DeepObfusCode: Source Code Obfuscation Through Sequence-to-Sequence Networks

Siddhartha Datta

Abstract:

The paper explores a novel methodology in source code obfuscation through the application of text-based recurrent neural network network (RNN) encoder-decoder models in ciphertext generation and key generation. Sequence-to-sequence models
are incorporated into the model architecture to generate obfuscated code, generate the deobfuscation key, and live execution. Quantitative benchmark comparison to existing obfuscation methods indicate significant improvement in stealth and execution cost for the proposed solution, and experiments regarding the model’s properties yield positive results regarding its character variation, dissimilarity to the original codebase, and consistent length of obfuscated code.

Keywords: sequence-to-sequence network, source code obfuscation, homomorphic encryption

TL;DR: Obfuscate code using seq2seq networks, and execute using the obfuscated code and key pair