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Over the past decade, side-channels have proven to be significant and practical threats to modern computing systems.
Cache-timing attacks on AES, 2004
Bernstein, D. J · 2004
Earlier work this paper cites.
Adversarial learning
Lowd, D., and Meek, C · 2005
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Cache missing for fun and profit, 2005
Percival, C · 2005
Earlier work this paper cites.
Cache attacks and countermeasures: the case of AES
Osvik, D. A., Shamir, A., and Tromer, E · 2006
Earlier work this paper cites.
Machine learning in adversarial environments, 2010
Laskov, P., and Lippmann, R · 2010
Earlier work this paper cites.
Support vector machines under adversarial label noise
Biggio, B., Nelson, B., and Laskov, P · 2011
Earlier work this paper cites.
Cache games–bringing access-based cache attacks on AES to practice
Gullasch, D., Bangerter, E., and Krenn, S · 2011
Earlier work this paper cites.
Machine learning in side-channel analysis: a first study
Hospodar, G., Gierlichs, B., De Mulder, E., Verbauwhede, I., and Vandewalle, J · 2011
Earlier work this paper cites.
Adversarial machine learning
Huang, L., Joseph, A. D., Nelson, B., Rubinstein, B. I., and Tygar, J · 2011
Earlier work this paper cites.
Poisoning attacks against support vector machines
Biggio, B., Nelson, B., and Laskov, P · 2012
Earlier work this paper cites.
Intelligent machine homicide
Heuser, A., and Zohner, M · 2012
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Adversarial support vector machine learning
Zhou, Y., Kantarcioglu, M., Thuraisingham, B., and Xi, B · 2012
Earlier work this paper cites.
Evasion attacks against machine learning at test time
Biggio, B., Corona, I., Maiorca, D., Nelson, B., Šrndić, N., Laskov, P., Giacinto, G., and Roli, F · 2013
Earlier work this paper cites.
Optimization of power analysis using neural network
Martinasek, Z., Hajny, J., and Malina, L · 2013
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Innovative method of the power analysis
Martinasek, Z., and Zeman, V · 2013
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Intriguing properties of neural networks
Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I., and Fergus, R · 2013
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Security evaluation of pattern classifiers under attack
Biggio, B., Fumera, G., and Roli, F · 2014
Earlier work this paper cites.
Explaining and harnessing adversarial examples
Goodfellow, I. J., Shlens, J., and Szegedy, C · 2014
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Wait a minute! a fast, cross-vm attack on aes
Irazoqui, G., Inci, M. S., Eisenbarth, T., and Sunar, B · 2014
Earlier work this paper cites.
FLUSH+RELOAD: A High Resolution, Low Noise, L3 Cache Side-Channel Attack
Yarom, Y., and Falkner, K · 2014
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Cross-tenant side-channel attacks in PaaS clouds
Zhang, Y., Juels, A., Reiter, M. K., and Ristenpart, T · 2014
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Deep-spying: Spying using smartwatch and deep learning
Beltramelli, T., and Risi, S · 2015
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Quickhpc
Chiappetta, M · 2015
Cited alongside, same era.
Cache template attacks: automating attacks on inclusive last-level caches
Gruss, D., Spreitzer, R., and Mangard, S · 2015
Cited alongside, same era.
The limitations of deep learning in adversarial settings
Papernot, N., McDaniel, P. D., Jha, S., Fredrikson, M., Celik, Z. B., and Swami, A · 2015
Cited alongside, same era.
Exploring the space of adversarial images
Tabacof, P., and Valle, E · 2015
Cited alongside, same era.
Lipnet: Sentence-level lipreading
Assael, Y. M., Shillingford, B., Whiteson, S., and de Freitas, N · 2016
Cited alongside, same era.
Evading classifiers by morphing in the dark
Dang, H., Huang, Y., and Chang, E.-C · 2017
Later among the works it cites.
