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The use of metaphor in cybersecurity discourse has become a topic of interest because of its ability to aid communication about abstract security concepts. In this paper, we borrow from existing metaphor identification algorithms and general theories to create a lightweight metaphor identification algorithm, which uses only one external source of knowledge. The algorithm also introduces a real time corpus builder for extracting collocates; this is, identifying words that appear together more frequently than chance. We implement several variations of the introduced algorithm and empirically evaluate the output using the TroFi dataset, a de facto evaluation dataset in metaphor research. We find first, contrary to our expectation, that adding word sense disambiguation to our metaphor identification algorithm decreases its performance. Second, we find, that our lightweight algorithms perform comparably to their existing, more complex, counterparts. Finally, we present the results of several case studies to observe the utility of the algorithm for future research in linguistic metaphor identification in text related to cybersecurity texts and threats.

 

This paper reports a formative evaluation of auditory representations of cyber security threat indicators and cues, referred to as sonifications, to warn users about cyber threats. Most Internet browsers provide visual cues and textual warnings to help users identify when they are at risk. Although these alarming mechanisms are very effective in informing users, there are certain situations and circumstances where these alarming techniques are unsuccessful in drawing the user’s attention: (1) security warnings and features (e.g., blocking out malicious Websites) might overwhelm a typical Internet user and thus the users may overlook or ignore visual and textual warnings and, as a result, they might be targeted, (2) these visual cues are inaccessible to certain users such as those with visual impairments. This work is motivated by our previous work of the use of sonification of security warnings to users who are visually impaired. To investigate the usefulness of sonification in general security settings, this work uses real Websites instead of simulated Web applications with sighted participants. The study targets sonification for three different types of security threats: (1) phishing, (2) malware downloading, and (3) form filling. The results show that on average 58% of the participants were able to correctly remember what the sonification conveyed. Additionally, about 73% of the participants were able to correctly identify the threat that the sonification represented while performing tasks using real Websites. Furthermore, the paper introduces “CyberWarner”, a sonification sandbox that can be installed on the Google Chrome browser to enable auditory representations of certain security threats and cues that are designed based on several URL heuristics.

It is feasible to develop sonified cyber security threat indicators that users intuitively understand with minimal experience and training.

Users are more cautious about malicious activities in general. However, when navigating real Websites, they are less informed. This might be due to the appearance of the navigating Websites or the overwhelming issues when performing tasks.

Participants’ qualitative responses indicate that even when they did not remember what the sonification conveyed, the sonification was able to capture the user’s attention and take safe actions in response.

 

Auditory icons are naturally occurring sounds that systems play to convey information. Systems must convey complex messages. To do so, systems can play: 1) a single sound that represents the entire message, or 2) a single sound that represents the first part of the message, followed by another sound that represents the next part of that message, etc. The latter are known as concatenated auditory icons. To evaluate those approaches, participants interpreted single and concatenated auditory icons designed to convey their message well and poorly. Single auditory icons designed to convey their message well were correctly interpreted more often than those designed to convey their message poorly; that was not true for concatenated auditory icons. Concatenated auditory icons should not be comprised of a series of sounds that each represents its piece of a message well. The whole of a concatenated auditory icon is not the sum of its parts. 

Purpose Nonexperts do not always follow the advice in cybersecurity warning messages. To increase compliance, it is recommended that warning messages use nontechnical language, describe how the cyberattack will affect the user personally and do so in a way that aligns with how the user thinks about cyberattacks. Implementing those recommendations requires an understanding of how nonexperts think about cyberattack consequences. Unfortunately, research has yet to reveal nonexperts’ thinking about cyberattack consequences. Toward that end, the purpose of this study was to examine how nonexperts think about cyberattack consequences. Design/methodology/approach Nonexperts sorted cyberattack consequences based on perceived similarity and labeled each group based on the reason those grouped consequences were perceived to be similar. Participants’ labels were analyzed to understand the general themes and the specific features that are present in nonexperts’ thinking. Findings The results suggested participants mainly thought about cyberattack consequences in terms of what the attacker is doing and what will be affected. Further, the results suggested participants thought about certain aspects of the consequences in concrete terms and other aspects of the consequences in general terms. Originality/value This research illuminates how nonexperts think about cyberattack consequences. This paper also reveals what aspects of nonexperts’ thinking are more or less concrete and identifies specific terminology that can be used to describe aspects that fall into each case. Such information allows one to align warning messages to nonexperts’ thinking in more nuanced ways than would otherwise be possible. 

Cyber-defenders must account for users’ perceptions of attack consequence severity. However, research has yet to investigate such perceptions of a wide range of cyber-attack consequences. Thus, we had users rate the severity of 50 cyber-attack consequences. We then analyzed those ratings to a) understand perceived severity for each consequence, and b) compare perceived severity across select consequences. Further, we grouped ratings into the STRIDE threat model categories and c) analyzed whether perceived severity varied across those categories. The current study’s results suggest not all consequences are perceived to be equally severe; likewise, not all STRIDE threat model categories are perceived to be equally severe. Implications for designing warning messages and modeling threats are discussed.

 

To combat phishing, system messages warn users of suspected phishing attacks. However, users do not always comply with warning messages. One reason for non-compliance is that warning messages contradict how users think about phishing threats. To increase compliance, warning messages should align with user perceptions of phishing threat risks. How users think about phishing threats is not yet known. To identify how users perceive phishing threats, participants were surveyed about their perceptions of the severity and likelihood of 9 phishing consequences. Results revealed perceived severity and likelihood levels for each consequence, as well as relative differences between consequences. Concrete examples of warning messages that reflect these findings are provided.