Institut für Wirtschaftsinformatik

Dauerhafte URI für die Sammlunghttps://irf.fhnw.ch/handle/11654/66

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Practice track: a learning tracker using digital biomarkers for autistic preschoolers
(2022) Sandhu, Gurmit; Kilburg, Anne; Martin, Andreas; Pande, Charuta; Witschel, Hans Friedrich; Laurenzi, Emanuele; Billing, Erik; Hinkelmann, Knut; Gerber, Aurona
Preschool children, when diagnosed with Autism Spectrum Disorder (ASD), often ex- perience a long and painful journey on their way to self-advocacy. Access to standard of care is poor, with long waiting times and the feeling of stigmatization in many social set- tings. Early interventions in ASD have been found to deliver promising results, but have a high cost for all stakeholders. Some recent studies have suggested that digital biomarkers (e.g., eye gaze), tracked using affordable wearable devices such as smartphones or tablets, could play a role in identifying children with special needs. In this paper, we discuss the possibility of supporting neurodiverse children with technologies based on digital biomark- ers which can help to a) monitor the performance of children diagnosed with ASD and b) predict those who would benefit most from early interventions. We describe an ongoing feasibility study that uses the “DREAM dataset”, stemming from a clinical study with 61 pre-school children diagnosed with ASD, to identify digital biomarkers informative for the child’s progression on tasks such as imitation of gestures. We describe our vision of a tool that will use these prediction models and that ASD pre-schoolers could use to train certain social skills at home. Our discussion includes the settings in which this usage could be embedded.
04B - Beitrag Konferenzschrift
Platform-based strategic consulting for digital transformation
(2022) Gatziu Grivas, Stella; Giovanoli, Claudio; Grasshoff, Gunnar; Imhof, Denis; Hinkelmann, Knut; Gerber, Aurona
The digital age poses manifold challenges and difficult conditions for all sizes of organizations in all industries. Organizations need to adapt to complex challenges and difficult conditions and to plan and execute their digital transformation strategies. More and more organizations need support by strategic business consulting companies which must be offered in an effective and efficient way so that also small and medium sized companies can profit from it to stay competitive. Our research work focusses on the development of online strategic consulting tools offered as self-services on a web-based platform supporting the definition of digital transformation strategy. The so-called Digital Backpack Assessment (DBA) measures the digital maturity and proposes possible cases for changes. The tool follows the following principles: (1) A holistic approach with focus on the customer orientation, the business models, the organizational excellence, and the operational excellence. (2) An open strategy approach where several stakeholders from the company participate
04B - Beitrag Konferenzschrift
A cyber attack simulation for teaching cybersecurity
(2023) Scherb, Christopher; Heitz, Luc; Grimberg, Frank; Grieder, Hermann; Maurer, Marcel; Gerber, Aurona; Hinkelmann, Knut
With the rising number of cyberattacks, such as ransomware attacks and cyber espionage, educating non-cybersecurity professionals to recognize threats has become more important than ever before. However, traditional training methods, such as phishing awareness campaigns, training videos and assessments have proven to be less effective over time. Therefore, it is time to rethink the approach on how to train cyber awareness. In this paper we suggest an alternative approach -- a serious game -- to educate awareness for common cyberattacks. While many serious games for cybersecurity education exist, all follow a very similar approach: showing people the effects of a cyber attack on their own system or company network. For example, one of the main tasks in these games is to sort out phishing mails. We developed and evaluated a new type of cybersecurity game: an attack simulator, which shows the entire setting from a different perspective. Instead of sorting out phishing mails the players should write phishing mails to trick potential victims and use other forms of cyberattacks. Our game explains the intention of each attack and shows the consequences of a successful attack. This way, we hope, players will get a better understanding on how to detect cyberattacks.
