3,919 research outputs found
UMSL Bulletin 2023-2024
The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp
An Adversarial Dance: Toward an Understanding of Insiders’ Responses to Organizational Information Security Measures
Despite the increased focus on organizational security policies and programs, some employees continue to engage in maladaptive responses to security measures (i.e., behaviors other than those recommended, intended, or prescribed). To help shed light on insiders’ adaptive and maladaptive responses to IS security measures, we conducted a case study of an organization at the forefront of security policy initiatives. Drawing on the beliefs-actions-outcomes (BAO) model to analyze our case data, we uncover a potentially nonvirtuous cycle consisting of security-related beliefs, actions, and outcomes, which we refer to as an “adversarial dance.” Explaining our results, we describe a novel belief framework that identifies four security belief profiles and uncovers an underexplored outcome of IS security: insiders’ lived security experiences. We find that individuals’ unfavorable lived security experiences produce counterproductive security-related beliefs that, in turn, lead to maladaptive behaviors. Maladaptive behaviors create new potential for security risk, leading to increased organizational security measures to counter them. Thus, the adversarial dance continues, as the new security measures have the potential to reinforce counterproductive security-related beliefs about the importance and risk of IS security and lead to new maladaptive behaviors. To help situate our findings within the current security literature, we integrate the results with prior research based on extant theories. While this paper is not the first to suggest that security measures can elicit maladaptive behaviors, the emergent belief framework and expanded BAO model of IS security constitute an important contribution to the behavioral IS security literature
Modelling, Monitoring, Control and Optimization for Complex Industrial Processes
This reprint includes 22 research papers and an editorial, collected from the Special Issue "Modelling, Monitoring, Control and Optimization for Complex Industrial Processes", highlighting recent research advances and emerging research directions in complex industrial processes. This reprint aims to promote the research field and benefit the readers from both academic communities and industrial sectors
A Sociotechnical Systems View of Computer Self-Efficacy and Usability Determinants of Technical Readiness
The specific research problem was that it is unknown whether computer self-efficacy and usability determine technical readiness in hourly and exempt information technology support employees in the United States. The purpose of this correlational study was to examine the relationship between computer self-efficacy and technical readiness, usability and technical readiness, and computer self-efficacy, usability, and technical readiness in hourly and exempt information technology support employees in the United States. Sociotechnical system theory suggests that every transaction has a human and technical aspect; thus, the theoretical framework. The convenience sample included 136 information technology support employees aged 18-70. The regression results indicated computer skills and usability at 20.2% of the variance and significant predictors of technical readiness, (F (1,134) = 11.96, p \u3c .001, R2 = .082) and (F (2,133) = 16.83, p \u3c .001, R2 = .202). When employees showed a higher level of computer skills, there was a correlation with a higher usability score. The dashboard management (p = 45), a predictor for computer self-efficacy, showed a negative correlation and increased the weights in the total Technical Readiness Index. The results show that employers, schools, and organizations can better plan for software implementations by identifying ways to promote computer self-efficacy and usability to increase technical readiness. The implications for positive social change may occur when hourly and exempt information technology support employees take a more active role in using computers, familiarizing themselves with the software, and providing feedback to influence their technical readiness, thereby leading to economic growth and sustainability in the United States
The Protection of Student Data Privacy in Wisconsin School Board Policies
American schools have increasingly adopted technology resources to fulfill their educational obligations. These tools are for instruction, communication, and storing and analyzing student information. Student data can be directory information, enrollment records, achievement data, and student-created products. This increased utilization began with the passage of No Child Left Behind in 2001, and the COVID-19 pandemic led to more educational technology use of student data. Districts turned to third-party vendors for assistance with data systems and virtual learning resources. Before, during, and after the pandemic, stakeholders were concerned about information security and the students\u27 privacy. School leaders looked to federal regulations to ensure appropriate and legal practices for student data use. The Family and Educational Rights and Privacy Act (FERPA) was implemented in 1974, and the growth of educational technology and digitization of student information has moved