Miracle-dz/UniFAR-FTUs huggingface dataset:
The Design of an Ontology for ATT&CK and its Application to Cybersecurity

The spread of attacks in computer networks and within systems can have severe consequences for both individuals and organizations. One approach to preventing the spread of attacks is to use ontological aid, which is the use of ontologies to provide a structured representation of knowledge about the attack and its components, especially the ones who often disguise themselves to remain undetected for a long time within the system. As soon as one particular stage of such an attack is detected, it is imperative to reduce the amount of spread so that no permanent damage can be done. For this, the security analyst must boil down to technical details from a behavioral perspective so that proper defensive initiatives can be taken. We propose an ontology that will aid security analysts to find out the list of vulnerabilities to be patched so that an ongoing attack campaign can be prevented from spreading even more.
What is Human-Centered about Human-Centered AI? A Map of the Research Landscape

The application of Artificial Intelligence (AI) across a wide range of domains comes with both high expectations of its benefits and dire predictions of misuse. While AI systems have largely been driven by a technology-centered design approach, the potential societal consequences of AI have mobilized both HCI and AI researchers towards researching human-centered artificial intelligence (HCAI). However, there remains considerable ambiguity about what it means to frame, design and evaluate HCAI. This paper presents a critical review of the large corpus of peer-reviewed literature emerging on HCAI in order to characterize what the community is defining as HCAI. Our review contributes an overview and map of HCAI research based on work that explicitly mentions the terms ‘human-centered artificial intelligence’ or ‘human-centered machine learning’ or their variations, and suggests future challenges and research directions. The map reveals the breadth of research happening in HCAI, established clusters and the emerging areas of Interaction with AI and Ethical AI. The paper contributes a new definition of HCAI, and calls for greater collaboration between AI and HCI research, and new HCAI constructs.
Sensorimotor Simulation of Redirected Reaching using Stochastic Optimal Feedback Control

Illusory VR interaction techniques such as hand redirection work because humans use vision to adjust their motor commands during movement (e.g., reaching). Existing simulations of redirected reaching are limited, however, and have not yet incorporated important stochastic characteristics like sensorimotor noise, nor captured redirection’s effect on movement duration. In this work, we propose adapting a stochastic optimal feedback control (SOFC) model of normal reach to simulate redirection by augmenting sensory feedback at run-time. We present a summary of our simulation and validate it against user data gathered in multiple redirection conditions. We also evaluate the impacts of visual attention on the effectiveness of redirection in real users and replicate the effects in simulation. Our results show that an infinite-horizon SOFC model is able to reproduce key characteristics of redirected reaches and highlight the benefits of SOFC as a tool for simulating, evaluating, and gaining insights about redirection techniques.
Exploration of verbal descriptions and dynamic indoors environments for people with sight loss

Our study explored the navigational challenges of an unfamiliar room (with moving furniture and people) and what verbal guidance would be useful for visually impaired people(VIPs). A mainly qualitative approach of observation and interviews with ten VIPs revealed a lot about the challenges, guidance content and delivery. Further research is indicated to explore effective implementation.
Building a Participatory Data Design Approach to Examine Gender Bias in English-Twi Machine Translation

This project attempts to build a data-design approach to examine the detection and mitigation of gender bias in an English– Twi machine translation. This project makes use of an open-source data English-Akuapem Twi parallel corpus. Training the dataset on a sequence-to sequence model reveals a stereotypical bias in the machine translation system associated with a high-status profession like 'engineering. ' The quality of translation for sentences associated with 'he' is higher than 'she. ' Hence, a proposed data design approach is made to help examine bias in the dataset. The quality of the translation of sentences associated with either 'he’ or 'she’ improved and got either identical bleu scores or just a little difference in the bleu scores.
Sympathetic Activation in Deadlines of Deskbound Research - A Study in the Wild

Paper and proposal deadlines are important milestones, conjuring up emotional memories to researchers. The question is if in the daily challenging world of scholarly research, deadlines truly incur higher sympathetic loading than the alternative. Here we report results from a longitudinal, in the wild study of n = 10 researchers working in the presence and absence of impeding deadlines. Unlike the retrospective, questionnaire-based studies of research deadlines in the past, our study is real-time and multimodal, including physiological, observational, and psychometric measurements. The results suggest that deadlines do not significantly add to the sympathetic loading of researchers. Irrespective of deadlines, the researchers’ sympathetic activation is strongly associated with the amount of reading and writing they do, the extent of smartphone use, and the frequency of physical breaks they take. The latter likely indicates a natural mechanism for regulating sympathetic overactivity in deskbound research, which can inform the design of future break interfaces.
AVOCUS: A Voice Customization System for Online Personas