04B - Beitrag Konferenzschrift
Agile management in cybersecurity
(2023) Asprion, Petra; Giovanoli, Claudio; Scherb, Christopher; Bhat, Sourabha; Gerber, Aurona; Hinkelmann, Knut
Cybersecurity management has emerged as a topic of growing importance on a global scale. Applying traditional management practices to cybersecurity is often too cumbersome and can lead to significant delays. Today's enterprises must be able to adapt to ever-evolving digital threats and act with corresponding agility and flexibility. Agile methods are well suited for projects without a defined scope, duration, tasks, and resources and has been identified as suitable for meeting the management challenges of cybersecurity teams. Based on an in-depth literature review, this study assumed that adopting an agile approach to cybersecurity helps organizations manage cybersecurity effectively. A first prototypical model was developed and evaluated which combines agile methods with cybersecurity functions - based on a recognized reference model.
04B - Beitrag Konferenzschrift
Towards an assistive and pattern learning-driven process modeling approach
(2019) Laurenzi, Emanuele; Hinkelmann, Knut; Jüngling, Stephan; Montecchiari, Devid; Pande, Charuta; Martin, Andreas; Martin, Andreas; Hinkelmann, Knut; Gerber, Aurona; Lenat, Doug; van Harmelen, Frank; Clark, Peter
The practice of business process modeling not only requires modeling expertise but also significant domain expertise. Bringing the latter into an early stage of modeling contributes to design models that appropriately capture an underlying reality. For this, modeling experts and domain experts need to intensively cooperate, especially when the former are not experienced within the domain they are modeling. This results in a time-consuming and demanding engineering effort. To address this challenge, we propose a process modeling approach that assists domain experts in the creation and adaptation of process models. To get an appropriate assistance, the approach is driven by semantic patterns and learning. Semantic patterns are domain-specific and consist of process model fragments (or end-to-end process models), which are continuously learned from feedback from domain as well as process modeling experts. This enables to incorporate good practices of process modeling into the semantic patterns. To this end, both machine-learning and knowledge engineering techniques are employed, which allow the semantic patterns to adapt over time and thus to keep up with the evolution of process modeling in the different business domains.
04B - Beitrag Konferenzschrift
Leverage white-collar workers with AI
(2019) Jüngling, Stephan; Hofer, Angelin; Martin, Andreas; Hinkelmann, Knut; Gerber, Aurona; Lenat, Doug; Clark, Peter
Based on the example of automated meeting minutes taking, the paper highlights the potential of optimizing the allocation of tasks between humans and machines to take the particular strengths and weaknesses of both into account. In order to combine the functionality of supervised and unsupervised machine learning with rule-based AI or traditionally programmed software components, the capabilities of AI-based system actors need to be incorporated into the system design process as early as possible.
04B - Beitrag Konferenzschrift
Combining machine learning with knowledge engineering to detect fake news in social networks - A survey
(2019) Ahmed, Sajjad; Hinkelmann, Knut; Corradini, Flavio; Martin, Andreas; Martin, Andreas; Hinkelmann, Knut; Gerber, Aurona; Lenat, Doug; van Harmelen, Frank
Due to extensive spread of fake news on social and news media it became an emerging research topic now a days that gained attention. In the news media and social media the information is spread highspeed but without accuracy and hence detection mechanism should be able to predict news fast enough to tackle the dissemination of fake news. It has the potential for negative impacts on individuals and society. Therefore, detecting fake news on social media is important and also a technically challenging problem these days. We knew that Machine learning is helpful for building Artificial intelligence systems based on tacit knowledge because it can help us to solve complex problems due to real word data. On the other side we knew that Knowledge engineering is helpful for representing experts knowledge which people aware of that knowledge. Due to this we proposed that integration of Machine learning and knowledge engineering can be helpful in detection of fake news. In this paper we present what is fake news, importance of fake news, overall impact of fake news on different areas, different ways to detect fake news on social media, existing detections algorithms that can help us to overcome the issue, similar application areas and at the end we proposed combination of data driven and engineered knowledge to combat fake news. We studied and compared three different modules text classifiers, stance detection applications and fact checking existing techniques that can help to detect fake news. Furthermore, we investigated the impact of fake news on society. Experimental evaluation of publically available datasets and our proposed fake news detection combination can serve better in detection of fake news.