Note on attacking object detectors with adversarial stickers
Eykholt, K., Evtimov, I., Fernandes, E., Li, B., Song, D., Kohno, T., Rahmati, A., Prakash, A., and Tramer, F · 2017
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Is attacking machine learning easier than defending it?
Goodfellow, I., and Papernot, N · 2017
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AI beats pros at Super Smash Bros
Gordon, R · 2017
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PerfWeb: How to Violate Web Privacy with Hardware Performance Events
Gülmezoglu, B., Zankl, A., Eisenbarth, T., and Sunar, B · 2017
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30 amazing applications of deep learning
Hadad, Y · 2017
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Gruss, D., Maurice, C., Wagner, K., and Mangard, S · 2016
Cited alongside, same era.
Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs
Gulshan, V., Peng, L., Coram, M., Stumpe, M. C., Wu, D., Narayanaswamy, A., Venugopalan, S., Widner, K., Madams, T., Cuadros, J., et al · 2016
Cited alongside, same era.
Cache attacks enable bulk key recovery on the cloud
Inci, M. S., Gulmezoglu, B., Irazoqui, G., Eisenbarth, T., and Sunar, B · 2016
Cited alongside, same era.
Adversarial machine learning at scale
Kurakin, A., Goodfellow, I., and Bengio, S · 2016
Cited alongside, same era.
Armageddon: Cache attacks on mobile devices
Lipp, M., Gruss, D., Spreitzer, R., Maurice, C., and Mangard, S · 2016
Cited alongside, same era.
Delving into transferable adversarial examples and black-box attacks
Liu, Y., Chen, X., Liu, C., and Song, D · 2016
Cited alongside, same era.
Breaking cryptographic implementations using deep learning techniques
Maghrebi, H., Portigliatti, T., and Prouff, E · 2016
Cited alongside, same era.
2 million people-and some dead ones-were impersonated in net neutrality comments
Jon Brodkin · 2017
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Detecting cancer metastases on gigapixel pathology images
Liu, Y., Gadepalli, K., Norouzi, M., Dahl, G. E., Kohlberger, T., Boyko, A., Venugopalan, S., Timofeev, A., Nelson, P. Q., Corrado, G. S., et al · 2017
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Magnet: a two-pronged defense against adversarial examples
Meng, D., and Chen, H · 2017
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Romance novels, generated by artificial intelligence
O’Brien, E · 2017
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Adversarial image perturbation for privacy protection a game theory perspective
Oh, S. J., Fritz, M., and Schiele, B · 2017
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Practical black-box attacks against machine learning
Papernot, N., McDaniel, P., Goodfellow, I., Jha, S., Celik, Z. B., and Swami, A · 2017
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Multiagent Bidirectionally-Coordinated Nets for Learning to Play StarCraft Combat Games
Peng, P., Yuan, Q., Wen, Y., Yang, Y., Tang, Z., Long, H., and Wang, J · 2017
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Foolbox v0.8.0: A python toolbox to benchmark the robustness of machine learning models
Rauber, J., Brendel, W., and Bethge, M · 2017
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One pixel attack for fooling deep neural networks
Su, J., Vargas, D. V., and Kouichi, S · 2017
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Ensemble adversarial training: Attacks and defenses
Tramèr, F., Kurakin, A., Papernot, N., Boneh, D., and McDaniel, P · 2017
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A comparison study on flush+reload and prime+probe attacks on aes using machine learning approaches
Allaf, Z., Adda, M., and Gegov, A · 2018
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Cacheshield: Detecting cache attacks through self-observation
Briongos, S., Irazoqui, G., Malagón, P., and Eisenbarth, T · 2018
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A survey of cyber security countermeasures using hardware performance counters
Foreman, J. C · 2018
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Fcc rules out delaying net neutrality repeal over fake comments
Susan Decker · 2018
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Statistical privacy for streaming traffic
Zhang, X., Hamm, J., Reiter, M. K., and Zhang, Y · 2019
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