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- Cabrera Arteaga, Javier, 1992-
(författare)
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Artificial Software Diversification for WebAssembly
- 2022
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- WebAssembly has become the fourth official web language, along with HTML, CSS and JavaScript since 2019. WebAssembly allows web browsers to execute existing programs or libraries written in other languages, such as C/C++ and Rust. In addition, WebAssembly evolves to be part of edge-cloud computing platforms. Despite being designed with security as a premise, WebAssembly is not exempt from vulnerabilities. Therefore, potential vulnerabilities and flaws are included in its distribution and execution, highlighting a software monoculture problem. On the other hand, while software diversity has been shown to mitigate monoculture, no diversification approach has been proposed for WebAssembly. This work proposes software diversity as a preemptive solution to mitigate software monoculture for WebAssembly.Besides, we provide implementations for our approaches, including a generic LLVM superdiversifier that potentially extends our ideas to other programming languages. We empirically demonstrate the impact of our approach by providing Randomization and Multivariant Execution (MVE) for WebAssembly. Our results show that our approaches can provide an automated end-to-end solution for the diversification of WebAssembly programs. The main contributions of this work are:We highlight the lack of diversification techniques for WebAssembly through an exhaustive literature review.We provide randomization and multivariant execution for WebAssembly with the implementation of two tools, CROW and MEWE respectively.We include constant inferring as a new code transformation to generate software diversification for WebAssembly.We empirically demonstrate the impact of our technique by evaluating the static and dynamic behavior of the generated diversification.Our approaches harden observable properties commonly used to conduct attacks, such as static code analysis, execution traces, and execution time.
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| 2. |
- Křepela, Martin, 1987-
(författare)
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Forever Young : Convolution Inequalities in Weighted Lorentz-type Spaces
- 2014
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis is devoted to an investigation of boundedness of a general convolution operator between certain weighted Lorentz-type spaces with the aim of proving analogues of the Young convolution inequality for these spaces.Necessary and sufficient conditions on the kernel function are given, for which the convolution operator with the fixed kernel is bounded between a certain domain space and the weighted Lorentz space of type Gamma. The considered domain spaces are the weighted Lorentz-type spaces defined in terms of the nondecreasing rearrangement of a function, the maximal function or the difference of these two quantities.In each case of the domain space, the corresponding Young-type convolution inequality is proved and the optimality of involved rearrangement-invariant spaces in shown.Furthermore, covering of the previously existing results is also discussed and some properties of the new rearrangement-invariant function spaces obtained during the process are studied.
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