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...

Täydet tiedot

Bibliografiset tiedot
Päätekijä: Lampinen, Kenneth
Muut tekijät: Informaatioteknologian tiedekunta, Faculty of Information Technology, Informaatioteknologia, Information Technology, Jyväskylän yliopisto, University of Jyväskylä
Aineistotyyppi: Pro gradu
Kieli:eng
Julkaistu: 2020
Aiheet:
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
Linkit: https://jyx.jyu.fi/handle/123456789/73442

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