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D&L: A Natural Language Processing Based Approach for Protecting Sensitive Information from Shoulder Surfing Attacks

2023 | Americas Conference on Information Systems | Citations: 0
Authors: Aldossari, Marran; Zhang, Dongsong

Abstract: Despite the increasing attention and research effort, how to protect sensitive ... Expand

Abstract: Despite the increasing attention and research effort, how to protect sensitive information from shoulder surfing attacks is still under studied. Existing methods for protecting sensitive textual content on users' screens from shoulder surfing attacks have various limitations, including ineffectiveness, insufficient protection of sensitive information, low usability, and high cognitive workload. To address those limitations, this paper proposes, develops, and evaluates a new solution called "detection and labeling" (D&L), which uses NLP techniques to automatically detect and label sensitive information in the textual content. The labeled and hidden sensitive information is then read to users through their headphones upon their clicking a label. Evaluation results demonstrate that D&L improves protection, enhances usability, reduces users' cognitive workload, and allows faster browsing speed compared to the baseline methods. Collapse

Semantic filters: macos

Topics: electronic mail laptop computer usability privacy perceived ease of use

Methods: survey parametric test experiment Tukey HSD for post poc analysis ANOVA
The Future of Digital Platform Design - The Case of the EU Platform Regulation Discourse

2023 | European Conference On Information Systems | Citations: 1
Authors: Heimburg, Vincent; Schmitt, Julian; Wiesche, Manuel

Abstract: Digital platform research focuses on the mechanisms in digital platform ecosyst ... Expand

Abstract: Digital platform research focuses on the mechanisms in digital platform ecosystems and the dynamics between platform owners, complementors, and end-users. Recent studies are beginning to look beyond the boundaries of narrow platform ecosystems. The development of the European Union's DigitalMarkets Act (DMA) is a revelatory case to study this wider perspective. Hundreds of actors participated in discourses on the regulation, which aims to regulate so-called gatekeeper platforms that are allegedly powerful, unfair to platform users, and incontestable for competitors. By means of a critical discourse analysis, we coded 1720 contributions on the proposed and adopted DMA between June 2020 and July 2022. We identify 72 positions and 14 narratives along five discourses. Our study creates a better understanding of a wider perspective of platform ecosystem structure that goes beyond the triangle of platform owner, complementors, and end users. Collapse

Semantic filters: macos

Topics: digital ecosystem closed platform value creation participatory design electronic market

Methods: qualitative coding design methodology qualitative content analysis memoing grounded theory
Knowledge Work ‘Unplugged’ - Digital Detox Effects on ICT Demands, Job Performance and Satisfaction

2022 | International Conference on Business Informatics | Citations: 0
Authors: Mirbabaie, Milad; Braun, Lea-Marie; Marx, Julian

Abstract: Information and communication technologies (ICT) have gained immense importance ... Expand

Abstract: Information and communication technologies (ICT) have gained immense importance in the world of work. Knowledge workers, however, do not only benefit from ICT use. One drawback is the so-called ICT availability demand which is associated with a constant pressure to be online, including afterwork time. This demand can have severe consequences on the individual such as impaired wellbeing, harmed job performance and satisfaction. This paper scrutinizes the extent to which digital detox, a periodic disconnection from technology, can support knowledge workers to prevent and cope with ICT availability demands. A two-week online experiment was conducted to measure the effects of digital detox in the context of knowledge work. The results indicate a significant decrease in ICT availability demands after conducting digital detox. Moreover, this paper derives theoretical and practical implications about how digital detox can be understood and applied in organizational contexts. Collapse

Semantic filters: macos

Topics: task productivity job satisfaction knowledge work IS management organizational context

Methods: experiment longitudinal research survey parametric test ANOVA
Virtual Machine Placement with Disk Anti-colocation Constraints Using Variable Neighborhood Search Heuristic
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2021 | Information Systems Frontiers | Citations: 0
Authors: Hbaieb, Ameni; Khemakhem, Mahdi; Ben Jemaa, Maher

