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Saurabh Shintre
Saurabh Shintre
Principal Researcher, NortonLifeLock Research Group
Verified email at nortonlifelock.com
Title
Cited by
Cited by
Year
Detecting adversarial samples from artifacts
R Feinman, RR Curtin, S Shintre, AB Gardner
arXiv preprint arXiv:1703.00410, 2017
6342017
" Real" and" complex" network codes: promises and challenges
S Shintre, S Katti, S Jaggi, BK Dey, D Katabi, M Medard
2008 Fourth Workshop on Network Coding, Theory and Applications, 1-6, 2008
382008
{SEAL}: Attack mitigation for encrypted databases via adjustable leakage
I Demertzis, D Papadopoulos, C Papamanthou, S Shintre
29th USENIX Security Symposium (USENIX Security 20), 2433-2450, 2020
352020
How feasible is network coding in current satellite systems?
F Vieira, S Shintre, J Barros
2010 5th Advanced Satellite Multimedia Systems Conference and the 11th …, 2010
342010
Real network codes
S Katti, S Shintre, S Jaggi, D Katabi, M Medard
Proc. Forty-Fifth Annual Allerton Conference, 389-395, 2007
312007
Examining the adoption and abandonment of security, privacy, and identity theft protection practices
Y Zou, K Roundy, A Tamersoy, S Shintre, J Roturier, F Schaub
Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems …, 2020
252020
Probabilistic key distribution in vehicular networks with infrastructure support
J Almeida, S Shintre, M Boban, J Barros
2012 IEEE Global Communications Conference (GLOBECOM), 973-978, 2012
202012
Optimization-guided binary diversification to mislead neural networks for malware detection
M Sharif, K Lucas, L Bauer, MK Reiter, S Shintre
arXiv preprint arXiv:1912.09064, 2019
112019
Systems and methods for protecting computing resources
S Shintre, A Parker-Wood
US Patent 10,015,182, 2018
10*2018
Detecting adversarial samples from artifacts. arXiv 2017
R Feinman, RR Curtin, S Shintre, AB Gardner
arXiv preprint arXiv:1703.00410, 0
10
Detecting adversarial samples from artifacts (2017)
R Feinman, RR Curtin, S Shintre, AB Gardner
arXiv preprint arXiv:1703.00410, 2017
92017
Systems and methods for protecting computing resources
S Shintre, A Parker-Wood
US Patent 10,015,182, 2018
82018
Gradient similarity: An explainable approach to detect adversarial attacks against deep learning
J Dhaliwal, S Shintre
arXiv preprint arXiv:1806.10707, 2018
82018
Verifying that the influence of a user data point has been removed from a machine learning classifier
S Shintre, J Dhaliwal
US Patent 10,225,277, 2019
72019
Making machine learning forget
S Shintre, KA Roundy, J Dhaliwal
Annual Privacy Forum, 72-83, 2019
62019
Probabilistic key distribution in vehicular networks with infrastructure support
JFCDO Barros, JPP De Almeida, M Boban, S Shintre
US Patent 9,276,743, 2016
62016
Malware Makeover: breaking ML-based static analysis by modifying executable bytes
K Lucas, M Sharif, L Bauer, MK Reiter, S Shintre
Proceedings of the 2021 ACM Asia Conference on Computer and Communications …, 2021
52021
Adversarial machine learning at scale
R Feinman, RR Curtin, S Shintre, AB Gardner
technical Report, 2016
52016
Generalized delay-secrecy-throughput trade-offs in mobile ad-hoc networks
S Shintre, L Sassatelli, J Barros
2011 IEEE-APS Topical Conference on Antennas and Propagation in Wireless …, 2011
52011
Detecting adversarial samples from artifacts. arXiv preprint (2017)
R Feinman, RR Curtin, S Shintre, AB Gardner
arXiv preprint arXiv:1703.00410, 2017
42017
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