Distribution of DDS-cerberus Authenticated Facial Recognition Streams

Successful missions in the field often rely upon communication technologies for tactics and coordination. One middleware used in securing these communication channels is Data Distribution Service (DDS) which employs a publish-subscribe model. However, researchers have found several security vulnerabilities in DDS implementations. DDS-Cerberus (DDS-C) is a security layer implemented into DDS to mitigate impersonation attacks using Kerberos authentication and ticketing. Even with the addition of DDS-C, the real-time message sending of DDS also needs to be upheld. This paper extends our previous work to analyze DDS-C’s impact on performance in a use case implementation. The use case covers an artificial intelligence (AI) scenario that connects edge sensors across a commercial network. Specifically, it characterizes how DDS-C performs between unmanned aerial vehicles (UAV), the cloud, and video streams for facial recognition. The experiments send a set number of video frames over the network using DDS to be processed by AI and displayed on a screen. An evaluation of network traffic using DDS-C revealed that it was not statistically significant compared to DDS for the majority of the configuration runs. The results demonstrate that DDS-C provides security benefits without significantly hindering the overall performance

Simulation and evaluation of deep learning autoencoders for image compression in multi-UAV network systems

Mobile multi-robot systems are versatile alternatives for improving single-robot capacities in many applications, such as logistics, environmental monitoring, search and rescue, photogrammetry, etc. In this sense, this kind of system must have a reliable communication network between the vehicles, ensuring that information exchanged within the nodes has little losses. This work simulates and evaluates the use of autoencoders for image compression in a multi-UAV simulation with ROS and Gazebo for a generic surveillance application. The autoencoder model was developed with the Keras library, presenting good training and validation results, with training and validation accuracy of 70%, and a Peak Signal Noise Ratio (PSNR) of 40dB. The use of the CPU for the simulated UAVs for processing and sending compressed images through the network is 25% faster. The results showed that this compression methodology is a good choice for improving the system’s performance without losing too much information.The authors thank CEFET/RJ, UFF, UFRJ, and the Brazilian research agencies CAPES, CNPq, and FAPERJ. Besides, the authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757/2020) and SusTEC (LA/P/0007/2021).info:eu-repo/semantics/publishedVersio

UAV IoT frameworks views and challenges : towards protecting drones as "things"

Unmanned aerial vehicles (UAVs) have enormous potential in enabling new applications in various areas, ranging from military, security, medicine, and surveillance to traffic-monitoring applications. Lately, there has been heavy investment in the development of UAVs and multi-UAVs systems that can collaborate and complete missions more efficiently and economically. Emerging technologies such as 4G/5G networks have significant potential on UAVs equipped with cameras, sensors, and GPS receivers in delivering Internet of Things (IoT) services from great heights, creating an airborne domain of the IoT. However, there are many issues to be resolved before the effective use of UAVs can be made, including security, privacy, and management. As such, in this paper we review new UAV application areas enabled by the IoT and 5G technologies, analyze the sensor requirements, and overview solutions for fleet management over aerial-networking, privacy, and security challenges. Finally, we propose a framework that supports and enables these technologies on UAVs. The introduced framework provisions a holistic IoT architecture that enables the protection of UAVs as "flying" things in a collaborative networked environment

DESIGN AND IMPLEMENTATION OF A DISTRIBUTED LEDGER TO SUPPORT DATA SURVIVABILITY IN AN UNMANNED MULTI-VEHICLE SYSTEM

Autonomous vehicle systems, including multi-vehicle systems, are becoming increasingly relevant in military operations. A problem emerges, however, when logging data within these systems. In particular, loss of individual vehicles and inherently lossy and noisy communications environments can result in the loss of important mission data. This thesis presents a novel distributed ledger protocol that can be used to ensure that the data in such a system survives. To test the efficacy of the protocol, we implemented it as a Robot Operating System (ROS) node on the Advanced Robotic Systems Engineering Laboratory (ARSENL) aerial swarm system. Results are presented for implementation tests in the ARSENL software-in-the-loop simulation environment and during live-flight field experiments conducted at Camp Roberts, CA.Outstanding ThesisCivilian, CyberCorps: Scholarship for ServiceApproved for public release. distribution is unlimite

Design, Analysis and Evaluation of Unmanned Aerial Vehicle Ad hoc Network for Emergency Response Communications

In any emergency situation, it is paramount that communication be established between those affected by an emergency and the emergency responders. This communication is typically initiated by contacting an emergency service number such as 9-1-1 which will then notify the appropriate responders. The communication link relies heavily on the use of the public telephone network. If an emergency situation causes damage to, or otherwise interrupts, the public telephone network then those affected by the emergency are unable to call for help or warn others. A backup emergency response communication system is required to restore communication in areas where the public telephone network is inoperable. The use of unmanned aerial vehicles is proposed to act as mobile base stations and route wireless communication to the nearest working public telephone network access point. This thesis performs an analysis based on wireless attributes associated with communication in this type of network such as channel capacity, network density and propagation delay

A Cloud Based Disaster Management System

The combination of wireless sensor networks (WSNs) and 3D virtual environments opens a new paradigm for their use in natural disaster management applications. It is important to have a realistic virtual environment based on datasets received from WSNs to prepare a backup rescue scenario with an acceptable response time. This paper describes a complete cloud-based system that collects data from wireless sensor nodes deployed in real environments and then builds a 3D environment in near real-time to reflect the incident detected by sensors (fire, gas leaking, etc.). The system’s purpose is to be used as a training environment for a rescue team to develop various rescue plans before they are applied in real emergency situations. The proposed cloud architecture combines 3D data streaming and sensor data collection to build an efficient network infrastructure that meets the strict network latency requirements for 3D mobile disaster applications. As compared to other existing systems, the proposed system is truly complete. First, it collects data from sensor nodes and then transfers it using an enhanced Routing Protocol for Low-Power and Lossy Networks (RLP). A 3D modular visualizer with a dynamic game engine was also developed in the cloud for near-real time 3D rendering. This is an advantage for highly-complex rendering algorithms and less powerful devices. An Extensible Markup Language (XML) atomic action concept was used to inject 3D scene modifications into the game engine without stopping or restarting the engine. Finally, a multi-objective multiple traveling salesman problem (AHP-MTSP) algorithm is proposed to generate an efficient rescue plan by assigning robots and multiple unmanned aerial vehicles to disaster target locations, while minimizing a set of predefined objectives that depend on the situation. The results demonstrate that immediate feedback obtained from the reconstructed 3D environment can help to investigate what–if scenarios, allowing for the preparation of effective rescue plans with an appropriate management effort.info:eu-repo/semantics/publishedVersio