Publication
Constrained Adversarial Learning and its applicability to Automated Software Testing: a systematic review
| dc.contributor.author | Vitorino, João | |
| dc.contributor.author | Dias, Tiago | |
| dc.contributor.author | Fonseca, Tiago | |
| dc.contributor.author | Maia, Eva | |
| dc.contributor.author | Praça, Isabel | |
| dc.date.accessioned | 2023-09-05T14:12:55Z | |
| dc.date.available | 2023-09-05T14:12:55Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | Every novel technology adds hidden vulnerabilities ready to be exploited by a growing number of cyber-attacks. Automated software testing can be a promising solution to quickly analyze thousands of lines of code by generating and slightly modifying function-specific testing data to encounter a multitude of vulnerabilities and attack vectors. This process draws similarities to the constrained adversarial examples generated by adversarial learning methods, so there could be significant benefits to the integration of these methods in automated testing tools. Therefore, this systematic review is focused on the current state-of-the-art of constrained data generation methods applied for adversarial learning and software testing, aiming to guide researchers and developers to enhance testing tools with adversarial learning methods and improve the resilience and robustness of their digital systems. The found constrained data generation applications for adversarial machine learning were systematized, and the advantages and limitations of approaches specific for software testing were thoroughly analyzed, identifying research gaps and opportunities to improve testing tools with adversarial attack methods. | pt_PT |
| dc.description.sponsorship | The present work was partially supported by the Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF), within project "Cybers SeC IP" (NORTE-01-0145-FEDER- 000044). This work has also received funding from UIDB/00760/2020. | pt_PT |
| dc.description.version | info:eu-repo/semantics/acceptedVersion | pt_PT |
| dc.identifier.doi | 10.48550/arXiv.2303.07546 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.22/23454 | |
| dc.language.iso | eng | pt_PT |
| dc.relation | NORTE-01-0145-FEDER- 000044 | pt_PT |
| dc.relation | Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | pt_PT |
| dc.subject | Software development | pt_PT |
| dc.subject | Constrained data generation | pt_PT |
| dc.subject | Adversarial attacks | pt_PT |
| dc.subject | Machine learning | pt_PT |
| dc.title | Constrained Adversarial Learning and its applicability to Automated Software Testing: a systematic review | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.awardTitle | Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00760%2F2020/PT | |
| oaire.citation.title | Information and Software Technology | pt_PT |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| person.familyName | Machado Vitorino | |
| person.familyName | Dias | |
| person.familyName | Caló Fonseca | |
| person.familyName | Maia | |
| person.familyName | Praça | |
| person.givenName | João Pedro | |
| person.givenName | Tiago Fontes | |
| person.givenName | Tiago Carlos | |
| person.givenName | Eva | |
| person.givenName | Isabel | |
| person.identifier | HlqCxhoAAAAJ | |
| person.identifier | 2140741 | |
| person.identifier | 2435478 | |
| person.identifier | 299522 | |
| person.identifier.ciencia-id | 3312-592F-B628 | |
| person.identifier.ciencia-id | F510-7CAD-42CD | |
| person.identifier.ciencia-id | 9210-B002-2CB5 | |
| person.identifier.ciencia-id | 4F14-EF83-C4B9 | |
| person.identifier.ciencia-id | C710-4218-1BFF | |
| person.identifier.orcid | 0000-0002-4968-3653 | |
| person.identifier.orcid | 0000-0002-1693-7872 | |
| person.identifier.orcid | 0000-0002-5592-3107 | |
| person.identifier.orcid | 0000-0002-8075-531X | |
| person.identifier.orcid | 0000-0002-2519-9859 | |
| person.identifier.rid | K-8430-2014 | |
| person.identifier.scopus-author-id | 57579914600 | |
| person.identifier.scopus-author-id | 57355096600 | |
| person.identifier.scopus-author-id | 22734900800 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
| relation.isAuthorOfPublication | 4435bb64-8a77-407b-ba18-4833d26e72ae | |
| relation.isAuthorOfPublication | dd54c1b5-5e59-4f2d-8018-15d06880f4bb | |
| relation.isAuthorOfPublication | 83a42983-837d-4db9-8144-2387bc338bf3 | |
| relation.isAuthorOfPublication | 47a108c4-cf8a-46f3-8954-90624174e8fc | |
| relation.isAuthorOfPublication | ee4ecacd-c6c6-41e8-bca1-21a60ff05f50 | |
| relation.isAuthorOfPublication.latestForDiscovery | 47a108c4-cf8a-46f3-8954-90624174e8fc | |
| relation.isProjectOfPublication | db3e2edb-b8af-487a-b76a-f6790ac2d86e | |
| relation.isProjectOfPublication.latestForDiscovery | db3e2edb-b8af-487a-b76a-f6790ac2d86e |