Design of a Novel Information System for Semi-automated Management of Cybersecurity in Industrial Control Systems

2023 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Ameri, Kimia; Hempel, Michael; Sharif, Hamid; Lopez, Juan; Perumalla, Kalyan

Abstract: There is an urgent need in many critical infrastructure sectors, including the e ... Expand

Abstract: There is an urgent need in many critical infrastructure sectors, including the energy sector, for attaining detailed insights into cybersecurity features and compliance with cybersecurity requirements related to their Operational Technology (OT) deployments. Frequent feature changes of OT devices interfere with this need, posing a great risk to customers. One effective way to address this challenge is via a semi-automated cyber-physical security assurance approach, which enables verification and validation of the OT device cybersecurity claims against actual capabilities, both pre- and post-deployment. To realize this approach, this article presents new methodology and algorithms to automatically identify cybersecurity-related claims expressed in natural language form in ICS device documents. We developed an identification process that employs natural language processing (NLP) techniques with the goal of semi-automated vetting of detected claims against their device implementation. We also present our novel NLP components for verifying feature claims against relevant cybersecurity requirements. The verification pipeline includes components such as automated vendor identification, device document curation, feature claim identification utilizing sentiment analysis for conflict resolution, and reporting of features that are claimed to be supported or indicated as unsupported. Our novel matching engine represents the first automated information system available in the cybersecurity domain that directly aids the generation of ICS compliance reports. Collapse

Topics: IT security database system website Python electronic authentication

Methods: computational algorithm sentiment analysis natural language processing BERT language model

ADAM - Towards a Software Model for the Automatic Detection of Data Attributes and Metadata in Business Processes

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Baumann, Nick; Schäffer, Thomas

Abstract: In the current era of digital transformation, organizations are faced with an u ... Expand

Abstract: In the current era of digital transformation, organizations are faced with an unprecedented volume of data that requires proper management. In order to effectively manage this data, organizations need to understand the data's requirements and usage. In addition, organizations want to leverage this data to improve their business processes and gain valuable insights. Unfortunately, many organizations lack visibility into which data attributes are being used within their processes and at what stage of the process they are being used. To address this problem, this paper presents a prototype called ADAM that uses process mining to identify data attributes and their associated metadata from processes. We provide a detailed description of the requirements gathered for the prototype and explain the design and implementation of ADAM. In particular, we show how ADAM can be utilized to identify data attributes and their specifications used in processes from an SAP ERP system. Collapse

Topics: process mining enterprise resource planning business process management electronic mail relational database

Methods: design artifact qualitative interview case study design science event log

Cost-based Optimization of Multistore Query Plans

2023 | Information Systems Frontiers | Citations: 0

Authors: Forresi, Chiara; Francia, Matteo; Gallinucci, Enrico; Golfarelli, Matteo

Abstract: Multistores are data management systems that enable query processing across diff ... Expand

Abstract: Multistores are data management systems that enable query processing across different and heterogeneous databases; besides the distribution of data, complexity factors like schema heterogeneity and data replication must be resolved through integration and data fusion activities. Our multistore solution relies on a dataspace to provide the user with an integrated view of the available data and enables the formulation and execution of GPSJ queries. In this paper, we propose a technique to optimize the execution of GPSJ queries by formulating and evaluating different execution plans on the multistore. In particular, we outline different strategies to carry out joins and data fusion by relying on different schema representations; then, a self-learning black-box cost model is used to estimate execution times and select the most efficient plan. The experiments assess the effectiveness of the cost model in choosing the best execution plan for the given queries and exploit multiple multistore benchmarks to investigate the factors that influence the performance of different plans. Collapse

Topics: database system MongoDB PostgreSQL document database relational database

Methods: computational algorithm experiment case study regression analysis method longitudinal research

In-Memory and Column Storage Changes IS Curriculum

2023 | HICSS | Citations: 0

Authors: Freeze, Ronald; Bristow, Susan

Abstract: Random Access Memory (RAM) prices have been dropping precipitously. This has giv ... Expand

