The 10 most recently published documents
Im Forschungsprojekt „ILSe“ wurde ein intelligenter Sensor entwickelt, der den Füllstand von Laubfangkörben im Straßenabfluss messen, mittels der LoRaWAN-Funktechnologie übertragen und auf einem Dashboard anzeigen kann. Auf Basis dieser Daten können die Laubfangkörbe gezielt gereinigt werden, um den Wasserabfluss, insbesondere bei starken Regenfällen, zu maximieren. So können Überschwemmungen reduziert bzw. vermieden werden. Zudem wird die Infrastruktur geschützt und die Sicherheit des Verkehrs erhöht. Des Weiteren können Betriebsabläufe durch die bedarfsgerechte Reinigung der Laubfangkörbe effizienter gestaltet werden.
A method for controlling the transmission of a media stream comprising a plurality of consecutive stream elements Is described. The method comprises the step of obtaining (32) a media description of the media stream, the media description indicating an initial element of the stream elements. A request for the initial stream element is sent (34) and a session control procedure is initiated (36) for a session. The media stream is associated (38) with the session in the session control procedure. The transmission of a subsequent element of the stream elements is controlled in accordance with a control rule of the session. Devices and further methods embodying the invention are also described.
The increasing complexity of information security threats and ever more stringent legal requirements mean that more and more organizations are setting themselves the goal of implementing an effective and efficient information security management system (ISMS). This paper examines the ways in which artificial intelligence (AI) in the form of a chatbot can support the development and operation of an ISMS. In particular, it evaluates how a chatbot can be integrated into standard setup and operating processes within an ISMS. In addition, various possible applications are shown and advantages, disadvantages and limitations are discussed. It turns out that the use of a chatbot as a supporting tool has many advantages and, in the hands of specialist personnel, offers a useful addition to established methods. Consequently, chatbots open up the possibility for organizations to optimize their organizational and operational processes.
Phishing remains one of the most common and effective forms of social engineering, with cybercriminals constantly refining their tactics to exploit human vulnerabilities. The sheer volume of phishing attacks is staggering: almost 1.2% of all emails sent are malicious. This equates to around 3.4 billion phishing emails per day. The effectiveness of phishing attacks is also underlined by numerous studies. Phishing is identified as the leading initial attack vector, responsible for 41% of security incidents. This means that practically every company is threatened by phishing attacks.In parallel, there have been rapid advances in the field of artificial intelligence (AI) in recent years, giving the general public access to powerful tools that can handle complex tasks with ease. However, alongside these benefits, the potential for abuse has also become a major concern. The integration of AI into social engineering attacks has significantly increased the opportunities for cybercriminals. Research has shown that AI-generated phishing emails are difficult for humans to distinguish from real messages. According to one study, phishing emails written by AI were opened by 78% of recipients, with 21% clicking on malicious content such as links or attachments. Although the click-through rate is still lower compared to human-crafted emails, generative AI tools (GenAI) can help cybercriminals compose phishing emails at least 40% faster, which can lead to a significant increase in phishing success rates. The increasing potential to use public AI tools for abusive purposes has also been recognized by the developers of AI models. Thus, publicly available AI tools often have built-in mechanisms to detect and prevent misuse. This paper examines the potential for misuse of publicly available AI in the context of phishing attacks, focusing on the content generation phase. In particular, the study examines the effectiveness of existing abuse prevention mechanisms implemented by AI platforms like fine-tuning, filters, rejection sampling, system prompts and dataset filtering. To this end, it is explored how prompts to the AI need to be altered for circumventing the misuse preventing mechanisms. While in some cases the simple request to write a phishing email succeeds, other AI tools implement more sophisticated mechanisms. In the end, however, all prevention safeguards could be circumvented. The findings highlight the significant threat posed by AI-powered social engineering attacks and emphasize the urgent need for robust defense in depth strategies against phishing attacks and increased awareness to mitigate the risks in the evolving digital landscape.In addition, the paper demonstrates that the quality of the AI tool varies in terms of the phishing emails generated. To this end, the phishing emails generated by circumventing the protection mechanisms of the AI are (subjectively) compared and evaluated by the authors. The preliminary conclusion is that automatically generated phishing emails of some public AI tools can certainly match that of manually generated emails. While the objective confirmation of this hypothesis requires further study even the subjective quality of the generated phishing emails shows the dimension of the problem.
