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Found 5 papers, 4 papers with code
In Nomine Function: Naming Functions in Stripped Binaries with Neural Networks
We investigate the applicability of tine-tuning (i. e., taking a model already trained on a large generic corpora and retraining it for a specific task).
How Decoding Strategies Affect the Verifiability of Generated Text
A generated sentence is verifiable if it can be corroborated or disproved by Wikipedia, and we find that the verifiability of generated text strongly depends on the decoding strategy.
SAFE: Self-Attentive Function Embeddings for Binary Similarity
We report the results from a quantitative and qualitative analysis that show how SAFE provides a noticeable performance improvement with respect to previous solutions.
Unsupervised Features Extraction for Binary Similarity Using Graph Embedding Neural Networks
Furthermore, we report on a qualitative analysis of functions embeddings.
Android Malware Family Classification Based on Resource Consumption over Time
An important task of malware analysis is the classification of malware samples into known families.
Cryptography and Security