beyond the original guidance of the regulation. District leaders also looked to state laws, but Wisconsin statutes provide little guidance. These leaders rely on their local board policies to ensure they benefit from educational technology while protecting the privacy of their students. I utilized the methodological approach of document analysis and the contextual integrity privacy framework to understand how Wisconsin districts address student data privacy in local board policies. In addition, I examined how federal regulations are addressed and the role of leadership in policy implementation. Findings from this study indicate differences for districts using a policy consultation service. These policies address federal regulations and account for the use of data by modern educational technology. The leadership activities required for student data privacy align with previous research for effective educational leadership. These findings show the need for local policies to address federal regulations for student privacy in the context of educational technology utilization
Distributed Spatial Data Sharing: a new era in sharing spatial data
The advancements in information and communications technology, including the widespread adoption of GPS-based sensors, improvements in computational data processing, and satellite imagery, have resulted in new data sources, stakeholders, and methods of producing, using, and sharing spatial data. Daily, vast amounts of data are produced by individuals interacting with digital content and through automated and semi-automated sensors deployed across the environment. A growing portion of this information contains geographic information directly or indirectly embedded within it. The widespread use of automated smart sensors and an increased variety of georeferenced media resulted in new individual data collectors. This raises a new set of social concerns around individual geopricacy and data ownership. These changes require new approaches to managing, sharing, and processing geographic data. With the appearance of distributed data-sharing technologies, some of these challenges may be addressed. This can be achieved by moving from centralized control and ownership of the data to a more distributed system. In such a system, the individuals are responsible for gathering and controlling access and storing data. Stepping into the new area of distributed spatial data sharing needs preparations, including developing tools and algorithms to work with spatial data in this new environment efficiently. Peer-to-peer (P2P) networks have become very popular for storing and sharing information in a decentralized approach. However, these networks lack the methods to process spatio-temporal queries. During the first chapter of this research, we propose a new spatio-temporal multi-level tree structure, Distributed Spatio-Temporal Tree (DSTree), which aims to address this problem. DSTree is capable of performing a range of spatio-temporal queries. We also propose a framework that uses blockchain to share a DSTree on the distributed network, and each user can replicate, query, or update it. Next, we proposed a dynamic k-anonymity algorithm to address geoprivacy concerns in distributed platforms. Individual dynamic control of geoprivacy is one of the primary purposes of the proposed framework introduced in this research. Sharing data within and between organizations can be enhanced by greater trust and transparency offered by distributed or decentralized technologies. Rather than depending on a central authority to manage geographic data, a decentralized framework would provide a fine-grained and transparent sharing capability. Users can also control the precision of shared spatial data with others. They are not limited to third-party algorithms to decide their privacy level and are also not limited to the binary levels of location sharing. As mentioned earlier, individuals and communities can benefit from distributed spatial data sharing. During the last chapter of this work, we develop an image-sharing platform, aka harvester safety application, for the Kakisa indigenous community in northern Canada. During this project, we investigate the potential of using a Distributed Spatial Data sharing (DSDS) infrastructure for small-scale data-sharing needs in indigenous communities. We explored the potential use case and challenges and proposed a DSDS architecture to allow users in small communities to share and query their data using DSDS. Looking at the current availability of distributed tools, the sustainable development of such applications needs accessible technology. We need easy-to-use tools to use distributed technologies on community-scale SDS. In conclusion, distributed technology is in its early stages and requires easy-to-use tools/methods and algorithms to handle, share and query geographic information. Once developed, it will be possible to contrast DSDS against other data systems and thereby evaluate the practical benefit of such systems. A distributed data-sharing platform needs a standard framework to share data between different entities. Just like the first decades of the appearance of the web, these tools need regulations and standards. Such can benefit individuals and small communities in the current chaotic spatial data-sharing environment controlled by the central bodies
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