Biblio

Systems for relative localization in multi-robot systems based on ultra-wideband (UWB) ranging have recently emerged as robust solutions for GNSS-denied environments. Scalability remains one of the key challenges, particularly in adhoc deployments. Recent solutions include dynamic allocation of active and passive localization modes for different robots or nodes in the system. with larger-scale systems becoming more distributed, key research questions arise in the areas of security and trustability of such localization systems. This paper studies the potential integration of collaborative-decision making processes with distributed ledger technologies. Specifically, we investigate the design and implementation of a methodology for running an UWB role allocation algorithm within smart contracts in a blockchain. In previous works, we have separately studied the integration of ROS2 with the Hyperledger Fabric blockchain, and introduced a new algorithm for scalable UWB-based localization. In this paper, we extend these works by (i) running experiments with larger number of mobile robots switching between different spatial configurations and (ii) integrating the dynamic UWB role allocation algorithm into Fabric smart contracts for distributed decision-making in a system of multiple mobile robots. This enables us to deliver the same functionality within a secure and trustable process, with enhanced identity and data access management. Our results show the effectiveness of the UWB role allocation for continuously varying spatial formations of six autonomous mobile robots, while demonstrating a low impact on latency and computational resources of adding the blockchain layer that does not affect the localization process.

The spread of the Internet of Things (IoT) and cloud services leads to a request for secure communication between devices, known as zero-trust security. The authors have been developing CYber PHysical Overlay Network over Internet Communication (CYPHONIC) to realize secure end-to-end communication among devices. A device requires installing the client program into the devices to realize secure communication over our overlay network. However, some devices refuse additional installation of external programs due to the limitation of system and hardware resources or the effect on system reliability. We proposed new technology, a CYPHONIC adapter, to support these devices. Currently, the CYPHONIC adapter supports only IPv4 virtual addresses and needs to be compatible with general devices that use IPv6. This paper proposes the dual-stack CYPHONIC adapter supporting IPv4/IPv6 virtual addresses for general devices. The prototype implementation shows that the general device can communicate over our overlay network using both IP versions through the proposed CYPHONIC adapter.

Information security construction is a social issue, and the most urgent task is to do an excellent job in information risk assessment. The bayesian neural network currently plays a vital role in enterprise information security risk assessment, which overcomes the subjective defects of traditional assessment results and operates efficiently. The risk quantification method based on fuzzy theory and Bayesian regularization BP neural network mainly uses fuzzy theory to process the original data and uses the processed data as the input value of the neural network, which can effectively reduce the ambiguity of language description. At the same time, special neural network training is carried out for the confusion that the neural network is easy to fall into the optimal local problem. Finally, the risk is verified and quantified through experimental simulation. This paper mainly discusses the problem of enterprise information security risk assessment based on a Bayesian neural network, hoping to provide strong technical support for enterprises and organizations to carry out risk rectification plans. Therefore, the above method provides a new information security risk assessment idea.

Using multi-UAV systems to accomplish both civil and military missions is becoming a popular trend. With the development of software and hardware technologies, Unmanned aerial vehicles (UAVs) are now able to operate autonomously at edge. However, the remote control of manned systems, e.g., ground control station (GCS), remains essential to mission success, and the system's control and non-payload communication (CNPC) are facing severe cyber threats caused by smart attacks. To avoid hijacking, in this paper, we propose a secure mechanism that reduces such security risks for multi-UAV systems. We introduce friendly jamming from UAVs to block eavesdropping on the remote control channel. The trade-off between security and energy consumption is optimized by three approaches designed for UAV and GCS under algorithms of different complexities. Numerical results show the approach efficiency under different mission conditions and security demands, and demonstrate the features of the proposed mechanism for various scenarios.

