The COVID-19 pandemic coincided with an equally-threatening scamdemic: a global epidemic of scams and frauds. The unprecedented cybersecurity concerns emerged during the pandemic sparked a torrent of research to investigate cyber-attacks and to propose solutions and countermeasures. Within the scamdemic, phishing was by far the most frequent type of attack. This survey paper reviews, summarises, compares and critically discusses 54 scientific studies and many reports by governmental bodies, security firms and the grey literature that investigated phishing attacks during COVID-19, or that proposed countermeasures against them. Our analysis identifies the main characteristics of the attacks and the main scientific trends for defending against them, thus highlighting current scientific challenges and promising avenues for future research and experimentation.
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http://dx.doi.org/10.1049/ise2.12073 | DOI Listing |
PeerJ Comput Sci
November 2024
Department of Computer Science, Taif University, Taif, Saudi Arabia.
The increased sophistication and frequency of phishing attacks that target organizations necessitate a comprehensive cyber security strategy to handle phishing attacks from several perspectives, such as the detection of phishing and testing of users' awareness. Through a systematic review of 163 research articles, we analyzed the organization-oriented phishing research to categorize current research and identify future opportunities. We find that a notable number of studies concentrate on phishing detection and awareness while other layers of protection are overlooked, such as the mitigation of phishing.
View Article and Find Full Text PDFFront Artif Intell
October 2024
Department of Environmental Health, Harvard T H Chan School of Public Health, Boston, MA, United States.
Life has become more comfortable in the era of advanced technology in this cutthroat competitive world. However, there are also emerging harmful technologies that pose a threat. Without a doubt, phishing is one of the rising concerns that leads to stealing vital information such as passwords, security codes, and personal data from any target node through communication hijacking techniques.
View Article and Find Full Text PDFPLoS One
October 2024
Faculty of Criminal Justice and Security, University of Maribor, Ljubljana, Slovenia.
Cyberattacks pose a significant business risk to organizations. Although there is ample literature focusing on why people pose a major risk to organizational cybersecurity and how to deal with it, there is surprisingly little we know about cyber and information security decision-makers who are essentially the people in charge of setting up and maintaining organizational cybersecurity. In this paper, we study cybersecurity awareness of cyber and information security decision-makers, and investigate factors associated with it.
View Article and Find Full Text PDFSci Rep
September 2024
National Institute of Digital Technology and Digital Transformation, Ministry of Information and Communications, Hanoi, Vietnam.
To enhance the effectiveness of the Advanced Persistent Threat (APT) detection process, this research proposes a new approach to build and analyze the behavior profiles of APT attacks in network traffic. To achieve this goal, this study carries out two main objectives, including (i) building the behavior profile of APT IP in network traffic using a new intelligent computation method; (ii) analyzing and evaluating the behavior profile of APT IP based on a deep graph network. Specifically, to build the behavior profile of APT IP, this article describes using a combination of two different data mining methods: Bidirectional Long Short-Term Memory (Bi) and Attention (A).
View Article and Find Full Text PDFHeliyon
September 2024
Master of Business Administration, Faculty of Graduate Studies, An-Najah National University, Nablus, Palestine.
Cybersecurity continues to be an important concern for financial institutions given the technology's rapid development and increasing adoption of digital services. Effective safety measures must be adopted to safeguard sensitive financial data and protect clients from potential harm due to the rise in cyber threats that target digital organizations. The aim of this study is to investigates how machine learning algorithms are integrated into cyber security measures in the context of digital banking and its benefits and drawbacks.
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