Results

Found 6 articles

Clear filters

Model-Based Cybersecurity Analysis
PDF
2023 | Business & Information Systems Engineering | Citations: 0
Authors: Jiang, Yuning; Jeusfeld, Manfred A.; Ding, Jianguo; Sandahl, Elin

Abstract: Critical infrastructure (CIs) such as power grids link a plethora of physical co ... Expand

Abstract: Critical infrastructure (CIs) such as power grids link a plethora of physical components from many different vendors to the software systems that control them. These systems are constantly threatened by sophisticated cyber attacks. The need to improve the cybersecurity of such CIs, through holistic system modeling and vulnerability analysis, cannot be overstated. This is challenging since a CI incorporates complex data from multiple interconnected physical and computation systems. Meanwhile, exploiting vulnerabilities in different information technology (IT) and operational technology (OT) systems leads to various cascading effects due to interconnections between systems. The paper investigates the use of a comprehensive taxonomy to model such interconnections and the implied dependencies within complex CIs, bridging the knowledge gap between IT security and OT security. The complexity of CI dependence analysis is harnessed by partitioning complicated dependencies into cyber and cyber-physical functional dependencies. These defined functional dependencies further support cascade modeling for vulnerability severity assessment and identification of critical components in a complex system. On top of the proposed taxonomy, the paper further suggests power-grid reference models that enhance the reproducibility and applicability of the proposed method. The methodology followed was design science research (DSR) to support the designing and validation of the proposed artifacts. More specifically, the structural, functional adequacy, compatibility, and coverage characteristics of the proposed artifacts are evaluated through a three-fold validation (two case studies and expert interviews). The first study uses two instantiated power-grid models extracted from existing architectures and frameworks like the IEC 62351 series. The second study involves a real-world municipal power grid. Collapse

Semantic filters: Semantic Scholar

Topics: IT security virtualization technology database system knowledge representation data center

Methods: reference modelling case study qualitative interview design artifact simulation
Text mining for classifying workplace severe injury events

2022 | Americas Conference on Information Systems | Citations: 0
Authors: Goldberg, David; Zaman, Nohel

Abstract: Occupational health and safety are significant issues for many organizations. W ... Expand

Abstract: Occupational health and safety are significant issues for many organizations. Workplace accidents have significant consequences for employees, and they also cause significant disruptions to business processes.In this paper, we analyze accident narrative data collected by the Occupational Safety and Health Administration (OSHA) to classify events leading to injuries and body parts injured. These datasets are collected in textual form, which can create difficulties for nuanced statistical analyses. By creating highperforming text classifiers, we can automatically code these records and provide decision-makers with useful information. We use BERT word embeddings and several variants thereof to perform these classifications, finding accuracy of approximately 89 percent and 79 percent for event types and body parts respectively. These contributions will improve organizations' capacities to understand and act upon textual accident narratives. Collapse

Semantic filters: Semantic Scholar

Topics: business process management Wikipedia

Methods: BERT word embedding SciBERT machine learning natural language processing
Where was COVID-19 first discovered? Designing a question-answering system for pandemic situations

2022 | European Conference On Information Systems | Citations: 0
Authors: Graf, Johannes; Lancho, Gino; Zschech, Patrick; Heinrich, Kai

Abstract: The COVID-19 pandemic is accompanied by a massive "infodemic" that makes it har ... Expand

Abstract: The COVID-19 pandemic is accompanied by a massive "infodemic" that makes it hard to identify concise and credible information for COVID-19-related questions, like incubation time, infection rates, or the effectiveness of vaccines. As a novel solution, our paper is concerned with designing a question-answering system based on modern technologies from natural language processing to overcome information overload and misinformation in pandemic situations. To carry out our research, we followed a design science research approach and applied Ingwersen's cognitive model of information retrieval interaction to inform our design process from a socio-technical lens. On this basis, we derived prescriptive design knowledge in terms of design requirements and design principles, which we translated into the construction of a prototypical instantiation. Our implementation is based on the comprehensive CORD-19 dataset, and we demonstrate our artifact's usefulness by evaluating its answer quality based on a sample of COVID-19 questions labeled by biomedical experts. Collapse

Semantic filters: Semantic Scholar

Topics: knowledge base pandemic covid 19 database system Elasticsearch

Methods: design artifact design principle design science question answering design requirement
A Holistic Framework for AI Systems in Industrial Applications

