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Data leaks and suspicious behavior detection in smart home using Taint Analysis

Dumoulin, Antoine ; Baillieux, Valentin
(2023)

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Details

Supervisors
Riviere, Etienne
Faculty
Ecole polytechnique de Louvain
Degree label
Master [120] en sciences informatiques, à finalité spécialisée
Abstract
The proliferation of modern technology, including smartphones, computers, and Internet of Things (IoT) devices, has revolutionized convenience and connectivity. However, this advancement comes with a trade-off between user comfort and the risk of data leakage and privacy breaches. This master's thesis focuses on privacy issues within smart homes. The objective is to provide a proof of concept of whether dynamic taint analysis on its own is a viable solution to identify and prevent sensitive data leaks within a smart home environment. To achieve this, we created TaintWasm a dynamic taint analysis for WebAssembly binaries. TaintWasm is based on Wasabi a dynamic analysis framework for WebAssembly. The research unveils that efficient dynamic taint analysis is challenging to implement in many aspects. The Most notable ones are real-time analysis, portability and implicit flow handling. Though some results are encouraging and dynamic taint analysis arises as a strong asset for such systems. It appears that to be a viable solution it should be combined with other techniques to overcome real-world limitations.