The digital transformation brought on by 5G is redefining current models of end-to-end (E2E) connectivity and service reliability to include security-by-design principles necessary to enable 5G to achieve its promise. 5G trustworthiness highlights the importance of embedding security capabilities from the very beginning while the 5G architecture is being defined and standardized. Security requirements need to overlay and permeate through the different layers of 5G systems (physical, network, and application) as well as different parts of an E2E 5G architecture within a risk-management framework that takes into account the evolving security-threats landscape. 5G presents a typical use-case of wireless communication and computer networking convergence, where 5G fundamental building blocks include components such as Software Defined Networks (SDN), Network Functions Virtualization (NFV) and the edge cloud. This convergence extends many of the security challenges and opportunities applicable to SDN/NFV and cloud to 5G networks. Thus, 5G security needs to consider additional security requirements (compared to previous generations) such as SDN controller security, hypervisor security, orchestrator security, cloud security, edge security, etc. At the same time, 5G networks offer security improvement opportunities that should be considered. Here, 5G architectural flexibility, programmability and complexity can be harnessed to improve resilience and reliability. The working group scope fundamentally addresses the following: •5G security considerations need to overlay and permeate through the different layers of the 5G systems (physical, network, and application) as well as different parts of an E2E 5G architecture including a risk management framework that takes into account the evolving security threats landscape. •5G exemplifies a use-case of heterogeneous access and computer networking convergence, which extends a unique set of security challenges and opportunities (e.g., related to SDN/NFV and edge cloud, etc.) to 5G networks. Similarly, 5G networks by design offer potential security benefits and opportunities through harnessing the architecture flexibility, programmability and complexity to improve its resilience and reliability. •The IEEE FNI security WG's roadmap framework follows a taxonomic structure, differentiating the 5G functional pillars and corresponding cybersecurity risks. As part of cross collaboration, the security working group will also look into the security issues associated with other roadmap working groups within the IEEE Future Network Initiative.

The Robotic Operating System (ROS) is a popular framework for robotics research and development. It's a system that provides hardware abstraction with low-level device management to handle communications and services. ROS is a distributed system, which allows various nodes in a network to communicate using a method such as message passing. When integrating systems using ROS, it is vital to consider the security and privacy of the data and information shared across ROS nodes, which is considered to be one of the most challenging aspects of ROS systems. The goal of this study is to examine the ROS architecture, primary components, and versions, as well as the types of vulnerabilities that might compromise the system. In order to achieve the CIA's three fundamental security criteria on a ROS-based platform, we categorized these vulnerabilities and looked into various security solutions proposed by researchers. We provide a comparative analysis of the ROS-related security solutions, the security threats and issues they addressed, the targeted architecture of the protection or defense system, the solution's evaluation methodology and the evaluation metric, and the limitations that might be viewed as unresolved issues for the future course of action. Finally, we look into future possibilities and open challenges to assist researchers to develop more secure and efficient ROS systems.

ROS 2 is rapidly becoming a standard in the robotics industry. Built upon DDS as its default communication middleware and used in safety-critical scenarios, adding secu-rity to robots and ROS computational graphs is increasingly becoming a concern. The present work introduces SROS2, a series of developer tools and libraries that facilitate adding security to ROS 2 graphs. Focusing on a usability-centric approach in SROS2, we present a methodology for securing graphs systematically while following the DevSecOps model. We also demonstrate the use of our security tools by presenting an application case study that considers securing a graph using the popular Navigation2 and SLAM Toolbox stacks applied in a TurtieBot3 robot. We analyse the current capabilities of SROS2 and discuss the shortcomings, which provides insights for future contributions and extensions. Ultimately, we present SROS2 as usable security tools for ROS 2 and argue that without usability, security in robotics will be greatly impaired.

The Domain Name System (DNS) is critical to Internet communications. EDNS Client Subnet (ECS), a DNS extension, allows recursive resolvers to include client subnet information in DNS queries to improve CDN end-user mapping, extending the visibility of client information to a broader range. Major content delivery network (CDN) vendors, content providers (CP), and public DNS service providers (PDNS) are accelerating their IPv6 infrastructure development. With the increasing deployment of IPv6-enabled services and DNS being the most foundational system of the Internet, it becomes important to analyze the behavioral and privacy status of IPv6 resolvers. However, there is a lack of research on ECS for IPv6 DNS resolvers.In this paper, we study the ECS deployment and compliance status of IPv6 resolvers. Our measurement shows that 11.12% IPv6 open resolvers implement ECS. We discuss abnormal noncompliant scenarios that exist in both IPv6 and IPv4 that raise privacy and performance issues. Additionally, we measured if the sacrifice of clients’ privacy can enhance IPv6 CDN performance. We find that in some cases ECS helps end-user mapping but with an unnecessary privacy loss. And even worse, the exposure of client address information can sometimes backfire, which deserves attention from both Internet users and PDNSes.

Using the methods of literature and interview, this paper analyzes the current situation of performance evaluation of volunteers in large-scale games based on mobile Internet, By analyzing the popularity of mobile Internet, the convenience of performance evaluation, the security and privacy of performance evaluation, this paper demonstrates the necessity of performance evaluation of volunteers in large-scale games based on mobile Internet, This paper puts forward the Countermeasures of performance evaluation of volunteers in large-scale games based on mobile Internet.

