The aviation domain is undergoing rapid digital transformation, exposing air navigation systems, surveillance, communication, and data sharing architectures to evolving cyber threats. While the MITRE ATT&CK framework is widely adopted in defense and detection contexts, its potential for guiding offensive security testing in aviation remains underexplored. In this paper, we present a structured methodology to map adversary emulation and penetration testing activities onto ATT&CK tactics and techniques, and apply it in a case study targeting System Wide Information Management (SWIM) and related Air Traffic Control (ATC) systems. We demonstrate how each phase of an offensive workflow, from reconnaissance to impact can be contextualized to aviation-specific assets, identify gaps in defenses, and derive mitigation strategies aligned with ATT&CK’s mitigations. Our results show that this approach can systematically uncover vulnerabilities in aviation systems and provide a common framework b ridging offense and defense. We discuss challenges, limitations, and directions for further research.

Smart meters (SM) generate critical data that provides real-time insights into energy consumption, grid performance, and load management, which are essential for improving grid reliability, energy efficiency, and renewable energy integration. However, achieving effective communication between smart meters and the control center remains a challenge due to limitations in Advanced Metering Infrastructure (AMI), including communication delays, metering technology constraints, and restricted data storage and processing capabilities. These limitations hinder the precision and timeliness of real-time data delivery, negatively impacting the efficiency of energy management and grid operations. While existing research predominantly focuses on optimizing communication network algorithms, the critical issue of comprehensive SM data scheduling has received limited attention. Moreover, current methods often fail to account for the complexity of communication networks and the dynamic nature of information flow. To address this gap, this paper introduces a novel method for scheduling SM data access by leveraging real-time data assessment and analysis. A quality metric termed mismatch probability evaluates data quality, and the Hungarian algorithm is employed to optimize meter scheduling. The proposed method is validated using real-world data from a Danish grid, demonstrating significant improvements in information quality for real-time monitoring compared to heuristic-based scheduling approaches.

Increased use of distributed renewable energy resources in low-voltage distribution grids open up for communication-based voltage control. However, non-ideal communication can affect the system and cause damage to the system. In particular, long update intervals, delays, and packet losses can be seen as imperfections of communication and should be compensated for. One solution is modeling these features and compensating for them in the control method. In this paper, a hybrid method to model the communication features and electrical grid together is presented. The model considers continuous dynamics of the electrical grid, discrete dynamics of the communication, as well as long update rates of communication, delays, and packet losses.

Energy systems are evolving towards 100% green energy production. The share of green energy in electrical distribution systems is progressively increasing, implying also an increment on the number of renewable energy units in the low-voltage grid. Following this trend, thousands of consumers connected to the power grid in a decentralized manner become small producers, changing the traditional paradigm of energy distribution from top to bottom. Currently, the modern Advanced Metering Infrastructure (AMI) enables the possibility of collecting several types of status data from the end-users which Distribution System Operators (DSOs) can use to their advantage to optimize management and planning operations. As a part of this optimization, having a spatial overview over the low-voltage grid can speed up the monitoring processes and allows to obtain a real-time insight on what is happening in the grid, compared to the traditionally used analysis methods. Many business structures for smart grid cyber physical systems are looking into how to integrate advanced data management models. Such models should provide the means for obtaining meaningful data visualization where only the relevant data is timely processed, filtered and visualized for the operators to efficiently react to grid anomalies in real-time.The purpose of this paper is to investigate how to efficiently design a monitoring/visualization system for low-voltage electrical grids based on the DSOs' needs and feedback. The proposed system implementation stands on emulating an existing geographic scenario by a virtual AMI integration. The efficiency of the prototype is evaluated versus the traditional monitoring operations derived from user experience studies, such as a reduction in time to perform a specific anomaly detection operation. Furthermore, the advantages of spatial awareness are meant to further strengthen the motivation for integrating measurements into a Geographic Information System (GIS) environment.

