Phishing attackers: prevention and response strategies

Jimmy Fnu ()

Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, 2024, vol. 2, issue 1, 307-318

Abstract: Phishing attacks remain one of the most prevalent and destructive forms of cybercrime, posing significant threats to individuals, organizations, and governments. These attacks, which typically involve fraudulent attempts to steal sensitive information, have evolved in sophistication, exploiting both technological vulnerabilities and human error. This paper reviews various prevention and response strategies for phishing attacks, examining both proactive measures to prevent phishing attempts and reactive responses to mitigate damage post-attack. It discusses common phishing techniques such as email phishing, spear phishing, and smishing, alongside the tools and frameworks designed to combat these threats. Additionally, the paper explores the role of awareness training, multi-factor authentication, and advanced email filtering in preventing phishing attacks. In response strategies, it covers incident reporting, containment actions, and the importance of post-attack analysis for improving organizational resilience. Ultimately, the paper provides a comprehensive overview of best practices for minimizing the risk and impact of phishing, aiming to equip both individuals and organizations with effective countermeasures.

Keywords: Phishing; Cybersecurity; Prevention Strategies; Response Strategies; Phishing Techniques; Spear Phishing; Email Security; Multi-Factor Authentication (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
https://newjaigs.com/index.php/JAIGS/article/view/249 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:das:njaigs:v:2:y:2024:i:1:p:307-318:id:249

Access Statistics for this article

Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023 is currently edited by Justyna Żywiołek

More articles in Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023 from Open Knowledge
Bibliographic data for series maintained by Open Knowledge ().