2021
DOI: 10.4108/eai.14-9-2021.170956
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Binary Code Similarity Detection through LSTM and Siamese Neural Network

Abstract: Given the fact that many software projects are closed-source, analyzing security-related vulnerabilities at the binary level is quintessential to protect computer systems from attacks of malware. Binary code similarity detection is a potential solution for detecting malware from the binaries generated by the processor. In this paper, we proposed a malware detection mechanism based on the binaries using machine learning techniques. Through utilizing the Recurrent Neural Network (RNN), more specifically Long Sho… Show more

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