Aug 16, 2017 · In this paper, we present a new system called EKLAVYA which trains a recurrent neural network to recover function type signatures from ...

In this paper, we present a new system called EKLAVYA which trains a recurrent neural network to recover function type signatures from disassembled binary code.

In this paper, we present a new system called EKLAVYA which trains a recurrent neural network to recover function type signatures from disassembled binary code.

A new system called E KLAVYA which trains a recurrent neural network to recover function type signatures from disassembled binary code and generalizes well ...

The dataset available from this page is the collection of function type signatures, which includes function banaries, number of arguments and types.

BYTEWEIGHT learns signatures for function starts using a weighted prefix tree, recognizes function starts by matching binary fragments with the signatures ...

Neural nets can learn function type signatures from binaries. ZL Chua, S Shen ... Quantitative verification of neural networks and its security applications.

Liang, “Neural nets can learn function type signatures from binaries,” in Proc. 26th USENIX Secur. Symp., 2017, pp. 99–116. [11] Z. Xu, C. Wen, and S. Qin ...

A collection of papers, tools about type inferring, variable renaming, function name inferring on stripped binary executables.

• Recurrent Neural Networks (RNNs) can solve the function identification problem more efficiently and accurately than previous state-of-the-art ML and ...