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The recent severity and frequency of cybercrime has been dominated by a single theme – the COVID-19 pandemic. This research develops a multi-level influence model to explore how cybercriminals are exploiting the COVID-19 pandemic by assessing situational factors, identifying victims, impersonating trusted sources, selecting attack methods, and employing social engineering techniques. The model extends upon prior work on influence techniques and emotional appeals that cybercriminals employ, by bringing into sharper focus the role of situational factors in COVID-19 related cybercrime attacks. Content and thematic analysis was conducted on 185 distinct COVID-19 cybercrime scam incident documents, including text, images, and photos, provided by a global online fraud and cybersecurity company tracking COVID-19 related cybercrime. The analysis reveals interesting patterns about the sheer breadth and diversity of COVID-19 related cybercrime and how these crimes are continually evolving in response to changing situational factors. It is hoped that these insights and recommendations for end-users and organisations can contribute to a safer digital world as we cope with many other pressing challenges during the COVID-19 pandemic.
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Stored only when both papers are in the corpus — 180 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.