At the consumer level in the electrical grid, the increase in distributed power generation from renewable energy resources creates operational challenges for the DSOs. Nowadays, grid data is only used for billing purposes. Intelligent management tools can facilitate enhanced control of the power system, where the first step is the ability to monitor the grid state in near-real-time. Therefore, the concepts of smart grids and Internet of Things can enable future enhancements via the application of smart analytics. This paper introduces a use case for low voltage grid observability. The proposal involves a state estimation algorithm (DSSE) that aims to eliminate errors in the received meter data and provide an estimate of the actual grid state by replacing missing or insufficient data for the DSSE by pseudo-measurements acquired from historical data. A state of the art of historical and near-real-time analytics techniques is further presented. Based on the proposed study model and the survey, the team near-real-time is defined. The proposal concludes with an evaluation of the different analytical methods and a subsequent set of recommendations best suited for low voltage grid observability.

Multiplayer online games are on the rise with millions of registered player and hundreds of thousands concurrent players. Current state of the art servers achieve scalability by splitting the game world into linked mini worlds that can be hosted on separate servers. One of the problems is that, players are flocking to one area, resulting in an overloaded server with decreasing Quality of Service(QoS) for the players. A number of approaches were developed to address these issues, by balancing loads between the over-loaded and under-loaded servers. This paper investigates a new dimension that is created due to the load balancing of servers. Load balancing among servers is sensitive to correct status information. The Markov based load prediction was introduced in this paper to predict load of under-loaded servers, based on arrival (μ) and departure (λ) rates of players. The prediction based algorithm is proposed to minimize the effect of out dated status information. This approach was compared with normal load status information exchange algorithm. The model presented in this paper does not deal directly with optimizing the load balancing of the server but rather tries to present a new insight that need to be considered when developing load balancing algorithm, that is the reliability of the information that is shared. Simulation results show that Markov based prediction of load information performed better from the normal load status information sharing.

The integration of renewable energy sources into the power grid requires added control intelligence which imposes new communication requirements onto the future power grid. Since large scale implementation of new communication infrastructure is infeasible, we consider methods of increasing dependability of existing networks. We develop models for network delays and information dynamics, and uses these to model information quality for three given information access schemes in an event triggered control scenario. We analyse the impact of model parameters, and show how optimal choice of information access scheme depends on network conditions as well as trade-offs between information quality, network resources and control reactivity.

The increasing amount of smart devices and handheld devices have widened the amount of information presence all over. The application running on one device can be distributed to a surrounding device for better functionality. A capability that might be enjoyable or frustrating for end user. This paper has identified the factors that contribute to the loss of user experience for seamless application migration in a context aware environment. These are the context information updates, transfer time and resumption time. To quantify the loss of user experience, a Quality of experience (QoE) Loss score value (representing the time that is lost in user experience during migrating process)is introduced. A high QoE loss score value indicates a higher loss of user experience and a lower QoE loss score value indicate a lower loss of user experience. A test-bed setup was implemented and different policies of migration processes in a context aware environment were evaluated.

For WLAN systems in which relaying is used to improve throughput performance for nodes located at the cell edge, node mobility and information collection delays can have a significant impact on the performance of a relay selection scheme. In this paper we extend our existing Markov Chain modeling framework for relay selection to allow for efficient calculation of relay policies given either mean throughput or kth throughput percentile as optimization criterium. In a scenario with static access point, static relay, and a mobile destination node, the kth throughput percentile optimization is furthermore shown to be beneficial for improving throughput among weak node positions that will otherwise achieve zero throughput.

Context-awareness is a key requirement in many of today's networks, services and applications. Context Management systems are in this respect used to provide access to distributed, dynamic context information. The reliability of remotely accessed dynamic context information is challenged by network delay, packet drop probability, information dynamics and the access strategies taken. QoS classification and system configuration of context management traffic is in this aspect important in order to efficiently balance generated access traffic between network delay, packet loss probability, information dynamics and reliability requirements to the information from the applications. In this paper we develop a QoS Control network concept for context management systems. The concept includes a soft realtime algorithm for model based context access configuration and QoS class assignment, and allows to put probabilistic bounds on.

When devices are mobile, they potentially move within range of several different wireless networks, which are not utilized due to security, inactive radios or it is just plain cumbersome for the user to exploit them. This paper proposes a vertical handover algorithm to utilize these networks, which selects the best available network at a given time, factoring in prediction of user movement, energy consumption, QoS of connections and application demand for the end-to-end connection in a (multiple) client/server setting. The algorithm allows support for different mechanisms of interaction, where we in this paper focus on 1) peer-to-peer in a WLAN setting, 2) p2p behind NAT and 3) what we call a server bounce mechanism. The algorithm is supported by a User-specific Virtual Network to obtain required network state information. Experimental tests are conducted, using both simulations and actual implementation on Android based tablets. The simulations cover a wide range of scenarios for two mobile users in an urban area with ubiquitous cellular coverage, and shows our algorithm leads to increased throughput, with fewer handovers, when considering the end-to-end connection than to other handover schemes. The implementation utilizing real world networks, shows the feasibility of the algorithm due to its low complexity compared to other algorithms.

