Evidence map›Paper›PMID 34192113›Full record

ArticleIEEE access : practical innovations, open solutions2020

Have You Been a Victim of COVID-19-Related Cyber Incidents? Survey, Taxonomy, and Mitigation Strategies.

Saqib Hakak, Wazir Zada Khan, Muhammad Imran, Kim-Kwang Raymond Choo, Muhammad Shoaib

Abstract read
In one paragraph

Article in IEEE access : practical innovations, open solutions, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Outbreak COVID-19 in Medical Image Processing Using Deep Learning: A State-of-the-Art Review.Archives of computational methods in engineering : state of the art reviews · 2022
    Review
  6. Article
  7. Article
  8. Article
  9. Cyber Risk Recommendation System for Digital Education Management Platforms.Computational intelligence and neuroscience · 2022
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Saqib HakakFaculty of Computer ScienceUniversity of Northern British ColumbiaPrince GeorgeBCV2N 4Z9Canada.
Wazir Zada KhanFaculty of CS & ISJazan UniversityJazan45142Saudi Arabia.
Muhammad ImranCollege of Applied Computer ScienceKing Saud UniversityRiyadh11451Saudi Arabia.
Kim-Kwang Raymond ChooDepartment of Information Systems and Cyber SecurityThe University of Texas at San AntonioSan AntonioTX78249USA.
Muhammad ShoaibCollege of Computer and Information SciencesKing Saud UniversityRiyadh11451Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cybercriminals are constantly on the lookout for new attack vectors, and the recent COVID-19 pandemic is no exception. For example, social distancing measures have resulted in travel bans, lockdowns, and stay-at-home orders, consequently increasing the reliance on information and communications technologies, such as Zoom. Cybercriminals have also attempted to exploit the pandemic to facilitate a broad range of malicious activities, such as attempting to take over videoconferencing platforms used in online meetings/educational activities, information theft, and other fraudulent activities. This study briefly reviews some of the malicious cyber activities associated with COVID-19 and the potential mitigation solutions. We also propose an attack taxonomy, which (optimistically) will help guide future risk management and mitigation responses.

Indexed as

COVID-19cyberattacksmitigationpotential solutionssecurity and privacytaxonomy

Identifiers

PMID34192113
PMCPMC8043498

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.