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

• URL: http://arxiv.org/abs/2107.03907v1
• Date: Thu, 8 Jul 2021 15:39:56 GMT
• Title: Remote Working Pre- and Post-COVID-19: An Analysis of New Threats and Risks to Security and Privacy
• Authors: Jason R. C. Nurse and Nikki Williams and Emily Collins and Niki Panteli and John Blythe and Ben Koppelman
• Abstract summary: Millions across the globe have been forced to work remotely during the coronavirus pandemic. Lack of remote-working security training, heightened stress and anxiety, rushed technology deployment, and the presence of untrusted individuals in a remote-working environment can result in new cyber-risk. As organisations look to manage these and other risks posed by their remote workforces, employee's privacy is often compromised.
• Score: 1.712670816823812
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

Related papers

• Enhancing Enterprise Security with Zero Trust Architecture [0.0]
  Zero Trust Architecture (ZTA) represents a transformative approach to modern cybersecurity. ZTA shifts the security paradigm by assuming that no user, device, or system can be trusted by default. This paper explores the key components of ZTA, such as identity and access management (IAM), micro-segmentation, continuous monitoring, and behavioral analytics.
  arXiv  Detail & Related papers  (2024-10-23T21:53:16Z)
• Cybersecurity Challenge Analysis of Work-from-Anywhere (WFA) and Recommendations guided by a User Study [1.1749564892273827]
  Many organizations were forced to quickly transition to the work-from-anywhere (WFA) model as a necessity to continue with their operations and remain in business despite the restrictions imposed during the COVID-19 pandemic. This paper attempts to uncover some challenges and implications related to the cybersecurity of the WFA model. We conducted an online user study to investigate the readiness and cybersecurity awareness of employers and their employees who shifted to work remotely from anywhere.
  arXiv  Detail & Related papers  (2024-09-11T18:47:04Z)
• PsySafe: A Comprehensive Framework for Psychological-based Attack, Defense, and Evaluation of Multi-agent System Safety [70.84902425123406]
  Multi-agent systems, when enhanced with Large Language Models (LLMs), exhibit profound capabilities in collective intelligence. However, the potential misuse of this intelligence for malicious purposes presents significant risks. We propose a framework (PsySafe) grounded in agent psychology, focusing on identifying how dark personality traits in agents can lead to risky behaviors. Our experiments reveal several intriguing phenomena, such as the collective dangerous behaviors among agents, agents' self-reflection when engaging in dangerous behavior, and the correlation between agents' psychological assessments and dangerous behaviors.
  arXiv  Detail & Related papers  (2024-01-22T12:11:55Z)
• The Security and Privacy of Mobile Edge Computing: An Artificial Intelligence Perspective [64.36680481458868]
  Mobile Edge Computing (MEC) is a new computing paradigm that enables cloud computing and information technology (IT) services to be delivered at the network's edge. This paper provides a survey of security and privacy in MEC from the perspective of Artificial Intelligence (AI) We focus on new security and privacy issues, as well as potential solutions from the viewpoints of AI.
  arXiv  Detail & Related papers  (2024-01-03T07:47:22Z)
• The New Frontier of Cybersecurity: Emerging Threats and Innovations [0.0]
  The research delves into the consequences of these threats on individuals, organizations, and society at large. The sophistication and diversity of these emerging threats necessitate a multi-layered approach to cybersecurity. This study emphasizes the importance of implementing effective measures to mitigate these threats.
  arXiv  Detail & Related papers  (2023-11-05T12:08:20Z)
• Global Pandemics Influence on Cyber Security and Cyber Crimes [5.8010446129208155]
  COVID-19 has caused widespread damage across many areas of life and has made humans more dependent on the internet and technology. This paper examines the different types of security threats and cyber crimes that people faced in the pandemic time and the need for a safe and secure cyber infrastructure.
  arXiv  Detail & Related papers  (2023-02-24T05:26:42Z)
• Weaving Privacy and Power: On the Privacy Practices of Labor Organizers in the U.S. Technology Industry [2.446409405016844]
  This study is situated at the intersection of two pivotal shifts in workplace dynamics: the increase in online workplace communications due to remote work and the resurgence of the labor movement. We investigate how labor organizers assess and mitigate risks to privacy while engaging in collective action. We conclude with design recommendations that can help create safer, more secure and more private tools to better address the risks that organizers face.
  arXiv  Detail & Related papers  (2022-05-31T18:18:47Z)
• Proceedings of the Artificial Intelligence for Cyber Security (AICS) Workshop at AAAI 2022 [55.573187938617636]
  The workshop will focus on the application of AI to problems in cyber security. Cyber systems generate large volumes of data, utilizing this effectively is beyond human capabilities.
  arXiv  Detail & Related papers  (2022-02-28T18:27:41Z)
• Dos and Don'ts of Machine Learning in Computer Security [74.1816306998445]
  Despite great potential, machine learning in security is prone to subtle pitfalls that undermine its performance. We identify common pitfalls in the design, implementation, and evaluation of learning-based security systems. We propose actionable recommendations to support researchers in avoiding or mitigating the pitfalls where possible.
  arXiv  Detail & Related papers  (2020-10-19T13:09:31Z)
• Adversarial Machine Learning Attacks and Defense Methods in the Cyber Security Domain [58.30296637276011]
  This paper summarizes the latest research on adversarial attacks against security solutions based on machine learning techniques. It is the first to discuss the unique challenges of implementing end-to-end adversarial attacks in the cyber security domain.
  arXiv  Detail & Related papers  (2020-07-05T18:22:40Z)
• Secure Byzantine-Robust Machine Learning [61.03711813598128]
  We propose a secure two-server protocol that offers both input privacy and Byzantine-robustness. In addition, this protocol is communication-efficient, fault-tolerant and enjoys local differential privacy.
  arXiv  Detail & Related papers  (2020-06-08T16:55:15Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.