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Textual Entailment for Cybersecurity: an Applicative Case

Livio Robaldo Orcid Logo, Giovanni Siragusa, Luigi Di Caro, Andrea Violato

Journal of Applied Logics, Volume: 8, Issue: 4, Pages: 975 - 992

Swansea University Author: Livio Robaldo Orcid Logo

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Abstract

Recognizing Textual Entailment (RTE) is the task of recognizing the relation between two sentences, in order to measure whether and to what extent one of the two is inferred from the other. It is used in many Natural Language Processing (NLP) tasks. In the last decades, with the digitization of many...

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Published in: Journal of Applied Logics
ISSN: 2631-9810 2631-9829
Published: College Publications 2021
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URI: https://cronfa.swan.ac.uk/Record/cronfa56726
first_indexed 2021-04-23T13:51:31Z
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spelling 2023-04-05T14:29:58.6719345 v2 56726 2021-04-23 Textual Entailment for Cybersecurity: an Applicative Case b711cf9f3a7821ec52bd1e53b4f6cf9e 0000-0003-4713-8990 Livio Robaldo Livio Robaldo true false 2021-04-23 HRCL Recognizing Textual Entailment (RTE) is the task of recognizing the relation between two sentences, in order to measure whether and to what extent one of the two is inferred from the other. It is used in many Natural Language Processing (NLP) tasks. In the last decades, with the digitization of manylegal documents, NLP applied to the legal domain has became prominent, due to the need of knowing which norms are complied with in case other norms are. In this context, from a set of obligations that are known to be complied with, RTE may be used to infer which other norms are complied with as well. We propose a dataset, regarding cybersecurity controls, for RTE on the legal domain. The dataset has been constructed using information available online, provided by domain experts from NIST (https://www.nist.gov). Journal Article Journal of Applied Logics 8 4 975 992 College Publications 2631-9810 2631-9829 4 5 2021 2021-05-04 https://www.collegepublications.co.uk/ifcolog/?00046 COLLEGE NANME Hillary Rodham Clinton Law School COLLEGE CODE HRCL Swansea University Not Required 2023-04-05T14:29:58.6719345 2021-04-23T14:47:06.9315154 Faculty of Humanities and Social Sciences Hilary Rodham Clinton School of Law Livio Robaldo 0000-0003-4713-8990 1 Giovanni Siragusa 2 Luigi Di Caro 3 Andrea Violato 4 56726__19979__abb11b2a36c14f97abcf40a0bcf4c8e3.pdf 56726.pdf 2021-05-24T13:13:58.7695725 Output 1255305 application/pdf Version of Record true true eng
title Textual Entailment for Cybersecurity: an Applicative Case
spellingShingle Textual Entailment for Cybersecurity: an Applicative Case
Livio Robaldo
title_short Textual Entailment for Cybersecurity: an Applicative Case
title_full Textual Entailment for Cybersecurity: an Applicative Case
title_fullStr Textual Entailment for Cybersecurity: an Applicative Case
title_full_unstemmed Textual Entailment for Cybersecurity: an Applicative Case
title_sort Textual Entailment for Cybersecurity: an Applicative Case
author_id_str_mv b711cf9f3a7821ec52bd1e53b4f6cf9e
author_id_fullname_str_mv b711cf9f3a7821ec52bd1e53b4f6cf9e_***_Livio Robaldo
author Livio Robaldo
author2 Livio Robaldo
Giovanni Siragusa
Luigi Di Caro
Andrea Violato
format Journal article
container_title Journal of Applied Logics
container_volume 8
container_issue 4
container_start_page 975
publishDate 2021
institution Swansea University
issn 2631-9810
2631-9829
publisher College Publications
college_str Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str Hilary Rodham Clinton School of Law{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}Hilary Rodham Clinton School of Law
url https://www.collegepublications.co.uk/ifcolog/?00046
document_store_str 1
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description Recognizing Textual Entailment (RTE) is the task of recognizing the relation between two sentences, in order to measure whether and to what extent one of the two is inferred from the other. It is used in many Natural Language Processing (NLP) tasks. In the last decades, with the digitization of manylegal documents, NLP applied to the legal domain has became prominent, due to the need of knowing which norms are complied with in case other norms are. In this context, from a set of obligations that are known to be complied with, RTE may be used to infer which other norms are complied with as well. We propose a dataset, regarding cybersecurity controls, for RTE on the legal domain. The dataset has been constructed using information available online, provided by domain experts from NIST (https://www.nist.gov).
published_date 2021-05-04T14:09:25Z
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