Many digital applications offer avatar customization options, positively affecting user experience. However, the adoption of auditory aspects in avatar customization has often been neglected and may have been understudied for its potential. Inspired by prior research that uncovers end-user’s demands for voice customization, we seek to apply the identified implications into practice and discover end-user’s voice preferences and behavior towards voice customization systems. To this end, we designed and deployed AVOCUS, a web application that enables users to search for specific voices or manipulate voice-related parameters to generate a voice similar to a target voice. Our findings suggest that (1) searching for specific voice using hashtags were perceived to be easy, (2) customized voices generated from voice reflection and voice parameter control functions had high satisfaction, and (3) participants tend to reflect the features of their desired voices when customizing their own voice.
Impact of Privacy Protection Methods of Lifelogs on Remembered Memories

Lifelogging is traditionally used for memory augmentation. However, recent research shows that users’ trust in the completeness and accuracy of lifelogs might skew their memories. Privacy-protection alterations such as body blurring and content deletion are commonly applied to photos to circumvent capturing sensitive information. However, their impact on how users remember memories remain unclear. To this end, we conduct a white-hat memory attack and report on an iterative experiment (N=21) to compare the impact of viewing 1) unaltered lifelogs, 2) blurred lifelogs, and 3) a subset of the lifelogs after deleting private ones, on confidently remembering memories. Findings indicate that all the privacy methods impact memories’ quality similarly and that users tend to change their answers in recognition more than recall scenarios. Results also show that users have high confidence in their remembered content across all privacy methods. Our work raises awareness about the mindful designing of technological interventions.
Structured Editing for All: Deriving Usable Structured Editors from Grammars

Structured editing can show benefits in learnability, tool building, and editing efficiency in programming. However, creating a usable structured editor is laborious and demanding, typically requiring tool builders to manually create or adjust editing interactions. We present Sandblocks, a system that allows users to automatically generate structured editors for every language with a formal grammar available. Our system’s input reconciliation process acts on arbitrary syntax trees to provides consistent interactions across our generated editors. Our editors’ editing experience is designed to be familiar to users from textual editing but, compared to previous work, requires no manual annotation in the grammars. We demonstrate our editors’ usability across languages through a user study (N=18). Compared to conventional text editors, even with minimal training, participants only took on average 21% (JS), 34% (Clojure), and 95% (RegExp) longer and reported that editing felt natural with a score of 6/7.
Challenging but Connective: Large-Scale Characteristics of Synchronous Collaboration Across Time Zones

Organizations are becoming increasingly distributed and many need to collaborate synchronously over great geographical distances. Despite a rich body of literature on spatially-distanced meetings, gaps remain in our understanding of temporally-distanced meetings. Here, we characterize cross time zone collaborations by analyzing 20 million meetings scheduled at a multinational corporation, Microsoft, supported by a survey on how 130 employees perceive their scheduling needs. We find that cross time zone meetings are closely associated with scheduling patterns around early morning and late evening hours, which are challenging and discordant with employees’ stated temporal preferences. Additionally, the burdens of meeting across time boundaries are asymmetrically distributed among workers at different levels of the organization and different geolocations. Nonetheless, we further observe evidence that cross time zone attendees are organizationally distant and diverse, suggesting that addressing these challenges by limiting meetings would disafford employees the opportunities to connect. We conclude by sharing opportunities for facilitating cross time zone meetings that foster healthier global collaborations.
A Descriptive Analysis of a Formative Decade of Research in Affective Haptic System Design

The global pandemic exposed serious drawbacks in relying on communication modalities in which social touch, however important, is absent. Considerable research has explored haptic technologies for sensing or displaying social touch and influencing affective state, for wellness, social communication, emotion regulation, and affect therapy. However, this Affective Haptic System design (AHSD) work varies widely in purpose and origin discipline, making it difficult to perceive overall progress and identify primary obstacles to practical deployment. We conducted a scoping review and conceptual analysis with a design lens, identifying 110 papers from the last decade in 11 ACM and IEEE venues that regularly attract AHSD work. Our analysis identified 38 dimensions within 8 facets: demographic, theoretical grounding, impact, system specification, usage specification, ethical consideration, technology, and evaluation. We visualize trends, disciplinary mixing, and topical focus over time, and highlight major advances while pinning down crucial gaps that can be addressed in the future.
Disability-First Design and Creation of A Dataset Showing Private Visual Information Collected With People Who Are Blind