A new goodness-of-fit test for the composite null hypothesis that data originate from a geometric Brownian motion is studied in the functional data setting. This is equivalent to testing if the data are from a scaled Brownian motion with linear drift. Critical values for the test are obtained, ensuring that the specified significance level is achieved in finite samples. The asymptotic behavior of the test statistic under the null distribution and alternatives is studied, and it is also demonstrated that the test is consistent. Furthermore, the proposed approach offers advantages in terms of fast and simple implementation. A comprehensive simulation study shows that the power of the new test compares favorably to that of existing methods. A key application is the assessment of financial time series for the suitability of the Black-Scholes model. Examples relating to various stock and interest rate time series are presented in order to illustrate the proposed test.
Das Planetarium in Bochum ist eine bedeutende kulturelle Institution der Stadt, die Wissenschaft und Kultur vereint. Ziel der Neugestaltung ist es, das Planetarium moderner und sichtbarer zu machen sowie sein kulturelles Ansehen zu stärken. Das Gestaltungskonzept richtet sich darauf aus, eine breitere, auch jüngere Zielgruppe anzusprechen und das Planetarium als Ort der Inspiration und Bildung sowie als festen Bestandteil der Bochumer Kulturszene zu festigen. Die Idee, dass Farben, Bildsprache und Typografie ihre Inspiration im Weltall finden, bildet die Grundlage des Designs und spiegelt die Faszination für das Universum in allen Gestaltungselementen wider.
Traditionally, agent architectures based on the Belief- Desire-Intention (BDI) model make use of precompiled plans, or if they do generate plans, the plans do not involve stochastic actions nor probabilistic observations. Plans that do involve these kinds of actions and observations are generated by partially observable Markov decision process (POMDP) planners. In particular for POMDP planning, we make use of a POMDP planner which is implemented in the robot programming and plan language Golog. Golog is very suitable for integrating beliefs, as it is based on the situation calculus and we can draw upon previous research on this. However, a POMDP planner on its own cannot cope well with dynamically changing environments and complicated goals. This is exactly a strength of the BDI model; the model is for reasoning over goals dynamically. Therefore, in this paper, we propose an architecture that will lay the groundwork for architectures that combine the advantages of a POMDP planner written in the situation calculus, and the BDI model of agency. We show preliminary results which can be seen as a proof of concept for integrating a POMDP into a BDI architecture.
A user-friendly, portable, low-cost readout system for the on-site or point-of-care characterization of chemo- and biosensors based on an electrolyte–insulator–semiconductor capacitor (EISCAP) has been developed using a thumb-drive-sized commercial impedance analyzer. The system is controlled by a custom Python script and allows to characterize EISCAP sensors with different methods (impedance spectra, capacitance-voltage, and constant-capacitance modes), which are selected in a user interface. The performance of the portable readout system was evaluated by pH measurements and the detection of the antibiotic penicillin, hereby using EISCAPs consisting of Al/p-Si/SiO₂/Ta₂O₅ structures and compared to the results obtained with a stationary commercial impedance analyzer. Both the portable and the commercial systems provide very similar results with almost perfectly overlapping recorded EISCAP signals. The new portable system can accelerate the transition of EISCAP sensors from research laboratories to commercial end-user devices.
Das vermehrte Aufkommen von Elektrofahrzeugen führt dazu, dass Lastspitzen durch erhöhtes Ladeaufkommen zu bestimmten Tageszeiten das Stromnetz überlasten. Im Gegensatz zum Status Quo, indem Lastspitzen ohne Regulierung toleriert werden, bedarf es einer „intelligenten“ Lösung zur dynamischen Glättung von Lastspitzen unter Vermeidung von Einschränkungen der Nutzungsmöglichkeiten bei gleichzeitiger Einhaltung physikalischer Obergrenzen der Netzinfrastruktur.
Dies ist zwingend erforderlich, um Netzausfälle zu vermeiden. Zukünftig wird diese Problemstellung durch die Distribution von Möglichkeiten des Smart-Chargings gelöst, welche individuell auf die aktuelle Netzlast, Marktgegebenheiten und den Ladebedarf reagieren. Ein mögliches Vorgehen zur Umsetzung wird in dieser Masterarbeit beschrieben. Zunächst wird eine technische Anforderungsanalyse durchgeführt. Die Machbarkeit wird mithilfe eines Prototyps einer Smart Charging Lösung nachgewiesen. Die Software bietet die Möglichkeit verschiedene Preisstrategien zu befolgen. Abschließend wird die Einhaltung der vorgegebenen funktionalen Anforderungen (REST-Protokolle: OSCP, OCPI; Websockets: OCPP; Anbindung an alle Netzteilnehmer: Ver-teilnetzbetreiber, App, Stromlieferant, Ladesäulenbetreiber) sowie nicht-funktionalen An-forderungen (bspw. geringe Kopplung der Module, flexible Erweiterbarkeit, performante Speicherung, Skalierbarkeit) beurteilt.
