Architecture-independent matching of stripped binary code files using BERT and a Siamese neural network

Architecture-independent matching of stripped binary code files using BERT and a Siamese neural network

The proliferation of IoT devices brings many cyber security challenges. Identifying executable code with known vulnerabilities is one of them, this despite the fact that open source code is commonly used in IoT firmware. Factors that contribute to this challenge include the high usage of heterogeneo...

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Bibliographic Details
Main Author: Lampinen, Kenneth
Other Authors: Informaatioteknologian tiedekunta, Faculty of Information Technology, Informaatioteknologia, Information Technology, Jyväskylän yliopisto, University of Jyväskylä
Format: Master's thesis
Language:eng
Published: 2020
Subjects:
binary file matching
deep learning
Natural Language Processing
NLP
BERT
transformer
LSTM
Siamese network
similarity detection
SSDEEP
SDHASH
Tietojenkäsittelytiede
Computer Science
601
kyberturvallisuus
koneoppiminen
esineiden internet
cyber security
machine learning
Internet of things
Online Access: https://jyx.jyu.fi/handle/123456789/73442

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