Harnessing the Challenges and Solutions to Improve Security Warnings: A Review

Abstract

The security warning is a representation of communication that is used to warn and to inform a person whether security menaces have been discovered in order to prevent any consequences of damage from taking place. The purpose of a security warning is to provide a legitimate alert (to notify and to warn) to the users so that a secure manner of action is safely conducted. It is worth noting that the majority of computer users prefer to dismiss security warnings due to lack of attention, the use of technical words, and the deficiency of information provided. This paper determines to achieve two outcomes: firstly, a thorough review of problems, challenges, and approaches to improving security warnings. Our work complements the previous classifications in the identification of problems and challenges in security warnings by value-adding a new classification, namely immersion in the primary task. Then, we add other related works within the known classifications accordingly. In addition, our work also presents the classifications of approaches to improving security warnings. Secondly, we propose two timelines by addressing the problems, challenges, and approaches to improving security warnings. It is expected that the outcomes of this research will be useful to researchers within the niche area for analysing trends and providing the groundwork in security warning studies, respectively.

Toward Designing Effective Warning Labels for Health Misinformation on Social Media

“…To minimize the spread of misinformation, platforms such as Twitter have started placing warning messages with corrective information as labels attached to the posts that are deemed to be misleading. Though similar to information security warnings, where users are alerted of any security threat discovered that may damage their computer systems or breach their personal information (Zaaba et al, 2021), misinformation warning labels specifically focus on mitigating the spread and use of misinformation that directly impact the health of users. For example, during the COVID-19 pandemic, Twitter used labels to warn users about false or misleading tweets related to topics such as vaccination (Sharevski et al, 2021).…”