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Conference proceeding
Scam Pandemic: How Attackers Exploit Public Fear through Phishing
2020 APWG Symposium on Electronic Crime Research (eCrime), v 2021-, pp 1-10
16 Nov 2020
Abstract
As the COVID-19 pandemic started triggering widespread lockdowns across the globe, cybercriminals did not hesitate to take advantage of users' increased usage of the Internet and their reliance on it. In this paper, we carry out a comprehensive measurement study of online social engineering attacks in the early months of the pandemic. By collecting, synthesizing, and analyzing DNS records, TLS certificates, phishing URLs, phishing website source code, phishing emails, web traffic to phishing websites, news articles, and government announcements, we track trends of phishing activity between January and May 2020 and seek to understand the key implications of the underlying trends.We find that phishing attack traffic in March and April 2020 skyrocketed up to 220% of its pre-COVID-19 rate, far exceeding typical seasonal spikes. Attackers exploited victims' uncertainty and fear related to the pandemic through a variety of highly targeted scams, including emerging scam types against which current defenses are not sufficient as well as traditional phishing which outpaced the ecosystem's collective response.
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Details
- Title
- Scam Pandemic: How Attackers Exploit Public Fear through Phishing
- Creators
- Marzieh Bitaab - Arizona State UniversityHaehyun Cho - Arizona State UniversityAdam Oest - Arizona State UniversityPenghui Zhang - Arizona State UniversityZhibo Sun - Arizona State UniversityRana Pourmohamad - Arizona State UniversityDoowon Kim - University of Tennessee at KnoxvilleTiffany Bao - Arizona State UniversityRuoyu Wang - Arizona State UniversityYan Shoshitaishvili - Arizona State UniversityAdam Doupe - Arizona State UniversityGail-Joon Ahn - Arizona State University
- Publication Details
- 2020 APWG Symposium on Electronic Crime Research (eCrime), v 2021-, pp 1-10
- Publisher
- IEEE
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science (Computing)
- Web of Science ID
- WOS:000717032200011
- Scopus ID
- 2-s2.0-85112011041
- Other Identifier
- 991021871062904721
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- Collaboration types
- Industry collaboration
- Domestic collaboration
- Web of Science research areas
- Computer Science, Information Systems
- Computer Science, Interdisciplinary Applications
- Computer Science, Theory & Methods
- Criminology & Penology