The energy importance of additional information

The cornerstone of the Smart City conception is the application of an advanced info-communication infrastructure. One of the main tasks of info-communication systems is the transmission of information. During transmission, however, not only the data representing the required information is transmitted, but also extra data. According to the receiver-side monitoring aspect of the communication, this involves some additional information. This additional information can be examined in many ways. The aim of the present study is to investigate the energy significance of additional information. During the investigation, the appearance of additional information is represented with an older Internet game. This game provides an opportunity to detect the incorporation and decoding of extra data. The study is then based on the energy balance modeling of the systems to point out the nature of the energy problems of such supplementary informatio

The Role of Additional Information in Obtaining Information

One of the basic components of the smart city concept is the infocommunication infrastructure. The purpose of the infocommunication system is, among others, to transmit information. Generally, besides the necessary information provided in a transmission, some additional information is displayed as well. In public communication the destination of the information is not a specific person or object. Therefore, additional information can be obtained by anyone. Thus, such additional information facilitates the unwanted acquisition of information and its later use. The present study illustrates the role of additional information in obtaining information through an example of an online game. This game is public, therefore, it is an open source of information. The technology of Open Source Intelligence is one of the basic elements of the social engineering information palette

On synergies of cyber and physical security modelling in vulnerability assessment of railway systems

The multifaceted nature of cyber-physical systems needs holistic study methods to detect essential aspects and interrelations among physical and cyber components. Like the systems themselves, security threats feature both cyber and physical elements. Although to apply divide et impera approaches helps handling system complexity, to consider just one aspect at a time does not provide adequate risk awareness and hence does not allow to design the most appropriate countermeasures. To support this claim, in this paper we provide a joint application of two model-driven techniques for physical and cyber-security evaluation. We apply two UML profiles, namely SecAM (for cyber-security) and CIP_VAM (for physical security), in combination. In such a way, we demonstrate the synergy between both profiles and the need for their tighter integration in the context of a reference case study from the railway domain

On synergies of cyber and physical security modelling in vulnerability assessment of railway systems

The multifaceted nature of cyber-physical systems needs holistic study methods to detect essential aspects and interrelations among physical and cyber components. Like the systems themselves, security threats feature both cyber and physical elements. Although to apply divide et impera approaches helps handling system complexity, to consider just one aspect at a time does not provide adequate risk awareness and hence does not allow to design the most appropriate countermeasures. To support this claim, in this paper we provide a joint application of two model-driven techniques for physical and cyber-security evaluation. We apply two UML profiles, namely SecAM (for cyber-security) and CIP_VAM (for physical security), in combination. In such a way, we demonstrate the synergy between both profiles and the need for their tighter integration in the context of a reference case study from the railway domain

Anomalous behaviour detection for cyber defence in modern industrial control systems

A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy.The fusion of pervasive internet connectivity and emerging technologies in smart cities creates fragile cyber-physical-natural ecosystems. Industrial Control Systems (ICS) are intrinsic parts of smart cities and critical to modern societies. Not designed for interconnectivity or security, disruptor technologies enable ubiquitous computing in modern ICS. Aided by artificial intelligence and the industrial internet of things they transform the ICS environment towards better automation, process control and monitoring. However, investigations reveal that leveraging disruptive technologies in ICS creates security challenges exposing critical infrastructure to sophisticated threat actors including increasingly hostile, well-organised cybercrimes and Advanced Persistent Threats. Besides external factors, the prevalence of insider threats includes malicious intent, accidental hazards and professional errors. The sensing capabilities create opportunities to capture various data types. Apart from operational use, this data combined with artificial intelligence can be innovatively utilised to model anomalous behaviour as part of defence-in-depth strategies. As such, this research aims to investigate and develop a security mechanism to improve cyber defence in ICS. Firstly, this thesis contributes a Systematic Literature Review (SLR), which helps analyse frameworks and systems that address CPS’ cyber resilience and digital forensic incident response in smart cities. The SLR uncovers emerging themes and concludes several key findings. For example, the chronological analysis reveals key influencing factors, whereas the data source analysis points to a lack of real CPS datasets with prevalent utilisation of software and infrastructure-based simulations. Further in-depth analysis shows that cross-sector proposals or applications to improve digital forensics focusing on cyber resilience are addressed by a small number of research studies in some smart sectors. Next, this research introduces a novel super learner ensemble anomaly detection and cyber risk quantification framework to profile anomalous behaviour in ICS and derive a cyber risk score. The proposed framework and associated learning models are experimentally validated. The produced results are promising and achieve an overall F1-score of 99.13%, and an anomalous recall score of 99% detecting anomalies lasting only 17 seconds ranging from 0.5% to 89% of the dataset. Further, a one-class classification model is developed, leveraging stream rebalancing followed by adaptive machine learning algorithms and drift detection methods. The model is experimentally validated producing promising results including an overall Matthews Correlation Coefficient (MCC) score of 0.999 and the Cohen’s Kappa (K) score of 0.9986 on limited variable single-type anomalous behaviour per data stream. Wide data streams achieve an MCC score of 0.981 and a K score of 0.9808 in the prevalence of multiple types of anomalous instances. Additionally, the thesis scrutinises the applicability of the learning models to support digital forensic readiness. The research study presents the concept of digital witness and digital chain of custody in ICS. Following that, a use case integrating blockchain technologies into the design of ICS to support digital forensic readiness is discussed. In conclusion, the contributions of this research thesis help towards developing the next generation of state-of-the-art methods for anomalous behaviour detection in ICS defence-in-depth

Multikonferenz Wirtschaftsinformatik (MKWI) 2016: Technische Universität Ilmenau, 09. - 11. März 2016; Band II

Übersicht der Teilkonferenzen Band II • eHealth as a Service – Innovationen für Prävention, Versorgung und Forschung • Einsatz von Unternehmenssoftware in der Lehre • Energieinformatik, Erneuerbare Energien und Neue Mobilität • Hedonische Informationssysteme • IKT-gestütztes betriebliches Umwelt- und Nachhaltigkeitsmanagement • Informationssysteme in der Finanzwirtschaft • IT- und Software-Produktmanagement in Internet-of-Things-basierten Infrastrukturen • IT-Beratung im Kontext digitaler Transformation • IT-Sicherheit für Kritische Infrastrukturen • Modellierung betrieblicher Informationssysteme – Konzeptuelle Modelle im Zeitalter der digitalisierten Wirtschaft (d!conomy) • Prescriptive Analytics in I