Cybersecurity threats in FinTech: A systematic review.
Saved in:
| Title: | Cybersecurity threats in FinTech: A systematic review. |
|---|---|
| Authors: | Javaheri, Danial1 (AUTHOR) javaheri@korea.ac.kr, Fahmideh, Mahdi2 (AUTHOR) mahdi.fahmideh@usq.edu.au, Chizari, Hassan3 (AUTHOR) hchizari@glos.ac.uk, Lalbakhsh, Pooia4 (AUTHOR) pooia.lalbakhsh@monash.edu, Hur, Junbeom1 (AUTHOR) jbhur@korea.ac.kr |
| Source: | Expert Systems with Applications. May2024, Vol. 241, pN.PAG-N.PAG. 1p. |
| Subjects: | Financial technology, Cyberterrorism, Internet security, Artificial intelligence, Data privacy, Computer crime prevention |
| Abstract: | • Adopting PRISMA methodology to investigate cybersecurity threats in FinTech. • Identifying the most effective defense strategies to negate the threats by examining 74 published papers. • Comparing the threats and defenses from different perspectives, including their impacts and technical details. • Proposing a novel and refined taxonomy of security threats and defense strategies in FinTech. • Recommending future research directions to address existing security gaps in current FinTech systems. The rapid evolution of the Smart-everything movement and Artificial Intelligence (AI) advancements have given rise to sophisticated cyber threats that traditional methods cannot counteract. Cyber threats are extremely critical in financial technology (FinTech) as a data-centric sector expected to provide 24/7 services. This paper introduces a novel and refined taxonomy of security threats in FinTech and conducts a comprehensive systematic review of defensive strategies. Through PRISMA methodology applied to 74 selected studies and topic modeling, we identified 11 central cyber threats, with 43 papers detailing them, and pinpointed 9 corresponding defense strategies, as covered in 31 papers. This in-depth analysis offers invaluable insights for stakeholders ranging from banks and enterprises to global governmental bodies, highlighting both the current challenges in FinTech and effective countermeasures, as well as directions for future research. [ABSTRACT FROM AUTHOR] |
| Copyright of Expert Systems with Applications is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 175345124 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Cybersecurity threats in FinTech: A systematic review. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Javaheri%2C+Danial%22">Javaheri, Danial</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> javaheri@korea.ac.kr</i><br /><searchLink fieldCode="AR" term="%22Fahmideh%2C+Mahdi%22">Fahmideh, Mahdi</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> mahdi.fahmideh@usq.edu.au</i><br /><searchLink fieldCode="AR" term="%22Chizari%2C+Hassan%22">Chizari, Hassan</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> hchizari@glos.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Lalbakhsh%2C+Pooia%22">Lalbakhsh, Pooia</searchLink><relatesTo>4</relatesTo> (AUTHOR)<i> pooia.lalbakhsh@monash.edu</i><br /><searchLink fieldCode="AR" term="%22Hur%2C+Junbeom%22">Hur, Junbeom</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> jbhur@korea.ac.kr</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Expert+Systems+with+Applications%22">Expert Systems with Applications</searchLink>. May2024, Vol. 241, pN.PAG-N.PAG. 1p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Financial+technology%22">Financial technology</searchLink><br /><searchLink fieldCode="DE" term="%22Cyberterrorism%22">Cyberterrorism</searchLink><br /><searchLink fieldCode="DE" term="%22Internet+security%22">Internet security</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Data+privacy%22">Data privacy</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+crime+prevention%22">Computer crime prevention</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: • Adopting PRISMA methodology to investigate cybersecurity threats in FinTech. • Identifying the most effective defense strategies to negate the threats by examining 74 published papers. • Comparing the threats and defenses from different perspectives, including their impacts and technical details. • Proposing a novel and refined taxonomy of security threats and defense strategies in FinTech. • Recommending future research directions to address existing security gaps in current FinTech systems. The rapid evolution of the Smart-everything movement and Artificial Intelligence (AI) advancements have given rise to sophisticated cyber threats that traditional methods cannot counteract. Cyber threats are extremely critical in financial technology (FinTech) as a data-centric sector expected to provide 24/7 services. This paper introduces a novel and refined taxonomy of security threats in FinTech and conducts a comprehensive systematic review of defensive strategies. Through PRISMA methodology applied to 74 selected studies and topic modeling, we identified 11 central cyber threats, with 43 papers detailing them, and pinpointed 9 corresponding defense strategies, as covered in 31 papers. This in-depth analysis offers invaluable insights for stakeholders ranging from banks and enterprises to global governmental bodies, highlighting both the current challenges in FinTech and effective countermeasures, as well as directions for future research. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Expert Systems with Applications is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=175345124 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.eswa.2023.122697 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 1 StartPage: N.PAG Subjects: – SubjectFull: Financial technology Type: general – SubjectFull: Cyberterrorism Type: general – SubjectFull: Internet security Type: general – SubjectFull: Artificial intelligence Type: general – SubjectFull: Data privacy Type: general – SubjectFull: Computer crime prevention Type: general Titles: – TitleFull: Cybersecurity threats in FinTech: A systematic review. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Javaheri, Danial – PersonEntity: Name: NameFull: Fahmideh, Mahdi – PersonEntity: Name: NameFull: Chizari, Hassan – PersonEntity: Name: NameFull: Lalbakhsh, Pooia – PersonEntity: Name: NameFull: Hur, Junbeom IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 09574174 Numbering: – Type: volume Value: 241 Titles: – TitleFull: Expert Systems with Applications Type: main |
| ResultId | 1 |
