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Distributed Heterogeneous N-Variant Execution

N-Variant Execution (NVX) systems utilize artificial diversity techniques to enhance software security. The general idea is to run multiple different variants of the same program alongside each other while monitoring their diverging behavior on a malicious input. Existing NVX systems execute diversi...

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Detalles Bibliográficos
Autores principales: Voulimeneas, Alexios, Song, Dokyung, Parzefall, Fabian, Na, Yeoul, Larsen, Per, Franz, Michael, Volckaert, Stijn
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7338185/
http://dx.doi.org/10.1007/978-3-030-52683-2_11
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author Voulimeneas, Alexios
Song, Dokyung
Parzefall, Fabian
Na, Yeoul
Larsen, Per
Franz, Michael
Volckaert, Stijn
author_facet Voulimeneas, Alexios
Song, Dokyung
Parzefall, Fabian
Na, Yeoul
Larsen, Per
Franz, Michael
Volckaert, Stijn
author_sort Voulimeneas, Alexios
collection PubMed
description N-Variant Execution (NVX) systems utilize artificial diversity techniques to enhance software security. The general idea is to run multiple different variants of the same program alongside each other while monitoring their diverging behavior on a malicious input. Existing NVX systems execute diversified program variants on a single host. This means the level of inter-variant diversity will be limited to what a single platform can offer, without costly emulation. This paper presents DMON , a novel distributed NVX design that executes native program variants across multiple heterogeneous hosts. Our approach greatly increases the level of diversity between the simultaneously running variants that can be supported, encompassing different ISAs and ABIs. Our evaluation shows that DMON can provide comparable performance to traditional, non-distributed NVX systems, while enhancing security.
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spelling pubmed-73381852020-07-07 Distributed Heterogeneous N-Variant Execution Voulimeneas, Alexios Song, Dokyung Parzefall, Fabian Na, Yeoul Larsen, Per Franz, Michael Volckaert, Stijn Detection of Intrusions and Malware, and Vulnerability Assessment Article N-Variant Execution (NVX) systems utilize artificial diversity techniques to enhance software security. The general idea is to run multiple different variants of the same program alongside each other while monitoring their diverging behavior on a malicious input. Existing NVX systems execute diversified program variants on a single host. This means the level of inter-variant diversity will be limited to what a single platform can offer, without costly emulation. This paper presents DMON , a novel distributed NVX design that executes native program variants across multiple heterogeneous hosts. Our approach greatly increases the level of diversity between the simultaneously running variants that can be supported, encompassing different ISAs and ABIs. Our evaluation shows that DMON can provide comparable performance to traditional, non-distributed NVX systems, while enhancing security. 2020-06-11 /pmc/articles/PMC7338185/ http://dx.doi.org/10.1007/978-3-030-52683-2_11 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Voulimeneas, Alexios
Song, Dokyung
Parzefall, Fabian
Na, Yeoul
Larsen, Per
Franz, Michael
Volckaert, Stijn
Distributed Heterogeneous N-Variant Execution
title Distributed Heterogeneous N-Variant Execution
title_full Distributed Heterogeneous N-Variant Execution
title_fullStr Distributed Heterogeneous N-Variant Execution
title_full_unstemmed Distributed Heterogeneous N-Variant Execution
title_short Distributed Heterogeneous N-Variant Execution
title_sort distributed heterogeneous n-variant execution
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7338185/
http://dx.doi.org/10.1007/978-3-030-52683-2_11
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