Abstract: In a cloud computing environment, virtual machine placement (VMP) represents an ... Expand

Abstract: In a cloud computing environment, virtual machine placement (VMP) represents an important challenge to select the most suitable set of physical machines (PMs) to host a set of virtual machines (VMs). The challenge is how to find optimal or near-optimal solution effectively and efficiently especially when VMP is considered as a NP-hard problem. However, the existing algorithms have focused mostly on compute resources when provisioning VMs and ignore storage resources. Therefore, they often generate non-optimal compute and storage resources for executing users applications. To address this problem, we outline more in details the binary linear programming (BLP) model previously proposed to solve the consolidated VMP with disk anti-colocation constraint (denoted VMcP-DAC) and we solve it using a heuristic algorithm. Our approach considers a special type of disk anti-colocation requirements to prevent Input/Output (IO) performance bottleneck. We implement a variable neighborhood search based optimization heuristic (denoted VNS-H) to solve the VMcP-DAC by minimizing both the resource wastage and the operational expenditure. To the best of our knowledge, only three studies in the literature that are devoted to VMcP-DAC problem. In two of these three works, authors proposed exact algorithms that are unable to solve large scale VMcP-DAC problem instances. For this reason, in a previous work, we proposed a decomposition based method to overcome the convergence issues for only large scale problems. In the present paper, our goal is to solve VMcP-DAC problem instances suitable for both regular and large data centers. We investigate the effectiveness of the proposed VNS-H, showing that it has a better convergence characteristics and it is more computationally efficient than compared methods from the literature. Collapse

Semantic filters: macos

Topics: data center cloud computing programming language macos virtualization technology

Methods: computational algorithm experiment linear optimization optimization model simulation
Alliance Governance Mechanisms in the Face of Disruption
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2021 | Organization Science | Citations: 2
Authors: Keller, Arne; Lumineau, Fabrice; Mellewigt, Thomas; Ariño, Africa

Abstract: Existing academic literature has discussed contracts and relational governance a ... Expand

Abstract: Existing academic literature has discussed contracts and relational governance as the key mechanisms that help alliance partners address problems of cooperation and coordination. However, when an alliance undergoes disruption, the nature and extent of such problems may change and therefore the value of these mechanisms may change. This study advances a dynamic perspective on alliance governance by examining the impact of disruption and subsequent adjustment on the value of alliance governance mechanisms. To this end, we longitudinally studied a revelatory case of a research and development alliance in the veterinary drug industry that experienced disruption triggered by an internal restructuring at one of the partner companies. We approached the evidence with a fine-grained typology that builds on two dimensions that underlie governance mechanisms: the means to enforce their ruling principles (contractual versus relational) and the level of codification of these principles (formal versus informal). Based on our findings, we (1) show the significance of this revised typology, which suggests that contractual governance is not necessarily formal and relational governance is not necessarily informal; (2) provide a more systematic discussion of the tradeoffs that the various mechanisms entail and how these are altered through disruption and adjustment dynamics; and (3) analyze how the interplay between different types of governance mechanisms evolves following disruption and adjustment. Overall, our study brings the concept of disruption to the dynamic perspective of alliance governance and highlights the contingent value of alliance governance mechanisms. Collapse

Semantic filters: macos

Topics: research and development interorganizational relationship database system anonymity macos

Methods: qualitative interview theory development case study archival research longitudinal research
Attack Modeling and Mitigation Strategies for Risk-Based Analysis of Networked Medical Devices

2020 | HICSS | Citations: 0
Authors: Hodges, Bronwyn J; McDonald, J Todd; Glisson, William Bradley; Jacobs, Michael

Abstract: The escalating integration of network-enabled medical devices raises concerns fo ... Expand