We present the design and creation of a disability-first dataset, “BIV-Priv,” which contains 728 images and 728 videos of 14 private categories captured by 26 blind participants to support downstream development of artificial intelligence (AI) models. While best practices in dataset creation typically attempt to eliminate private content, some applications require such content for model development. We describe our approach in creating this dataset with private content in an ethical way, including using props rather than participants’ own private objects and balancing multi-disciplinary perspectives (e.g., accessibility, privacy, computer vision) to meet the tangible metrics (e.g., diversity, category, amount of content) to support AI innovations. We observed challenges that our participants encountered during the data collection, including accessibility issues (e.g., understanding foreground vs. background object placement) and issues due to the sensitive nature of the content (e.g., discomfort in capturing some props such as condoms around family members).
Mobilizing Social Media Data: Reflections of a Researcher Mediating between Data and Organization

This paper examines the practices involved in mobilizing social media data from their site of production to the institutional context of non-profit organizations. We report on nine months of fieldwork with a transnational and intergovernmental organization using social media data to understand the role of grassroots initiatives in Mexico, in the unique context of the COVID-19 pandemic. We show how different stakeholders negotiate the definition of problems to be addressed with social media data, the collective creation of ground-truth, and the limitations involved in the process of extracting value from data. The meanings of social media data are not defined in advance; instead, they are contingent on the practices and needs of the organization that seeks to extract insights from the analysis. We conclude with a list of reflections and questions for researchers who mediate in the mobilization of social media data into non-profit organizations to inform humanitarian action.
Disentangling Fairness Perceptions in Algorithmic Decision-Making: the Effects of Explanations, Human Oversight, and Contestability

Recent research claims that information cues and system attributes of algorithmic decision-making processes affect decision subjects’ fairness perceptions. However, little is still known about how these factors interact. This paper presents a user study (N = 267) investigating the individual and combined effects of explanations, human oversight, and contestability on informational and procedural fairness perceptions for high- and low-stakes decisions in a loan approval scenario. We find that explanations and contestability contribute to informational and procedural fairness perceptions, respectively, but we find no evidence for an effect of human oversight. Our results further show that both informational and procedural fairness perceptions contribute positively to overall fairness perceptions but we do not find an interaction effect between them. A qualitative analysis exposes tensions between information overload and understanding, human involvement and timely decision-making, and accounting for personal circumstances while maintaining procedural consistency. Our results have important design implications for algorithmic decision-making processes that meet decision subjects’ standards of justice.
“I Could Wear It All of the Time, Just Like My Wedding Ring:” Insights into Older People’s Perceptions of Smart Rings

We present findings from an examination of older adults’ perceptions of and preferences for smart rings, a unique class of interactive wearables gaining traction in the consumer market. To this end, we conducted semi-structured interviews with nine older adults, aged between 61 and 69 years old, to understand their perceptions regarding several smart ring models representative of rings, ring-like, and ring-ready finger-augmentation devices. We also elicited our participants’ preferences for using smart rings in their everyday life, such as for controlling various home appliances and electronic devices. Our results show an overall positive experience and openness toward adopting smart rings, which were perceived useful to assist with various activities. Based on our findings and following the aging research agenda in HCI, we propose future work opportunities for designing smart ring technology tailored to the needs and preferences of older adults.
A Wearable Haptic Interface for Assisting Blind and Visually Impaired Students in Learning Algebraic Equations

BVI (blind and visually impaired) persons do not have the same degree of access to concepts and procedures in learning algebraic equations as sighted persons. As tactile resources are uncommon, most rely on auditory-based methods that place heavy stress on working memory. We propose a novel approach that leverages haptic technology to communicate mathematical symbols via vibrotactile patterns; this design addresses open challenges found in existing resources for BVI people and explores the potential utility of this medium for all users. We conducted three separate studies to evaluate the feasibility of our gloves that included BVI participants. The outcomes of our studies yielded insightful design discussions, including a blind participant who found the device immediately intuitive and exciting in potential.
“Where is history”: Toward Designing a Voice Assistant to help Older Adults locate Interface Features quickly