Abstract: Random Access Memory (RAM) prices have been dropping precipitously. This has given rise to the possibility of keeping all data gathered in RAM rather than utilizing disk storage. This technological capability, along with benefits associated with a columnar storage database system, reduces the benefit of Relational Database Management Systems (RDBMS) and eliminates the need for Online Transactional Processing (OLTP) and Online Analytical Processing (OLAP) activities to remain separate. The RDBMS was a required data structure due to the need to separate the daily OLTP activities from the OLAP analysis of that data. In-memory processing allows both activities simultaneously. Data analysis can be done at the speed of data capture. Relational databases are not the only option for organizations. In-Memory is emerging, and university curriculum needs to innovate and create skills associated with denormalization of existing database (legacy) systems to prepare for the next generation of data managers. Collapse

Topics: organizational impact relational database computer data storage

Methods: qualitative interview

ARTIFICIAL INTELLIGENCE-AUGMENTED DECISION MAKING IN SUPPLY CHAIN MONITORING: AN ACTION DESIGN RESEARCH STUDY

2023 | European Conference On Information Systems | Citations: 0

Authors: Herath Pathirannehelage, Savindu; Jóhannsson, Jóhann; Shrestha, Yash; Krogh, Georg von

Abstract: Organizations are progressively adopting hybrid human-artificial intelligence ( ... Expand

Abstract: Organizations are progressively adopting hybrid human-artificial intelligence (AI) systems in decisionmaking processes, with human decisions being augmented by AI insights. Among the promising AI applications in supply chain monitoring (SCMo) are predictive maintenance systems that predict potential device failures and augment maintenance decisions, allowing for timely and efficient interventions. Despite the growing proliferation of such systems, prescriptive knowledge encompassing technical, business, and organizational aspects on how to design, develop, and deploy them in actual operational environments remains limited. To address this shortcoming of evidence-based design principles in practice, our action design research developed a predictive maintenance system that predicts SCMo device failures and augments the maintenance decisions about those devices. By doing so, we outline generalizable design principles to guide prospective predictive maintenance systems in SCMo. Collapse

Topics: artificial intelligence predictive maintenance organizational context decision making systems evaluation

Methods: machine learning design principle design artifact artificial neural network random forest classification

Theories: evidence-based design

Navigating Workload Compatibility Between a Recommender System and a NoSQL Database: An Interactive Tutorial

2023 | Communications of the Association for Information Systems | Citations: 0

Authors: Kayhan, Varol; Berndt, Donald

Abstract: Follow this and additional works at: https://aisel.aisnet.org/cais Recommended ... Expand

Abstract: Follow this and additional works at: https://aisel.aisnet.org/cais Recommended Citation Recommended Citation Abstract:In this tutorial, the issue of compatibility between a big data storage technology and an analytic workload is explored using a fictitious streaming company as an example. The tutorial offers an interactive approach to help students understand the importance of considering workload compatibility when adopting new technologies. We provide instructors with the following: two Jupyter Notebooks that analyze compatibility, a detailed instructor guide on how to execute these notebooks, lessons learned, and appendices containing solutions and explanations. This tutorial provides a valuable resource for instructors teaching courses in database systems, big data, and analytic concepts, helping students develop practical skills to navigate effectively the complexities of big data technologies. Collapse

Topics: database system document database recommender system collaborative filtering nosql database

Methods: database modeling design science survey

Analyzing the Needs of Ukrainian Refugees on Telegram in Real-Time: A Machine Learning Approach

2023 | International Conference on Business Informatics | Citations: 0

Authors: Reimann, Raphael; Caron, Matthew

Abstract: The humanitarian crisis resulting from the Russian invasion of Ukraine has led ... Expand

