Tan, M. Biglari-Abhari, and Z. Salcic, “Towards decentralized system-level security for MPSoC-based embedded applications,” Journal of Systems Architecture (JSA), vol. 80, pp. 41–55, Oct. 2017.

  • B. Tan, M. Biglari-Abhari, and Z. Salcic, “A System-level Security Approach for Heterogeneous MPSoCs,” in Conference on Design & Architectures for Signal & Image Processing (DASIP), Rennes, France, 2016.

Writings (Pre-prints)

  • H. Pearce, B. Tan, R. Karri, "DAVE: Deriving Automatically Verilog from English", arxiv:2009.01026 [cs.SE], Sept. 2020

  • B. Tan, R. Karri, N. Limaye, A. Sengupta, O. Sinanoglu, M. M. Rahman, S. Bhunia, D. Duvalsaint, R. D. Blanton,A. Rezaei, Y. Shen, H. Zhou, L. Li, A. Orailoglu, Z. Han, A. Benedetti, L. Brignone, M. Yasin, J. Rajendran, M. Zuzak, A. Srivastava, U. Guin, C. Karfa, K. Basu, V. V. Menon, M. French, P. Song, F. Stellari, G. Nam, P. Gadfort, A. Althoff, J. Tostenrude, S. Fazzari, E. Breckenfeld, K. Plaks, “Benchmarking at the Frontier of Hardware Security: Lessons from Logic Locking,” arXiv:2006.06806 [cs], Jun. 2020.

  • K. Liu*, B. Tan*, G. R. Reddy, S. Garg, Y. Makris, R. Karri, "Bias Busters: Robustifying DL-based Lithographic Hotspot Detectors Against Backdooring Attacks," arxiv:2004.12492, Apr. 2020

  • A. K. Veldanda, K. Liu, B. Tan, P. Krishnamurthy, F. Khorrami, R. Karri, B. Dolan-Gavitt, S. Garg, "NNoculation: Broad Spectrum and Targeted Treatment of Backdoored DNNs," arXiv:2002.08313 [cs.CR], Feb. 2020

  • K. Liu, H. Yang, Y. Ma, B. Tan, B. Yu, E. F. Y. Young, R. Karri, S. Garg, “Are Adversarial Perturbations a Showstopper for ML-Based CAD? A Case Study on CNN-Based Lithographic Hotspot Detection,” arXiv:1906.10773 [cs, stat], Jun. 2019.

Presentations/Posters

  • IEEE International Workshop on Robust and Trustworthy Machine Learning (RTML)

  • 1st ACM/IEEE Workshop on Machine Learning for CAD

    • "Improving Robustness Against Adversarial Perturbation Attacks on DNNs for CAD", B. Tan, K. Liu, R. Karri and S. Garg

    • "Predetermining CNN-Based Hotspot Detection Results Through Training Data Poisoning", K. Liu, B. Tan, R. Karri and S. Garg

  • 56th Design Automation Conference 2018 (Accepted as a WiP)

    • "Application-specific customization of MPSoC design for improved security", B. Tan, M. Biglari-Abhari, Z. Salcic

My thesis: Improving the Security of Multiprocessor-based Embedded System Designs, (Ph.D. Thesis) University of Auckland