Evasion Attacks against Machine Learning at Test Time

LeCun, Y., Jackel, L., Bottou, L., Brunot, A., Cortes, C., Denker, J., Drucker, H., Guyon, I., Müller, U., Säckinger, E., Simard, P., Vapnik, V.: Comparison of learning algorithms for handwritten digit recognition. In: Int’l Conf. on Art. Neu. Net. pp. 53–60 (1995)

1995

Earlier work this paper cites.

Platt, J.: Probabilistic outputs for support vector machines and comparison to regularized likelihood methods. In: Smola, A., Bartlett, P., Schölkopf, B., Schuurmans, D. (eds.) Adv. in L. M. Class. pp. 61–74 (2000)

2000

Earlier work this paper cites.

Golland, P.: Discriminative direction for kernel classifiers. In: Neu. Inf. Proc. Syst. (NIPS). pp. 745–752 (2002)

2002

Earlier work this paper cites.

Dalvi, N., Domingos, P., Mausam, Sanghai, S., Verma, D.: Adversarial classification. In: 10th ACM SIGKDD Int’l Conf. on Knowl. Discovery and Data Mining (KDD). pp. 99–108. (2004)

2004

Earlier work this paper cites.

Lowd, D., Meek, C.: Adversarial learning. In: Press, A. (ed.) Proc. of the Eleventh ACM SIGKDD Int’l Conf. on Knowl. Disc. and D. Mining (KDD). pp. 641–647. Chicago, IL. (2005)

2005

Earlier work this paper cites.

Barreno, M., Nelson, B., Sears, R., Joseph, A.D., Tygar, J.D.: Can machine learning be secure? In: ASIACCS ’06: Proc. of the 2006 ACM Symp. on Information, computer and comm. security. pp. 16–25. ACM, New York, NY, USA (2006)

2006

Earlier work this paper cites.

Fogla, P., Sharif, M., Perdisci, R., Kolesnikov, O., Lee, W.: Polymorphic blending attacks. In: Proc. 15th Conf. on USENIX Sec. Symp. USENIX Association, CA, USA (2006)

2006

Earlier work this paper cites.

Globerson, A., Roweis, S.T.: Nightmare at test time: robust learning by feature deletion. In: Cohen, W.W., Moore, A. (eds.) Proc. of the 23rd Int’l Conf. on Mach. Learn. vol. 148, pp. 353–360. ACM (2006)

2006

Earlier work this paper cites.

Nelson, B., Barreno, M., Chi, F.J., Joseph, A.D., Rubinstein, B.I.P., Saini, U., Sutton, C., Tygar, J.D., Xia, K.: Exploiting machine learning to subvert your spam filter. In: LEET’08: Proc. of the 1st Usenix Work. on L.-S. Exp. and Emerg. Threats. pp. 1–9. USENIX Association, Berkeley, CA, USA (2008)

2008

Earlier work this paper cites.

Kolcz, A., Teo, C.H.: Feature weighting for improved classifier robustness. In: Sixth Conf. on Email and Anti-Spam (CEAS). Mountain View, CA, USA (2009)

2009

Cited alongside, same era.

Laskov, P., Kloft, M.: A framework for quantitative security analysis of machine learning. In: AISec ’09: Proc. of the 2nd ACM works. on Sec. and art. int. pp. 1–4. ACM, New York, NY, USA (2009)

2009

Cited alongside, same era.

Biggio, B., Fumera, G., Roli, F.: Multiple classifier systems for robust classifier design in adversarial environments. Int’l J. of Machine Learning and Cybernetics 1(1), 27–41 (2010)

2010

Cited alongside, same era.

Dekel, O., Shamir, O., Xiao, L.: Learning to classify with missing and corrupted features. Mach. Learn. 81, 149–178 (2010)

2010

Cited alongside, same era.

Kloft, M., Laskov, P.: Online anomaly detection under adversarial impact. In: Proc. of the 13th Int’l Conf. on Art. Int. and Stats. (AISTATS). pp. 405–412 (2010)

Huang, L., Joseph, A.D., Nelson, B., Rubinstein, B., Tygar, J.D.: Adversarial machine learning. In: 4th ACM Workshop on Art. Int. and Sec. (AISec 2011). pp. 43–57. Chicago, IL, USA (2011)

2011

Later among the works it cites.

Biggio, B., Nelson, B., Laskov, P.: Poisoning attacks against support vector machines. In: Langford, J., Pineau, J. (eds.) 29th Int’l Conf. on Mach. Learn. (2012)

2012

Later among the works it cites.

Brückner, M., Kanzow, C., Scheffer, T.: Static prediction games for adversarial learning problems. J. Mach. Learn. Res. 13, 2617–2654 (2012)

2012

Later among the works it cites.

Maiorca, D., Giacinto, G., Corona, I.: A pattern recognition system for malicious pdf files detection. In: MLDM. pp. 510–524 (2012)

2012

Later among the works it cites.

Nelson, B., Rubinstein, B.I., Huang, L., Joseph, A.D., Lee, S.J., Rao, S., Tygar, J.D.: Query strategies for evading convex-inducing classifiers. J. Mach. Learn. Res. 13, 1293–1332 (2012)