04B - Beitrag Konferenzschrift
Post-quantum cryptography: an introductory overview and implementation challenges of quantum-resistant algorithms
(2022) Käppler, Sherdel; Schneider, Bettina; Hinkelmann, Knut; Gerber, Aurona
Cryptographic algorithms are an essential measure to ensure confidentiality and integrity of internet communication. The development of quantum computers (QCs) and their potential to utilize Shor’s Law, is increasingly recognized as a threat to asymmetric cryptography. In response, post-quantum cryptography (PQC) is gaining prominence as a notable field of research aiming to standardize quantum resistant algorithms before the operational usage of QCs. This paper is addressed to people with preliminary knowledge in the field of cryptography and QC. Based on a literature review, the authors provide an overview of challenges faced by the research community and elaborate the advancements in addressing post-quantum threats. A migration strategy from classical cryptosystems to PQC systems is in development, but obstacles such as time constraints and improper implementation complicate the process. Full implementation could take a decade or more. Until then, our paper aims to create awareness for potential challenges when transitioning towards PQC. As categorization scheme for these potential obstacles, we refer to a well- established model in cybersecurity – the McCumber Cube. Conclusions embrace preparing for risks of improper implementation and deriving a multi-step migration. Special attention is expected to be needed for data migration of existing data sets. As a request for future research in PQC, the authors identified the process of implementing post-cryptography standards, e.g., from the National Institute of Standards and Technology (NIST), and an assessment of the perceived readiness of industry to adapt.
04B - Beitrag Konferenzschrift
A system of customer co-creation for new product development of digital products with a pilot study of the Swiss media industry
(2023) Le Cunff, Eric; Schlick, Sandra; Gerber, Aurona; Hinkelmann, Knut
In the age of digitisation, the media industry is faced with declining advertising revenues. Therefore, the focus on the development of new digital products is a key element to survive in such a fast-changing market and to increase the innovation performance. One of the most important elements thereby is the involvement of customers as co-creators in the new product development (NPD) process, so that new digital products are developed that are in demand on the market. However, the process of how companies turn external knowledge from customers into knowledge creation for generating new ideas and the development of innovative products has not been analysed. This pilot study, which presents an initial system of customer co-creation for NPD of digital products from the literature and searches for similarities and dissimilarities through an abductive qualitative data analysis from interviews with three managers in three different Swiss media companies, explores this unresolved research gap. The system of this study is based on an overarching phase model, which is derived from Application Lifecycle Management (ALM). The process anchored in it, which focuses on the customer co-creation of digital products, integrates process elements from the two user-centered approaches, namely User Centered Design (UCD) and Design Thinking (DT). The results from the interviews show that the system is largely in line with the NPD process procedures in the three media companies. It was found that customers can be involved everywhere in the NPD process, but that this is not yet implemented in practice. However, as the future ambition in media companies is to become even more customer- centric, the proposed system in this study is very promising.
04B - Beitrag Konferenzschrift
Combining symbolic and sub-symbolic AI in the context of education and learning
(2020) Telesko, Rainer; Jüngling, Stephan; Gachnang, Phillip; Martin, Andreas; Hinkelmann, Knut; Fill, Hans-Georg; Gerber, Aurona; Lenat, Doug; Stolle, Reinhard; van Harmelen, Frank
Abstraction abilities are key to successfully mastering the Business Information Technology Programme (BIT) at the FHNW (Fachhochschule Nordwestschweiz). Object-Orientation (OO) is one example - which extensively requires analytical capabilities. For testing the OO-related capabilities a questionnaire (OO SET) for prospective and 1st year students was developed based on the Blackjack scenario. Our main target of the OO SET is to identify clusters of students which are likely to fail in the OO-related modules without a substantial amount of training. For the interpretation of the data the Kohonen Feature Map (KFM) is used which is nowadays very popular for data mining and exploratory data analysis. However, like all sub-symbolic approaches the KFM lacks to interpret and explain its results. Therefore, we plan to add - based on existing algorithms - a “postprocessing” component which generates propositional rules for the clusters and helps to improve quality management in the admission and teaching process. With such an approach we synergistically integrate symbolic and sub-symbolic artificial intelligence by building a bridge between machine learning and knowledge engineering.
04B - Beitrag Konferenzschrift

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