Older adults often struggle to locate a function quickly in feature-rich user interfaces (UIs). Mobile UIs not only pack a ton of features in a small screen but also get frequent updates to their visual layouts—thereby exacerbating the problem. This paper explores a design solution where users could search for a UI feature using spoken-word queries. We investigated: 1) what type of questions older users ask when facing interaction challenges in unfamiliar scenarios, 2) how those query types compare with younger users’ inquiries, and 3) how older adults use a voice assistant design probe in a Wizard-of-Oz (WoZ) study. Results reveal five query types when verbally articulating interaction issues: validation, directed and undirected informational, navigational, and conceptual. In the WoZ study, older users typically asked for help following a series of non-unique or off-task feature selections (n = 13/15), and in 77% of those instances, they completed the task in the next interaction.
All Your IoT Devices Are Belong to Us: Security Weaknesses in IoT Management Platforms

IoT devices have become an integral part of our day to day activities, and are also being deployed to fulfil a number of industrial, enterprise and agricultural use cases. To efficiently manage and operate these devices, the IoT ecosystem relies on several IoT management platforms. Given the security-sensitive nature of the operations performed by these platforms, analyzing them for security vulnerabilities is critical to protect the ecosystem from potential cyber threats. In this work, by exploring the core functionalities offered by leading platforms, we first design a security evaluation framework. Subsequently, we use our framework to analyze 42 IoT management platforms. Our analysis uncovers a number of high severity unauthorized access vulnerabilities in 9/42 platforms, which could lead to attacks such as remote SIM deactivation, IoT SIM overcharging and device data forgery. Furthermore, we find broken authentication in 11/42 platforms, including complete account takeover on 7/42 platforms, along with remote code execution on one of the platforms. Overall, on 11/42 platforms, we find vulnerabilities that could lead to platform-wide attacks, that affect all users and all devices connected to those platforms.
Exploring Physiological Correlates of Visual Complexity Adaptation: Insights from EDA, ECG, and EEG Data for Adaptation Evaluation in VR Adaptive Systems

Physiologically-adaptive Virtual Reality can drive interactions and adjust virtual content to better fit users’ needs and support specific goals. However, the complexity of psychophysiological inference hinders efficient adaptation as the relationship between cognitive and physiological features rarely show one-to-one correspondence. Therefore, it is necessary to employ multimodal approaches to evaluate the effect of adaptations. In this work, we analyzed a multimodal dataset (EEG, ECG, and EDA) acquired during interaction with a VR-adaptive system that employed EDA as input for adaptation of secondary task difficulty. We evaluated the effect of dynamic adjustments on different physiological features and their correlation. Our results show that when the adaptive system increased the secondary task difficulty, theta, beta, and phasic EDA features increased. Moreover, we found a high correlation between theta, alpha, and beta oscillations during difficulty adjustments. Our results show how specific EEG and EDA features can be employed for evaluating VR adaptive systems.
All it Takes is a Slight Rotation: Robotic Bar-stools Enhance Intimacy in Couples’ Conflict

Couples’ ability to manage conflicts is fundamental in the discourse of romantic relationships. A supportive environment for conflict management highly depends on non-verbal communication cues. We explored the possibility to facilitate positive non-verbal cues by using autonomous furniture that do not alter the dyadic nature of the interaction. Couples discussed a subject of disagreement while seated on autonomous bar-stools. During the discussion, the stools rotated inward, directing partners toward one another. In the baseline condition, the bar-stools were inactive. Our findings showed that the inward rotation facilitated couples’ non-verbal cues (e.g., eye-gaze, body-orientation), which highly contributed to their communication and decreased conflict intensity. The positive effect was also evident in the number of intimate touch occurrences. The bar-stools’ movement led to a significant increase in hand-holding, kisses, and hugs. This work highlights the great potential of leveraging autonomous furniture for enhancing romantic interactions while preserving their intimate and emotional nature.
Why I Can’t Authenticate — Understanding the Low Adoption of Authentication Ceremonies with Autoethnography

Authentication ceremonies detect and mitigate Man-in-the-Middle (MitM) attacks on end-to-end encrypted messengers, such as Signal, WhatsApp, or Threema. However, prior work found that adoption remains low as non-expert users have difficulties using them correctly. Anecdotal evidence suggests that security researchers also have trouble authenticating others. Since their issues are probably unrelated to user comprehension or usability, the root causes may lie deeper. This work explores these root causes using autoethnography. The first author kept a five-month research diary of their experience with authentication ceremonies. The results uncover points of failure while planning and conducting authentication ceremonies. They include cognitive load, forgetfulness, social awkwardness, and explanations required by a communication partner. Additionally, this work identifies and discusses how sociocultural aspects affect authentication ceremonies. Lastly, this work discusses a design approach for cooperative security that employs cultural transcoding to improve sociocultural aspects of security by design.