Logo des Repositoriums

Auflistung nach Autor:in "Sultanow,Eldar"

1 - 3 von 3
  • Textdokument
    Entwicklung einer Open-Data-Referenzarchitektur für die Luftfahrtindustrie
    (INFORMATIK 2022, 2022) Losse,Ann-Kathrin; Gehrke,Melanie; Ullrich,André; Czarnecki,Christian; Sultanow,Eldar; Breithaupt,Carsten; Koch,Christian
    Open Data impliziert die freie Zugänglichkeit, Verfügbarkeit und Wiederverwendbarkeit von Datensätzen. Obwohl hochwertige Datensätze öffentlich verfügbar sind, ist der Zugang zu diesen und die Transparenz über die Formate nicht immer gegeben. Dies mindert die optimale Nutzung des Potenzials zur Wertschöpfung, trotz der vorherrschenden Einigkeit über ihre Chancen. Denn Open Data ermöglicht das Vorantreiben von Compliance-Themen wie Transparenz und Rechenschaftspflicht bis hin zur Förderung von Innovationen. Die Nutzung von Open Data erfordert Mut und eine gemeinsame Anstrengung verschiedener Akteure und Branchen. Im Rahmen des vorliegenden Beitrags werden auf Grundlage des Design Science-Ansatzes eine Open Data Capability Map sowie darauf aufbauend eine Datenarchitektur für Open Data in der Luftfahrtindustrie an einem Beispiel entwickelt.
  • Textdokument
    Infrastructure anomaly detection: A cloud-native architecture at Germany’s Federal Employment Agency
    (INFORMATIK 2022, 2022) Herget,Gebhard; Sultanow,Eldar; Chircu,Alina; Ludsteck,Johannes; Hammer,Sebastian; Koch,Christian; Reuter,Willy; Seßler,Matthias
    In prior research we explored the use of time series analysis methods to detect one class of information technology (IT) infrastructure anomalies - Distributed Denial of Service (DDoS) attacks. The results of this prior work were a mathematical model and a prototype implementation that were concretely trialed and operated in the data centers of Germany's Federal Employment Agency (FEA). With this paper, we go one step further and generalize as well as optimize the mathematical model and create higher performance and scalability for an updated prototype through targeted use of cloud technologies. The starting point of our generalization is the Exponential Smoothing (E-S) approach, which underlies, for example, the well-known Holt-Winters method. This method is used to predict univariate time series. To detect anomalies (such as DDoS attacks) in infrastructure data, we extend the E-S approach to enable it to forecast multivariate time series. In this optimization of our method and our prototype, we take an exploratory, agile approach. Furthermore, we present a cloud-native architecture stack which we pilot in Azure.
  • Textdokument
    A Reference Architecture for On-Premises Chatbots in Banks and Public Institutions
    (INFORMATIK 2021, 2021) Koch, Christian; Linnik, Benjamin; Pelzel, Frank; Sultanow,Eldar; Welter, Sebastian; Cox, Sean
    Chatbots have the potential to significantly increase the efficiency of banks and public institutions. Both sectors, however, are subject to special regulations and restrictions in areas such as information security and data protection. The policies of these organizations therefore, in some cases, reject the use of cloud and proprietary products because in their view they lack transparency. As a result, the implementation of chatbots in banks and public institutions often focuses on open-source and on-premises solutions; however, there are hardly any scientific guidelines on how to implement these systems. Our paper aims to close this research gap. The article proposes a reference architecture for chatbots in banks and public institutions that are a.) based on open-source software and b.) are hosted on-premises. The framework is validated by case studies at TeamBank AG and the German Federal Employment Agency. Even if our architecture is designed for these specific industries, it may also add value in other sectors – as chatbots are expected to become increasingly important for the practical application of artificial intelligence in enterprises.