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Remote Working Pre- and Post-COVID-19: An Analysis of New Threats and Risks to Security and Privacy

Nurse, Jason R. C., Williams, Nikki, Collins, Emily, Panteli, Niki, Blythe, John, Koppelman, Ben (2021) Remote Working Pre- and Post-COVID-19: An Analysis of New Threats and Risks to Security and Privacy. In: 23rd International Conference on Human-Computer Interaction, 24-29 Jul 2021, Online. (doi:10.1007/978-3-030-78645-8_74) (KAR id:87308)

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https://doi.org/10.1007/978-3-030-78645-8_74

Abstract

COVID-19 has radically changed society as we know it. To reduce the spread of the virus, millions across the globe have been forced to work remotely, often in make-shift home offices, and using a plethora of new, unfamiliar digital technologies. In this article, we critically analyse cyber security and privacy concerns arising due to remote working during the coronavirus pandemic. Through our work, we discover a series of security risks emerging because of the realities of this period. For instance, lack of remote-working security training, heightened stress and anxiety, rushed technology deployment, and the presence of untrusted individuals in a remote-working environment (e.g., in flatshares), can result in new cyber-risk. Simultaneously, we find that as organisations look to manage these and other risks posed by their remote workforces, employee's privacy (including personal information and activities) is often compromised. This is apparent in the significant adoption of remote workplace monitoring, management and surveillance technologies. Such technologies raise several privacy and ethical questions, and further highlight the tension between security and privacy going forward.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1007/978-3-030-78645-8_74
Uncontrolled keywords: Remote working, Working from home, Coronavirus, Cyber security, Privacy, Human Factors, Workplace surveillance, Ethics
Subjects: H Social Sciences > HF Commerce
Q Science > QA Mathematics (inc Computing science)
T Technology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Jason Nurse
Date Deposited: 24 Mar 2021 20:51 UTC
Last Modified: 07 Jul 2021 15:53 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/87308 (The current URI for this page, for reference purposes)
Nurse, Jason R. C.: https://orcid.org/0000-0003-4118-1680
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