IoT Marketplace: Willingness-To-Pay vs. Willingness-To-Accept

Gopavaram, Shakthidhar; Dev, Jayati; Das, Sanchari; Camp, L. Jean

doi:10.2139/ssrn.3867652

Cited by 4 publications

(4 citation statements)

References 25 publications

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“…Scientific literature on phishing defense can be divided in two categories: technical papers (e.g., [10,49,50,52,53]), which propose (or attack) a given solution; and user studies (e.g., [8,35,82]), which seek to investigate the response of humans to phishing (useful for phishing training and education). However, to the best of our knowledge, none of these categories have questioned how humans respond to phishing webpages crafted to bypass ML-PWDs.…”

Section: Research Gapmentioning

confidence: 99%

“…However, to the best of our knowledge, none of these categories have questioned how humans respond to phishing webpages crafted to bypass ML-PWDs. Indeed, from an "adversarial ML" perspective, technical papers typically stop after showing that a given ML-PWD has been evaded (e.g., [11,57]); whereas user studies either entailed "phishing" webpages that have been crafted ad-hoc (e.g., [35,58]) or, even when real phishing webpages were considered (e.g., [8,12]), the role of ML was irrelevant. Hence, the question: "Are adversarial webpages a problem in reality?"…”

Section: Research Gapmentioning

confidence: 99%

“…To this purpose, we perform a quantitative analysis of the responses we collected for8 Our user studies have a population that is larger than most previous user studies on (non-adversarial) phishing webpages[16]. Specifically, most works ([7,8,12,13,26,39,45,46,67,68,83]) have less than 100 participants, while six ([29,35,58,77,82]) have [100-400] participants. Only the work by Purkait et al[64] has more participants (621) than ours, but it was carried out in 2014.…”

mentioning

confidence: 99%

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"Are Adversarial Phishing Webpages a Threat in Reality?" Understanding the Users' Perception of Adversarial Webpages

Yuan,

Hao,

Apruzzese

et al. 2024

Proceedings of the ACM Web Conference 2024

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Machine learning based phishing website detectors (ML-PWD) are a critical part of today's anti-phishing solutions in operation. Unfortunately, ML-PWD are prone to adversarial evasions, evidenced by both academic studies and analyses of real-world adversarial phishing webpages. However, existing works mostly focused on assessing adversarial phishing webpages against ML-PWD, while neglecting a crucial aspect: investigating whether they can deceive the actual target of phishing-the end users. In this paper, we fill this gap by conducting two user studies (𝑛=470) to examine how human users perceive adversarial phishing webpages, spanning both synthetically crafted ones (which we create by evading a state-ofthe-art ML-PWD) as well as real adversarial webpages (taken from the wild Web) that bypassed a production-grade ML-PWD. Our findings confirm that adversarial phishing is a threat to both users and ML-PWD, since most adversarial phishing webpages have comparable effectiveness on users w.r.t. unperturbed ones. However, not all adversarial perturbations are equally effective. For example, those with added typos are significantly more noticeable to users, who tend to overlook perturbations of higher visual magnitude (such as replacing the background). We also show that users' selfreported frequency of visiting a brand's website has a statistically negative correlation with their phishing detection accuracy, which is likely caused by overconfidence. We release our resources [5]. CCS CONCEPTS• Security and privacy → Phishing.

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Section: Research Gapmentioning

confidence: 99%

Section: Research Gapmentioning

confidence: 99%

mentioning

confidence: 99%

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"Are Adversarial Phishing Webpages a Threat in Reality?" Understanding the Users' Perception of Adversarial Webpages

Yuan,

Hao,

Apruzzese

et al. 2024

Proceedings of the ACM Web Conference 2024

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“…WTP is a well-established concept in economics that has been widely applied to research on privacy. It captures the maximum amount an individual would pay to opt out from their personal data being disclosed (Acquisti et al, 2013 ; Gopavaram et al, 2021 ). In this paper, we assess basic quality aspects of the measurement instrument for WTP that was included in the Bundesbank’s Online Panel on Households’ Expectations (BOP-HH).…”

Section: Introductionmentioning

confidence: 99%

The value of data privacy during the COVID-19 pandemic: a new set of survey questions

Helmschrott

Anand

Zhou

et al. 2022

Meas Instrum Soc Sci

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Contact-tracing smartphone apps that rely on users’ private data have been proposed as important tools in fighting the COVID-19 pandemic. The use of these apps, however, has sparked new debates on the value of data privacy. Several earlier studies have investigated citizens’ willingness to use such apps. We propose a set of questions as a new measurement instrument that goes beyond eliciting acceptance and aims at quantifying users’ willingness to pay (WTP) for data privacy. We assess some aspects of the measurement instrument pertaining to its validity. We find central assumptions of our theoretical model met, suggesting that the instrument serves as a good starting point for measuring WTP. For example, we found a rather low WTP for data privacy in times of a pandemic, with high consent rates to data sharing and a majority of people who would pay amounts of up to 10€ only to not have to share data. Nevertheless, there are several improvements to the instrument possible that should be addressed by future research. We also encourage researchers to field the refined version in larger samples including the offline population.

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Exploring The Security Issues in Home-Based IoT Devices Through Denial of Service Attacks

Toutsop

Das

Kornegay

2021

2021 IEEE SmartWorld, Ubiquitous Intelligence &Amp; Computing, Advanced &Amp; Trusted Computing, Scalable Computing &Amp; Commu

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IoT Marketplace: Willingness-To-Pay vs. Willingness-To-Accept

Cited by 4 publications

References 25 publications

"Are Adversarial Phishing Webpages a Threat in Reality?" Understanding the Users' Perception of Adversarial Webpages

"Are Adversarial Phishing Webpages a Threat in Reality?" Understanding the Users' Perception of Adversarial Webpages

The value of data privacy during the COVID-19 pandemic: a new set of survey questions

Exploring The Security Issues in Home-Based IoT Devices Through Denial of Service Attacks

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