Esha Sarkar
Esha Sarkar
AI Research Scientist at Intel Corporation
Verified email at
Cited by
Cited by
Security and privacy in cyber-physical systems: A survey of surveys
J Giraldo, E Sarkar, AA Cardenas, M Maniatakos, M Kantarcioglu
IEEE Design & Test 34 (4), 7-17, 2017
Stop-and-Go: Exploring Backdoor Attacks on Deep Reinforcement Learning-based Traffic Congestion Control Systems
Y Wang, E Sarkar, M Maniatakos, SE Jabari
arXiv preprint arXiv:2003.07859, 2020
Facehack: Attacking facial recognition systems using malicious facial characteristics
E Sarkar, H Benkraouda, G Krishnan, H Gamil, M Maniatakos
IEEE Transactions on Biometrics, Behavior, and Identity Science 4 (3), 361-372, 2021
Backdoor suppression in neural networks using input fuzzing and majority voting
E Sarkar, Y Alkindi, M Maniatakos
IEEE Design & Test 37 (2), 103-110, 2020
Fast and scalable private genotype imputation using machine learning and partially homomorphic encryption
E Sarkar, E Chielle, G Gürsoy, O Mazonka, M Gerstein, M Maniatakos
IEEE access 9, 93097-93110, 2021
Privacy-preserving cancer type prediction with homomorphic encryption
E Sarkar, E Chielle, G Gursoy, L Chen, M Gerstein, M Maniatakos
Scientific reports 13 (1), 1661, 2023
I came, I saw, I hacked: Automated generation of process-independent attacks for industrial control systems
E Sarkar, H Benkraouda, M Maniatakos
Proceedings of the 15th ACM asia conference on computer and communications …, 2020
Remote non-intrusive malware detection for plcs based on chain of trust rooted in hardware
PHN Rajput, E Sarkar, D Tychalas, M Maniatakos
2021 IEEE European Symposium on Security and Privacy (EuroS&P), 369-384, 2021
Explainability Matters: Backdoor Attacks on Medical Imaging
M Nwadike, T Miyawaki, E Sarkar, M Maniatakos, F Shamout
AAAI 2021 Workshop: Trustworthy AI for Healthcare, 2020
On automating delayered IC analysis for hardware IP protection
E Sarkar, M Maniatakos
Proceedings of the International Conference on Omni-Layer Intelligent …, 2019
PerDoor: Persistent Backdoors in Federated Learning using Adversarial Perturbations
M Alam, E Sarkar, M Maniatakos
2023 IEEE International Conference on Omni-layer Intelligent Systems (COINS …, 2023
A Subspace Projective Clustering Approach for Backdoor Attack Detection and Mitigation in Deep Neural Networks
Y Wang, W Li, E Sarkar, M Shafique, M Maniatakos, SE Jabari
IEEE Transactions on Artificial Intelligence, 2024
Practical data-in-use protection using binary decision diagrams
O Mazonka, E Sarkar, E Chielle, NG Tsoutsos, M Maniatakos
IEEE Access 8, 23847-23862, 2020
TRAPDOOR: Repurposing neural network backdoors to detect dataset bias in machine learning-based genomic analysis
E Sarkar, C Doumanidis, M Maniatakos
2023 IFIP/IEEE 31st International Conference on Very Large Scale Integration …, 2023
On the Vulnerability of Deep Reinforcement Learning to Backdoor Attacks in Autonomous Vehicles
Y Wang, E Sarkar, SE Jabari, M Maniatakos
Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing: Use …, 2023
Enhancing Security and Privacy of Cyber-Physical Systems Using Machine Learning
E Sarkar
New York University Tandon School of Engineering, 2022
Standardization and Diversity in Industrial Control Systems: Fallacies and Pitfalls from a Cybersecurity Standpoint
D. Tychalas, E. Sarkar, P. Rajput, H. Benkraouda, M. Maniatakos
TC-CPS Newsletter 5 (1), 7-12, 2020
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