2021 | International Conference on Business Informatics | Citations: 0
Authors: Kaymakci, Can; Wenninger, Simon; Sauer, Alexander

Abstract: Although several promising use cases for artificial intelligence (AI) for manufa ... Expand

Abstract: Although several promising use cases for artificial intelligence (AI) for manufacturing companies have been identified, these are not yet widely used. Existing literature covers a variety of frameworks, methods and processes related to AI systems. However, the application of AI systems in manufacturing companies lacks a uniform understanding of components and functionalities as well as a structured process that supports developers and project managers in planning, implementing, and optimizing AI systems. To close this gap, we develop a generic conceptual model of an AI system for the application in manufacturing systems and a four-phase model to guide developers and project managers through the realization of AI systems. Collapse

Semantic filters: Semantic Scholar

Topics: artificial intelligence database system manufacturing information system systems development industrial artificial intelligence

Methods: conceptual modelling qualitative interview design science design artifact experiment
Current Issues Of Metrics For Information Security Awareness

2020 | European Conference On Information Systems | Citations: 0
Authors: Fertig, Tobias; Schütz, Andreas; Weber, Kristin

Abstract: Measuring information security awareness (ISA) is mostly done by the measuremen ... Expand

Abstract: Measuring information security awareness (ISA) is mostly done by the measurement of knowledge. However, knowledge does not allow any statement about actual behavior. Therefore, measurement techniques are required, that are focusing on the behavior of employees. We carried out a structured literature review as well as expert interviews in order to retrieve current requirements for metrics in theory and practice. Moreover, we show that the interviewees defined some more requirements than are available in literature. The goal of our research is, to create a performance measurement system (PMS) based on the integrated behavioral model (IBM). Therefore, we had to check if the different aspects of the IBM can be covered by existing metrics. Although many of the requirements can be fulfilled by current metrics, not all aspects of the IBM can be covered. Therefore, we need additional research to create a PMS that allows the evaluation of ISA in companies. Collapse

Semantic filters: Semantic Scholar

Topics: data security cybersecurity awareness anonymity social network internet technology

Methods: qualitative interview structured literature research literature study design science maturity model
TOWARDS AN INTEGRATIVE THEORETICAL FRAMEWORK OF INTERACTIVE MACHINE LEARNING SYSTEMS

2019 | European Conference On Information Systems | Citations: 0
Authors: MartÃŁnez, Miguel Angel Meza; Nadj, Mario; Maedche, Alexander

Abstract: Interactive machine learning (IML) is a learning process in which a user interac ... Expand

Abstract: Interactive machine learning (IML) is a learning process in which a user interacts with a system to iteratively define and optimise a model. Although recent years have illustrated the proliferation of IML systems in the fields of Human-Computer Interaction (HCI), Information Systems (IS), and Computer Science (CS), current research results are scattered leading to a lack of integration of existing work on IML. Furthermore, due to diverging functionalities and purposes IML systems can refer to, an uncertainty exists regarding the underlying distinct capabilities that constitute this class of systems. By reviewing extensive IML literature, this paper suggests an integrative theoretical framework for IML systems to address these current impediments. Reviewing 2,879 studies in leading journals and conferences during the years 1966-2018, we found an extensive range of applications areas that have implemented IML systems and the necessity to standardise the evaluation of those systems. Our framework offers an essential step to provide a theoretical foundation to integrate concepts and findings across different fields of research. The main contribution of this paper is organising and structuring the body of knowledge in IML for the advancement of the field. Furthermore, we suggest three opportunities for future IML research. From a practical point of view, our integrative theoretical framework can serve as a reference guide to inform the design and implementation of IML systems. Collapse

Semantic filters: Semantic Scholar

Topics: database system information retrieval human computer interaction usability information retrieval system

Methods: cluster analysis structured literature research cross sectional research reinforcement learning literature study

Page 1 of 1

AIS11

Journals

Conferences

Semantic Filter

Found 6 articles

Model-Based Cybersecurity Analysis

Text mining for classifying workplace severe injury events

Where was COVID-19 first discovered? Designing a question-answering system for pandemic situations

A Holistic Framework for AI Systems in Industrial Applications

Current Issues Of Metrics For Information Security Awareness

TOWARDS AN INTEGRATIVE THEORETICAL FRAMEWORK OF INTERACTIVE MACHINE LEARNING SYSTEMS