# In Nomine Function: Naming Functions in Stripped Binaries with Neural Networks

- Published: 17 Dec 2019

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[1] “cxxfilt.” [Online]. Available: https://pypi.org/project/cxxfilt/

[2] A. Vaswan, S. Bengio, E. Brevdo, F. Chollet, A. N. Gomez, S. Gouws, L. Jones, L. Kaiser, N. Kalchbrenner, N. Parmar, R. Sepassi, N. Shazeer, J. Uszkoreit, “Tensor2tensor for neural machine translation,” CoRR, vol. abs/1803.07416, 2018. [Online]. Available: http://arxiv.org/abs/1803.07416

[3] D. Britz, A. Goldie, M. T. Luong, Q. Le, “Massive Exploration of Neural Machine Translation Architectures.” [Online]. Available: https://github.com/google/seq2seq

[4] David, Yaniv and Alon, Uri and Yahav, Eran, “Neural Reverse Engineering of Stripped Binaries,” arXiv preprint arXiv:1902.09122, Tech. Rep., 2019.

[5] S. H. Ding, B. C. Fung, and P. Charland, “Asm2vec: Boosting static representation robustness for binary clone search against code obfuscation and compiler optimization,” in 2019 IEEE Symposium on Security and Privacy (SP). IEEE, 2019, pp. 472-489.

[6] C. Fu, H. Chen, H. Liu, X. Chen, Y. Tian, F. Koushanfar, and J. Zhao, “Coda: An end-to-end neural program decompiler,” in Advances in Neural Information Processing Systems 32, H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alche´-Buc, E. Fox, and R. Garnett, Eds. Curran Associates, Inc., 2019, pp. 3703-3714. [Online]. Available: http://papers.nips.cc/paper/8628-coda-an-end-to-end-neural-program-decompiler.pdf

[7] J. He, P. Ivanov, P. Tsankov, V. Raychev, and M. Vechev, “Debin: Predicting debug information in stripped binaries,” in Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security. ACM, 2018, pp. 1667-1680.

[8] N. Kalchbrenner and P. Blunsom, “Recurrent continuous translation models,” in Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, 2013, pp. 1700-1709. [OpenAIRE]

[9] O. Katz, Y. Olshaker, Y. Goldberg, and E. Yahav, “Towards neural decompilation,” CoRR, vol. abs/1905.08325, 2019. [Online]. Available: http://arxiv.org/abs/1905.08325 [OpenAIRE]

[10] L. Pointal, “TreeTagger.” [Online]. Available: https://treetaggerwrapper.readthedocs.io/en/latest/

[11] J. Lacomis, P. Yin, E. J. Schwartz, M. Allamanis, C. L. Goues, G. Neubig, and B. Vasilescu, “Dire: A neural approach to decompiled identifier naming,” arXiv preprint arXiv:1909.09029, 2019. [OpenAIRE]

[12] Q. Le and T. Mikolov, “Distributed representations of sentences and documents,” in International conference on machine learning, 2014, pp. 1188-1196. [OpenAIRE]

[13] C.-Y. Lin, “Rouge: A package for automatic evaluation of summaries,” in Text summarization branches out, 2004, pp. 74-81.

[14] M. Allamanis, E.T. Barr, P. Devanbu, C. Sutton, “A Survey of Machine Learning for Big Code and Naturalness,” 2018. [Online]. Available: https://arxiv.org/pdf/1709.06182.pdf [OpenAIRE]

[15] L. Massarelli, G. A. Di Luna, F. Petroni, L. Querzoni, and R. Baldoni, “Investigating graph embedding neural networks with unsupervised features extraction for binary analysis,” in Proceedings of the 2nd Workshop on Binary Analysis Research (BAR), 2019.

- 1
- 2

- 1
- 2

[1] “cxxfilt.” [Online]. Available: https://pypi.org/project/cxxfilt/

[2] A. Vaswan, S. Bengio, E. Brevdo, F. Chollet, A. N. Gomez, S. Gouws, L. Jones, L. Kaiser, N. Kalchbrenner, N. Parmar, R. Sepassi, N. Shazeer, J. Uszkoreit, “Tensor2tensor for neural machine translation,” CoRR, vol. abs/1803.07416, 2018. [Online]. Available: http://arxiv.org/abs/1803.07416

[3] D. Britz, A. Goldie, M. T. Luong, Q. Le, “Massive Exploration of Neural Machine Translation Architectures.” [Online]. Available: https://github.com/google/seq2seq

[4] David, Yaniv and Alon, Uri and Yahav, Eran, “Neural Reverse Engineering of Stripped Binaries,” arXiv preprint arXiv:1902.09122, Tech. Rep., 2019.

[5] S. H. Ding, B. C. Fung, and P. Charland, “Asm2vec: Boosting static representation robustness for binary clone search against code obfuscation and compiler optimization,” in 2019 IEEE Symposium on Security and Privacy (SP). IEEE, 2019, pp. 472-489.

[6] C. Fu, H. Chen, H. Liu, X. Chen, Y. Tian, F. Koushanfar, and J. Zhao, “Coda: An end-to-end neural program decompiler,” in Advances in Neural Information Processing Systems 32, H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alche´-Buc, E. Fox, and R. Garnett, Eds. Curran Associates, Inc., 2019, pp. 3703-3714. [Online]. Available: http://papers.nips.cc/paper/8628-coda-an-end-to-end-neural-program-decompiler.pdf

[7] J. He, P. Ivanov, P. Tsankov, V. Raychev, and M. Vechev, “Debin: Predicting debug information in stripped binaries,” in Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security. ACM, 2018, pp. 1667-1680.

[8] N. Kalchbrenner and P. Blunsom, “Recurrent continuous translation models,” in Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, 2013, pp. 1700-1709. [OpenAIRE]

[9] O. Katz, Y. Olshaker, Y. Goldberg, and E. Yahav, “Towards neural decompilation,” CoRR, vol. abs/1905.08325, 2019. [Online]. Available: http://arxiv.org/abs/1905.08325 [OpenAIRE]

[10] L. Pointal, “TreeTagger.” [Online]. Available: https://treetaggerwrapper.readthedocs.io/en/latest/

[11] J. Lacomis, P. Yin, E. J. Schwartz, M. Allamanis, C. L. Goues, G. Neubig, and B. Vasilescu, “Dire: A neural approach to decompiled identifier naming,” arXiv preprint arXiv:1909.09029, 2019. [OpenAIRE]

[12] Q. Le and T. Mikolov, “Distributed representations of sentences and documents,” in International conference on machine learning, 2014, pp. 1188-1196. [OpenAIRE]

[13] C.-Y. Lin, “Rouge: A package for automatic evaluation of summaries,” in Text summarization branches out, 2004, pp. 74-81.

[14] M. Allamanis, E.T. Barr, P. Devanbu, C. Sutton, “A Survey of Machine Learning for Big Code and Naturalness,” 2018. [Online]. Available: https://arxiv.org/pdf/1709.06182.pdf [OpenAIRE]

[15] L. Massarelli, G. A. Di Luna, F. Petroni, L. Querzoni, and R. Baldoni, “Investigating graph embedding neural networks with unsupervised features extraction for binary analysis,” in Proceedings of the 2nd Workshop on Binary Analysis Research (BAR), 2019.

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