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相关论文: Detecting Deceptive Dark Patterns in E-commerce Pl…

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Dark patterns have become increasingly pervasive in online choice architectures, encompassing practices like subscription traps, hiding information about fees, pre-selecting options by default, nagging, and drip pricing. Regulators around…

人机交互 · 计算机科学 2024-04-03 Martin Brenncke

Manipulation defines many of our experiences as a consumer, including subtle nudges and overt advertising campaigns that seek to gain our attention and money. With the advent of digital services that can continuously optimize online…

人机交互 · 计算机科学 2022-07-22 Colin M. Gray , Jingle Chen , Shruthi Sai Chivukula , Liyang Qu

This work aims at expanding previous works done in the context of illegal activities classification, performing three different steps. First, we created a heterogeneous dataset of 113995 onion sites and dark marketplaces. Then, we compared…

信息检索 · 计算机科学 2023-12-11 Giuseppe Cascavilla , Gemma Catolino , Mirella Sangiovanni

Mobile user interfaces abundantly feature so-called 'dark patterns'. These deceptive design practices manipulate users' decision making to profit online service providers. While past research on dark patterns mainly focus on visual design,…

Past studies have illustrated the prevalence of UI dark patterns, or user interfaces that can lead end-users toward (unknowingly) taking actions that they may not have intended. Such deceptive UI designs can result in adverse effects on end…

软件工程 · 计算机科学 2023-03-14 SM Hasan Mansur , Sabiha Salma , Damilola Awofisayo , Kevin Moran

Current dark pattern research tells designers what not to do, but how do they know what to do? In contrast to prior approaches that focus on patterns to avoid and their underlying principles, we present a framework grounded in positive…

人机交互 · 计算机科学 2024-03-05 Evan Caragay , Katherine Xiong , Jonathan Zong , Daniel Jackson

User experience designers are facing increasing scrutiny and criticism for creating harmful technologies, leading to a pushback against unethical design practices. While clear-cut harmful practices such as dark patterns have received…

人机交互 · 计算机科学 2023-04-04 Hauke Sandhaus

Recent research has suggested that there are clear differences in the language used in the Dark Web compared to that of the Surface Web. As studies on the Dark Web commonly require textual analysis of the domain, language models specific to…

计算与语言 · 计算机科学 2023-05-19 Youngjin Jin , Eugene Jang , Jian Cui , Jin-Woo Chung , Yongjae Lee , Seungwon Shin

Although deceptive design patterns are subject to growing regulatory oversight, enforcement races to keep up with the scale of the problem. One promising solution is automated detection tools, many of which are developed within academia. We…

人机交互 · 计算机科学 2026-02-19 Arianna Rossi , Simon Parkin

The study of UX dark patterns, i.e., UI designs that seek to manipulate user behaviors, often for the benefit of online services, has drawn significant attention in the CHI and CSCW communities in recent years. To complement previous…

人机交互 · 计算机科学 2024-02-06 Yuwen Lu , Chao Zhang , Yuewen Yang , Yaxing Yao , Toby Jia-Jun Li

Dark jargons are benign-looking words that have hidden, sinister meanings and are used by participants of underground forums for illicit behavior. For example, the dark term "rat" is often used in lieu of "Remote Access Trojan". In this…

密码学与安全 · 计算机科学 2021-01-12 Dominic Seyler , Wei Liu , XiaoFeng Wang , ChengXiang Zhai

Dark patterns are (evil) design nudges that steer people's behaviour through persuasive interface design. Increasingly found in cookie consent requests, they possibly undermine principles of EU privacy law. In two preregistered online…

计算机与社会 · 计算机科学 2025-09-24 Paul Graßl , Hanna Schraffenberger , Frederik Zuiderveen Borgesius , Moniek Buijzen

Illegal marketplaces have increasingly shifted to concealed parts of the internet, including the deep and dark web, as well as platforms such as Telegram, Reddit, and Pastebin. These channels enable the anonymous trade of illicit goods…

The clear, social, and dark web have lately been identified as rich sources of valuable cyber-security information that -given the appropriate tools and methods-may be identified, crawled and subsequently leveraged to actionable…

密码学与安全 · 计算机科学 2021-09-16 Paris Koloveas , Thanasis Chantzios , Christos Tryfonopoulos , Spiros Skiadopoulos

The issue of dark patterns and deceptive designs (DPs) in everyday interfaces and interactions continues to grow. DPs are manipulative and malicious elements within user interfaces that deceive users into making unintended choices. In…

人机交互 · 计算机科学 2024-05-16 Weichen Joe Chang , Katie Seaborn , Andrew A. Adams

The availability of sophisticated technologies and methods of perpetrating criminogenic activities in the cyberspace is a pertinent societal problem. Darknet is an encrypted network technology that uses the internet infrastructure and can…

密码学与安全 · 计算机科学 2020-03-18 Victor Adewopo , Bilal Gonen , Said Varlioglu , Murat Ozer

Malicious bots pose a growing threat to e-commerce platforms by scraping data, hoarding inventory, and perpetrating fraud. Traditional bot mitigation techniques, including IP blacklists and CAPTCHA-based challenges, are increasingly…

机器学习 · 计算机科学 2026-02-19 Sichen Zhao , Zhiming Xue , Yalun Qi , Xianling Zeng , Zihan Yu

The dark patterns, deceptive interface designs manipulating user behaviors, have been extensively studied for their effects on human decision-making and autonomy. Yet, with the rising prominence of LLM-powered GUI agents that automate tasks…

The opaque nature of transformer-based models, particularly in applications susceptible to unethical practices such as dark-patterns in user interfaces, requires models that integrate uncertainty quantification to enhance trust in…

Large language models can influence users through conversation, creating new forms of dark patterns that differ from traditional UX dark patterns. We define LLM dark patterns as manipulative or deceptive behaviors enacted in dialogue.…

人机交互 · 计算机科学 2026-03-20 Yike Shi , Qing Xiao , Qing Hu , Hong Shen , Hua Shen