Abstract: The humanitarian crisis resulting from the Russian invasion of Ukraine has led to millions of displaced individuals across Europe. Addressing the evolving needs of these refugees is crucial for hosting countries and humanitarian organizations. This study leverages social media analytics to supplement traditional surveys, providing real-time insights into refugee needs by analyzing over two million messages from Telegram, a vital platform for Ukrainian refugees in Germany. We employ Natural Language Processing techniques, including language identification, sentiment analysis, and topic modeling, to identify well-defined topic clusters such as housing, financial and legal assistance, language courses, job market access, and medical needs. Our findings also reveal changes in topic occurrence and nature over time. To support practitioners, we introduce an interactive web-based dashboard for continuous analysis of refugee needs. Collapse

Topics: Telegram social media digital dashboard Twitter decision making

Methods: topic model natural language processing sentiment analysis transformer model data transformation

They Work with Data and Do Some Science: How Identity Conflict Turns Data Professionals away from Data Science

2023 | International Conference on Information Systems | Citations: 0

Authors: Rosa, Marta; Aikath, Devdeep; Mayer, Anne

Abstract: Data science is widely perceived as an attractive, lucrative, and prestigious e ... Expand

Abstract: Data science is widely perceived as an attractive, lucrative, and prestigious emerging occupation. Research so far has focused on understanding data scientists' practices and identity work associated with establishing and legitimizing this new occupation. This work, however, is not sufficient to explain a phenomenon we observed whereby professionals rejected the opportunity to adopt this new occupational identity. To understand why professionals may not want to be labeled data scientists, we analyzed 43 interviews with data professionals at an educational measurement company in the U.S. Despite a clear steer from management towards the data science label, many interviewees stuck to their established professional identities. In our preliminary findings, we use the literature on identity conflict as a lens to make sense of our observations. By identifying three types of conflicts: 1) task conflict, 2) role conflict, 3) tool conflict, we begin to explain what turns professionals away from data science. Collapse

Topics: database system structured query language Tableau software programming language relational database

Methods: qualitative interview grounded theory machine learning personal interview qualitative coding

Measuring Ecosystem Complexity - Decision-Making Based on Complementarity Graphs

2023 | HICSS | Citations: 0

Authors: Schmidt, Rainer; Alt, Rainer; Zimmermann, Alfed

Abstract: Platforms feature increasingly complex architectures with regard to interconnect ... Expand

Abstract: Platforms feature increasingly complex architectures with regard to interconnecting with other digital platforms as well as with a variety of devices and services. This development also impacts the structure of digital platform ecosystems and forces providers of these services, devices, and services to incorporate this complexity in their decision-making. To contribute to the existing body of knowledge on measuring ecosystem complexity, the present research proposes two key artefacts based on ecosystem intelligence: On the one hand, complementarity graphs represent ecosystems with an ecosystem's functional modules as vertices and complementarities as edges. The nodes carry information about the category membership of the module. On the other hand, a process is suggested that can collect important information for ecosystem intelligence using proxies and web scraping. Our approach allows replacing data, which today is largely unavailable due to competitive reasons. We demonstrated the use of the artefacts in category-oriented complementarity maps that aggregate the information from complementarity graphs and support decision-making. They show which combination of module categories creates strong and weak complementarities. The paper evaluates complementarity maps and the data collection process by creating category-oriented complementarity graphs on the Alexa skill ecosystem and concludes with a call to pursue more research based on functional ecosystem intelligence. Collapse

Topics: digital ecosystem digital dashboard missing data relational database decision making

Methods: data modeling design science

Rethinking the “Cloud Course”: A Cloud-Native Approach

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Schuff, David; Doyle, Mart

Abstract: As organizations move to the cloud, they realize that simply migrating existing ... Expand

Abstract: As organizations move to the cloud, they realize that simply migrating existing legacy applications has not achieved the anticipated efficiencies and cost savings. The result is an increased focus on the design and deployment of truly cloud-native applications. This shift must take place within information systems curricula to remain relevant in this space, but this requires rethinking the structure, focus, and approach of these courses. This paper describes the redesign of an undergraduate cloud infrastructure course where students create and deploy APIs using cloud-native technologies. Collapse

Topics: cloud computing application programming interface systems design web page database system

Methods: design principle