Different from traditional transport systems, such as cars or trains, which are limited by land transit space, flying cars (such as UAS, drones, and air taxis) do not occupy space with traffic. They have a degree of freedom in space and time, smaller displacement, and consequently, less stress for their users. Large companies and researchers around the world are working with different architectures, algorithms, and techniques to test air taxi transport to serve a significant proportion of people safely and autonomously. One of the main issues surrounding the diffusion of air taxis is safety and security, since a simple failure can lead to the loss of high-value assets, loss of the vehicle, and/or injuries to human lives, including fatalities. In this sense, despite significant efforts, the literature is still specific and limited regarding air taxi safety and security. Therefore, this study aimed to carry out an extensive systematic literature review of the main modern advances in techniques, architectures, and research carried out around the world focused on these types of vehicles. More than 210 articles from between 2015 and January 2022 were individually reviewed. In addition, this study also presents gaps that could serve as a direction for future research. As far as the authors are aware, no other study performs this type of review focused on air taxi safety.

Smart homes are pervasive environments to enhance the comfort, the security, the safety and the energy consumption of the residence. An ambient intelligence system uses information of devices to represent the context of the home and its residents. Based on a context database, this system infer the daily life activities of the resident. Hence, abnormal behavior or chronic disease can be detected by the system. Due to the complexity of these systems, a large variety of anomalies may occur and disrupt the functioning of critical and essential applications. To detect anomalies and take appropriate measures, an anomaly management system has to be integrated in the overall architecture. In this paper, we propose an anomaly management framework for smart homes. This framework eases the work of designers in the conception of anomaly detection modules and processes to respond to an anomaly appropriately. Our framework can be used in all heterogeneous environments such as smart home because it uses Semantic Web ontologies to represent anomaly information. Our framework can be useful to detect hardware, software, network, operator and context faults. To test the efficiency of our anomaly management framework, we integrate it in the universAAL middleware. Based on a reasoner, our framework can easily infer some context anomalies and take appropriate measures to restore the system in a full functioning state

Network security is a crucial issue of Software Defined Networking (SDN). It is probably, one of the key features for the success and the future pervasion of the SDN technology. In this perspective, we propose a SDN reactive stateful firewall. Our solution is integrated into the SDN architecture. The application filters TCP communications according to the network security policies. It records and processes the different states of connections and interprets their possible transitions into OpenFlow (OF) rules. The proposition uses a reactive behavior in order to reduce the number of OpenFlow rules in the data plane devices and to mitigate some Denial of Service (DoS) attacks like SYN Flooding. The firewall processes the Finite State Machine of network protocols so as to withdraw useless traffic not corresponding to their transitions’ conditions. In terms of cost efficiency, our proposal empowers the behavior of Openflow compatible devices to make them behaving like stateful firewalls. Therefore, organizations do not need to spend money and resources on buying and maintaining conventional firewalls. Furthermore, we propose an orchestrator in order to spread and to reinforce security policies in the whole network with a fine grained strategy. It is thereupon able to secure the network by filtering the traffic related to an application, a node, a subnetwork connected to a data plane device, a sub SDN network connected to a controller, traffic between different links, etc. The deployment of rules of the firewall becomes flexible according to a holistic network view provided by the management plane. In addition, the solution enlarges the security perimeter inside the network by securing accesses between its internal nodes.

Today with the emergence of an industrial information system in industry of the future which includes the connection between all trades, applications and the converged technologies between information technology and operational technology, cybersecurity has become urgent. Industrial Intrusion Detection System are no longer sufficient to counter cyberattacks because of their natures, which is usually misuse, and are unable to detect attacks that target the application layer of the Open Systems Interconnection model. Therefore, cybersecurity in industrial systems adopts known information technology security solutions, such as an Intrusion Detection System which has to be modified, completed and adapted to work in industrial field. We propose to deepen this approach by developing an adapted IDS to monitor industrial systems against illegitimate access and detect abnormal activities. For this purpose, we expose in this paper our efficient hybrid intrusion detection solution based on International Society of Automation 95 standard and neural network. Our research work is focused on Manufacturing Executive System which represents the central and main element in industry.