Benefits of Location-Based Access Control:A Literature Study

Location-based access control (LBAC) has been suggested as a means to improve IT security. By 'grounding' users and systems to a particular location, \ud attackers supposedly have more difficulty in compromising a system. However, the motivation behind LBAC and its potential benefits have not been investigated thoroughly. To this end, we perform a structured literature review, and examine the goals that LBAC can potentially fulfill, \ud the specific LBAC systems that realize these goals and the context on which LBAC depends. Our paper has four main contributions:\ud first we propose a theoretical framework for LBAC evaluation, based on goals, systems and context. Second, we formulate and apply criteria for evaluating the usefulness of an LBAC system. Third, we identify four usage scenarios for LBAC: open areas and systems, hospitals, enterprises, and finally data centers and military facilities. Fourth, we propose directions for future research:\ud (i) assessing the tradeoffs between location-based, physical and logical access control, (ii) improving the transparency of LBAC decision making, and \ud (iii) formulating design criteria for facilities and working environments for optimal LBAC usage

Policy inconsistency detection bassed on RBAC model in cross-organizational collaboration

Policy integration and conflict resolutions among various organizations still remain a major challenge.Moreover, policy inconsistency detection approach with logical reasoning techniques which considers integration requirements from collaboration parties has not been well studied.In this paper, we proposed a model to detect inconsistencies based on role-based access control (RBAC) that considers role hierarchy (RH) and temporal and spatial constraints.A model to prune and collect only the required policies based on access control requirements from different organizations is designed.Policy inconsistency detection should be enhanced with logical-based analysis in order to develop security policy integration.We believe this work could provide manner to filter a large amount of unrelated policies and only return potential collaboration policies for conflict resolution

Electrotactile Communication via Matrix Electrode Placed on the Torso Using Fast Calibration, and Static vs. Dynamic Encoding

Electrotactile stimulation is a technology that reproducibly elicits tactile sensations and can be used as an alternative channel to communicate information to the user. The presented work is a part of an effort to develop this technology into an unobtrusive communication tool for first responders. In this study, the aim was to compare the success rate (SR) between discriminating stimulation at six spatial locations (static encoding) and recognizing six spatio-temporal patterns where pads are activated sequentially in a predetermined order (dynamic encoding). Additionally, a procedure for a fast amplitude calibration, that includes a semi-automated initialization and an optional manual adjustment, was employed and evaluated. Twenty subjects, including twelve first responders, participated in the study. The electrode comprising the 3 × 2 matrix of pads was placed on the lateral torso. The results showed that high SRs could be achieved for both types of message encoding after a short learning phase; however, the dynamic approach led to a statistically significant improvement in messages recognition (SR of 93.3%), compared to static stimulation (SR of 83.3%). The proposed calibration procedure was also effective since in 83.8% of the cases the subjects did not need to adjust the stimulation amplitude manually

Multiscale design for system-wide peer-to-peer energy trading

The integration of renewable generation and the electrification of heating and transportation are critical for the sustainable energy transition toward net-zero greenhouse gas emissions. These changes require the large-scale adoption of distributed energy resources (DERs). Peer-to-peer (P2P) energy trading has gained attention as a new approach for incentivizing the uptake and coordination of DERs, with advantages for computational scalability, prosumer autonomy, and market competitiveness. However, major unresolved challenges remain for scaling out P2P trading, including enforcing network constraints, managing uncertainty, and mediating transmission and distribution conflicts. Here, we propose a novel multiscale design framework for P2P trading, with inter-platform coordination mechanisms to align local transactions with system-level requirements, and analytical tools to enhance long-term planning and investment decisions by accounting for forecast real-time operation. By integrating P2P trading into planning and operation across spatial and temporal scales, the adoption of large-scale DERs is tenable and can create economic, environmental, and social co-benefits

A review of the role of spatial resolution in energy systems modelling:Lessons learned and applicability to the North Sea region

The importance of spatial resolution for energy modelling has increased in the last years. Incorporating more spatial resolution in energy models presents wide benefits, but it is not straightforward, as it might compromise their computational performance. This paper aims to provide a comprehensive review of spatial resolution in energy models, including benefits, challenges and future research avenues. The paper is divided in four parts: first, it reviews and analyses the applications of geographic information systems (GIS) for energy modelling in the literature. GIS analyses are found to be relevant to analyse how meteorology affects renewable production, to assess infrastructure needs, design and routing, and to analyse resource allocation, among others. Second, it analyses a selection of large scale energy modelling tools, in terms of how they can include spatial data, which resolution they have and to what extent this resolution can be modified. Out of the 34 energy models reviewed, 16 permit to include regional coverage, while 13 of them permit to include a tailor-made spatial resolution, showing that current available modelling tools permit regional analysis in large scale frameworks. The third part presents a collection of practices used in the literature to include spatial resolution in energy models, ranging from aggregated methods where the spatial granularity is non-existent to sophisticated clustering methods. Out of the spatial data clustering methods available in the literature, k-means and max-p have been successfully used in energy related applications showing promising results. K-means permits to cluster large amounts of spatial data at a low computational cost, while max-p ensures contiguity and homogeneity in the resulting clusters. The fourth part aims to apply the findings and lessons learned throughout the paper to the North Sea region. This region combines large amounts of planned deployment of variable renewable energy sources with multiple spatial claims and geographical constraints, and therefore it is ideal as a case study. We propose a complete modelling framework for the region in order to fill two knowledge gaps identified in the literature: the lack of offshore integrated system modelling, and the lack of spatial analysis while defining the offshore regions of the modelling framework