Detecting Similar Versions of Software by Learning with Logistic Regression on Binary Opcode Information

Logistic regression is widely used in decision problems to classify inputs through training from the previously known training data. In this paper, we propose an approach to detecting similar versions of software by learning with logistic regression on binary opcode information. Because the binary opcode information has detailed information for executing software on an individual machine, the learning from the binary opcode information can provide effective information in detecting similar versions of software. To evaluate the proposed approach, we experiment with two Java applications. The experimental results showed that the proposed logistic regression model can accurately detect similar versions of software after learning from training data. The proposed logistic regression model is expected to be applied in applications for comparing and detecting similar versions of software.