Abstract: The escalating integration of network-enabled medical devices raises concerns for both practitioners and academics in terms of introducing new vulnerabilities and attack vectors. This prompts the idea that combining medical device data, security vulnerability enumerations, and attack-modeling data into a single database could enable security analysts to proactively identify potential security weaknesses in medical devices and formulate appropriate mitigation and remediation plans. This study introduces a novel extension to a relational database risk assessment framework by using the open-source tool OVAL to capture device states and compare them to security advisories that warn of threats and vulnerabilities, and where threats and vulnerabilities exist provide mitigation recommendations. The contribution of this research is a proof of concept evaluation that demonstrates the integration of OVAL and CAPEC attack patterns for analysis using a database-driven risk assessment framework. Collapse

Semantic filters: macos

Topics: database system Python extensible markup language open source macos

Methods: case study simulation design artifact testing design science entity relationship modeling
Designing scalability in required in-class introductory college courses

2020 | Information & Management | Citations: 0
Authors: Piccoli, Gabriele

Abstract: We posit that design science enables the creation of in-class introductory colle ... Expand

Abstract: We posit that design science enables the creation of in-class introductory college courses that can scale to large numbers of students, under resource constraints. We build on the centrality of human interactions in learning environments and conceptualize a college course as a socio-technical (ST) artifact. Grounded in the intervention theory, we draw meta-requirements guiding the design of college courses that leverage IT to scale, while maintaining the centrality of the professor’s role. We use the design-build-evaluate cycle to instantiate the ST artifact and demonstrate its feasibility using evaluation episodes as prescribed by the Framework for Evaluation in Design Science Research. Collapse

Semantic filters: macos

Topics: online learning system office information system digital dashboard mobile application macos

Methods: design artifact design science design artifact testing kernel theory design requirement
A probabilistic data-driven framework for scoring the preoperative recipient-donor heart transplant survival
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2016 | Decision Support Systems | Citations: 0
Authors: Dag, Ali; Topuz, Kazim; Oztekin, Asil; Bulur, Serkan; Megahed, Fadel M.

Abstract: Recent research has shown that data mining models can accurately predict the out ... Expand

Abstract: Recent research has shown that data mining models can accurately predict the outcome of a heart transplant based on predictors that include patient and donor's health/demographics. These models have not been adopted in practice, however, since they did not: a) consider the interactions between the explanatory variables; b) provide a patient's specific risk of survival (reported results have been primarily deterministic); and c) offer an automated decision tool that can provide some data-driven insights to practitioners. In this study, we attempt to overcome these three limitations through the use of Bayesian Belief Networks (BBN). The proposed BBN framework is comprised of four phases. In the first two phases, the data is preprocessed, and a candidate set of predictors is generated based on employing several variable selection methods. The third phase involves the addition of medically relevant variables to the list. In phase four, the BBN model is applied. The results show that the proposed BBN method provides similar predictive performance to the best approaches in the literature. More importantly, our method provides novel information on the interactions among the predictors and the conditional probability of survival for a given set of relevant donor–recipient characteristics. We offer U.S. practitioners a decision support tool that presents an individualized survival score based on our BBN model (and the UNOS dataset). Collapse

Semantic filters: macos

Topics: decision support system analytical information system database system explicit knowledge Linux

Methods: machine learning computational algorithm sensitivity analysis k-nearest neighbor proportional hazards model

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Found 8 articles

D&L: A Natural Language Processing Based Approach for Protecting Sensitive Information from Shoulder Surfing Attacks

The Future of Digital Platform Design - The Case of the EU Platform Regulation Discourse

Knowledge Work ‘Unplugged’ - Digital Detox Effects on ICT Demands, Job Performance and Satisfaction

Virtual Machine Placement with Disk Anti-colocation Constraints Using Variable Neighborhood Search Heuristic

Alliance Governance Mechanisms in the Face of Disruption

Attack Modeling and Mitigation Strategies for Risk-Based Analysis of Networked Medical Devices

Designing scalability in required in-class introductory college courses

A probabilistic data-driven framework for scoring the preoperative recipient-donor heart transplant survival