Checking and Enforcing Security through Opacity in Healthcare Applications

The Internet of Things (IoT) is a paradigm that can tremendously revolutionize health care thus benefiting both hospitals, doctors and patients. In this context, protecting the IoT in health care against interference, including service attacks and malwares, is challenging. Opacity is a confidentiality property capturing a system's ability to keep a subset of its behavior hidden from passive observers. In this work, we seek to introduce an IoT-based heart attack detection system, that could be life-saving for patients without risking their need for privacy through the verification and enforcement of opacity. Our main contributions are the use of a tool to verify opacity in three of its forms, so as to detect privacy leaks in our system. Furthermore, we develop an efficient, Symbolic Observation Graph (SOG)-based algorithm for enforcing opacity

Modeling and simulation of the two-tank system within a hybrid framework

Most real-world dynamical systems are often involving continuous behaviors and discrete events, in this case, they are called hybrid dynamical systems (HDSs). To properly model this kind of systems, it is necessary to consider both the continuous and the discrete aspects of its dynamics. In this paper, a modeling framework based on the hybrid automata (HA) approach is proposed. This hybrid modeling framework allows combining the multi-state models of the system, described by nonlinear differential equations, with the system’s discrete dynamics described by finite state machines. To attest to the efficiency of the proposed modeling framework, its application to a two-tank hybrid system (TTHS) is presented. The TTHS studied is a typical benchmark for HDSs with four operating modes. The MATLAB Simulink and Stateflow tools are used to implement and simulate the hybrid model of the TTHS. Different simulations results demonstrate the efficiency of the proposed modeling framework, which allows us to appropriately have a complete model of an HDS

Quantitative Analysis of Opacity in Cloud Computing Systems

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Federated cloud systems increase the reliability and reduce the cost of the computational support. The resulting combination of secure private clouds and less secure public clouds, together with the fact that resources need to be located within different clouds, strongly affects the information flow security of the entire system. In this paper, the clouds as well as entities of a federated cloud system are assigned security levels, and a probabilistic flow sensitive security model for a federated cloud system is proposed. Then the notion of opacity --- a notion capturing the security of information flow --- of a cloud computing systems is introduced, and different variants of quantitative analysis of opacity are presented. As a result, one can track the information flow in a cloud system, and analyze the impact of different resource allocation strategies by quantifying the corresponding opacity characteristics

Identification and Visualization of the Conceptual Structure and Main Research Themes of Studies in Informatics and Control Journal from 2008 to 2019

Studies in Informatics and Control journal is a quarterly publication for all those involved in the field of Information Technology (IT). Studies in Informatics and Control journal provides important perspectives on topics relevant to IT, with an emphasis on useful applications in the most important areas of IT, and it is aimed at advanced practitioners and researchers in the field of IT. The core subjects covered by Studies in Informatics and Control journal are relating to innovative research and practice in Information Technology: IT use in control and management systems; integration of IT with control; application of IT in socio-economic systems and manufacturing processes, mainly. The current research conducts a bibliometric performance and conceptual structure analysis of Studies in Informatics and Control journal from 2008 to 2019. Firstly, the journal performance is analysed according to the data retrieved from the Web of Science Core Collection, putting the focus on the productivity of the authors, citations, countries, organizations and most relevant publications. Finally, the conceptual structure of the journal is analysed with bibliometric software tool SciMAT, identifying the main thematic areas that have been the object of research, their composition, relationship and evolution during the period analysed

Zelus renardii Roaming in Southern Italy

This study collects data from the literature and updates our Zelus renardii Kolenati, 1856 (Leafhopper Assassin Bug, LAB) prey knowledge. The literature consists of ca. 170 entries encompassing the years 1856 to 2021. This reduviid originated in the Nearctic region, but has entered and acclimatised in many Mediterranean countries. Our quantitative predation experiments—in the laboratory on caged plants plus field or environmental observations—confirm that LAB prefers a selected array of prey. Laboratory predation tests on living targets (Hemiptera, Coleoptera, Diptera, and Hymenoptera) agree with the literature. Zelus renardii prefers comparatively large, highly mobile, and readily available prey. LAB preferences on available hemipterans targets suggest that Zelus renardii is a good inundative biocontrol agent for Xylella fastidiosa pauca ST53 infections. LAB also prey on other important olive pests, such as Bactrocera oleae. Therefore, Zelus renardii is a major integrated pest management (IPM) component to limit Xylella fastidiosa pandemics and other pest invasions

Qualitative and Quantitative Risk Analysis and Safety Assessment of Unmanned Aerial Vehicles Missions Over the Internet

In the last few years, unmanned aerial vehicles (UAVs) are making a revolution as an emerging technology with many different applications in the military, civilian, and commercial elds. The advent of autonomous drones has initiated serious challenges, including how to maintain their safe operation during their missions. The safe operation of UAVs remains an open and sensitive issue since any unexpected behavior of the drone or any hazard would lead to potential risks that might be very severe. The motivation behind this work is to propose a methodology for the safety assurance of drones over the Internet (Internet of drones (IoD)). Two approaches will be used in performing the safety analysis: (1) a qualitative safety analysis approach and (2) a quantitative safety analysis approach. The rst approach uses the international safety standards, namely, ISO 12100 and ISO 13849 to assess the safety of drone's missions by focusing on qualitative assessment techniques. The methodology starts with hazard identi cation, risk assessment, risk mitigation, and nally draws the safety recommendations associated with a drone delivery use case. The second approach presents a method for the quantitative safety assessment using Bayesian networks (BN) for probabilistic modeling. BN utilizes the information provided by the rst approach to model the safety risks related to UAVs' ights. An illustrative UAV crash scenario is presented as a case study, followed by scenario analysis, to demonstrate the applicability of the proposed approach. These two analyses, qualitative and quantitative, enable all involved stakeholders to detect, explore, and address the risks of UAV ights, which will help the industry to better manage the safety concerns of UAVs.info:eu-repo/semantics/publishedVersio

Using Probabilistic Temporal Logic PCTL and Model Checking for Context Prediction

Context prediction is a promoting research topic with a lot of challenges and opportunities. Indeed, with the constant evolution of context-aware systems, context prediction remains a complex task due to the lack of formal approach. In this paper, we propose a new approach to enhance context prediction using a probabilistic temporal logic and model checking. The probabilistic temporal logic PCTL is used to provide an efficient expressivity and a reasoning based on temporal logic in order to fit with the dynamic and non-deterministic nature of the system's environment. Whereas, the probabilistic model checking is used for automatically verifying that a probabilistic system satisfies a property with a given likelihood. Our new approach allows a formal expressivity of a multidimensional context prediction. Tested on real data our model was able to achieve 78% of the future activities prediction accuracy