For centralized selection of communication relays, the necessary decision information needs to be collected from the mobile nodes by the access point (centralized decision point). In mobile scenarios, the required information collection and forwarding delays will affect the reliability of the collected information and hence will influence the performance of the relay selection method. This paper analyzes this influence in the decision process for the example of a mobile location-based relay selection approach using a continuous time Markov chain model. The model is used to obtain optimal relay policies via a heuristically reduced brute-force search. Numerical results show how forwarding delays affect these optimal policies.

Context aware network services are a new and interesting way to enhance network users experience. A context aware application/service enhances network performance in relation to dynamic context information, e.g. mobility, location and device information as it senses and reacts to environment changes. The reliability of the information accessed is a key factor in achieving reliable context aware application. This paper will review the service degradation in Context Management Frameworks (CMF) and the effect of high network utilization, with particular focus on the reliability of the accessed information. The paper considers a developed framework from the ICT project, OPEN, and investigates the impact of applying Differentiated Services (DiffServ) Quality of Services (QoS). The paper finally provides insight in how the insight gained can be utilized to ensure reliable remote accessed context information.

Location information has become an important enabler for services that interacts with the physical environment. Focus has therefore been on providing accurate information on the user's position, but less on the reliability of the information. This paper gives a methodology to evaluate numerically the reliability of estimated positioning of mobile devices, and shows how the methodology can be applied to decide upon the trade-off between reliability and accuracy of location systems.

Efficient access strategies to dynamically changing context information is an important functionality in many scenarios of context-sensitive networking. Access delay requirements and bounded communication overhead can be achieved via caching of the remotely available context information; meeting such QoS constraints is particularly relevant for wireless settings. However, caching increases the probability that the used context information does not correspond to its true value at the remote node. The paper develops a quantitative analytic model to calculate mismatch probability, mean access delay, and network overhead as a function of the cache lifetimes, network delays, request rates, and properties of the dynamically changing context information. Parametric studies of these performance metrics provide insights into the impact of different distribution types and parameter choices on these performance metrics. Due to monotonicity properties, the choice of optimal cache durations can be reduced to numerical solutions of the analytic equations. Results for two optimality criterions are presented and discussed. The quantitative models presented in this paper allow to implement adaptive caching strategies for context-sensitive networking functionalities.

Remote access to dynamically changing information elements is a required functionality for various network services, including routing and instances of context-sensitive networking. Three fundamentally different strategies for such access are investigated in this paper: (1) a reactive approach initiated by the requesting entity, and two versions of proactive approaches in which the entity that contains the information element actively propagates its changes to potential requesters, either (2) periodically or triggered by changes of the information element (3). This paper first develops a set of analytic models to compute different performance metrics for these approaches, with special focus on the so-called mismatch probability. The results of the analytic models allow for design decisions on which strategy to implement for specific input parameters (change rate of the information element, network delay characterization) and specific requirements on mismatch probability, traffic overhead, and access delay. Finally, the analysis is applied to the use-case of context-sensitive service discovery.

In this paper we introduce a high level architecture for a context management system for personal networks (PN). The main objective of the context management framework (CMF) described in this paper is to support the interactions between context information sources and context aware components, services and applications in a generic manner, independently of their nature and operation area. To this end, we propose a structure consisting of a context management interface, context access manager module, processing and storage module, and a data source abstraction layer. Nodes provide a certain set of these modules depending on their computational capabilities and their role within the system. We differentiate between basic context nodes (BCN), enhanced context nodes (ECN) and context management nodes (CMN) within the CMF. CMNs operate on two levels, i.e., local/cluster level and PN level. In the paper we also describe how these entities will interact with each other and how different context information will be exchanged within the personal network. Finally, we provide an outlook of the work and issues that need to be addressed in order to complete the described framework