The concept of a microgrid has emerged as a promising solution for the management of local groups of electricity consumers and producers. The use of end-users' energy usage data can help in increasing efficient operation of a microgrid. However, existing data-aggregation schemes for a microgrid suffer different cyber attacks and do not provide high level of accuracy. This work aims at designing a privacy-preserving data-aggregation scheme for a microgrid of prosumers that achieves high level of accuracy, thereby benefiting to the management and control of a microgrid. First, a novel smart meter readings data protection mechanism is proposed to ensure privacy of prosumers by hiding the real energy usage data from other parties. Secondly, a blockchain-based data-aggregation scheme is proposed to ensure privacy of the end-users, while achieving high level of accuracy in terms of the aggregated data. The proposed data-aggregation scheme is evaluated using real smart meter readings data from 100 prosumers. The results show that the proposed scheme ensures prosumers' privacy and achieves high level of accuracy, while it is secure against eavesdropping and man-in-the-middle cyber attacks.

This paper builds an Augmented Reality Sandbox (AR Sandbox) system based on augmented reality technology, and performs a 3D reconstruction for the sandbox terrain using the depth sensor Microsoft Kinect in the AR Sandbox, as an entry point to pave the way for later development of related metaverse applications, such as the metaverse architecting and visual interactive modeling. The innovation of this paper is that for the AR Sandbox scene, a 3D reconstruction method based on depth sensor is proposed, which can automatically cut off the edge of the sandbox table in Kinect field of view, and accurately and completely reconstruct the sandbox terrain in Matlab.

To ensure comprehensive information protection, it is necessary to use various means of information protection, distributed by levels and segments of the information system. This creates a contradiction, which consists in the presence of many different means of information protection and the inability to ensure their joint coordinated application in ensuring the protection of information due to the lack of an automated control system. One of the tasks that contribute to the solution of this problem is the task of generating a feasible organizational structure and the structure of such an automated control system, the results of which would provide these options and choose the one that is optimal under given initial parameters and limitations. The problem is solved by reducing the General task with particular splitting the original graph of the automated cyber defense control system into subgraphs. As a result, the organizational composition and the automated cyber defense management system structures will provide a set of acceptable variants, on the basis of which the optimal choice is made under the given initial parameters and restrictions. As a result, admissible variants for the formation technique of organizational structure and structure by the automated control system of cyber defense is received.

Middleware for IoT (Internet of Things) helps application developers face challenges, such as device heterogeneity, service interoperability, security and scalability. While extensively adopted nowadays, IoT middleware systems are static because, after deployment, updates are only possible by stopping the thing. Therefore, adaptive capabilities can improve existing solutions by allowing their dynamic adaptation to changes in the environmental conditions, evolve provided functionalities, or fix bugs. This paper presents AMoT, an adaptive publish/subscribe middleware for IoT whose design and implementation adopt software architecture principles and evolutive adaptation mechanisms. The experimental evaluation of AMoT helps to measure the impact of the proposed adaptation mechanisms while also comparing the performance of AMoT with a widely adopted MQTT (Message Queuing Telemetry Transport) based middleware. In the end, adaptation has an acceptable performance cost and the advantage of tunning the middleware functionality at runtime.

Information-Centric Networking (ICN) is among the promising architecture that can drive the need and versatility towards the future generation (xG) needs. In the future, support for network communication relies on the area of telemedicine, autonomous vehicles, and disaster recovery. In the disaster recovery case, there is a high possibility where the communication path is severed. Multicast communication and DTN-friendly route algorithm are becoming suitable options to send a packet message to get a faster response and to see any of the nodes available for service, this approach could give burden to the core network. Also, during disaster cases, many people would like to communicate, receive help, and find family members. Flooding the already disturbed/severed network will further reduce communication performance efficiency even further. Thus, this study takes into consideration prioritization factors to allow networks to process and delivering priority content. For this purpose, the proposed technique introduces the Routable Prefix Identifier (RP-ID) that takes into account the prioritization factor to enable optimization in Delay Tolerant ICN communication.

The Open Data Cube (ODC), created and facilitated by the Committee on Earth Observation Satellites (CEOS), is an open source software architecture that continues to gain global popularity through the integration of analysis-ready data (ARD) on cloud computing frameworks. In 2021, CEOS released a new ODC sandbox that provides global users with a free and open programming interface connected to Google Earth Engine datasets. The open source toolset allows users to run application algorithms using a Google Colab Python notebook environment. This tool demonstrates rapid creation of science products anywhere in the world without the need to download and process the satellite data. Basic operation of the tool will support many users but can also be scaled in size and scope to support enhanced user needs. The creation of the ODC sandbox was prompted by the migration of many CEOS ARD satellite datasets to the cloud. The combination of these datasets in an interoperable data cube framework will inspire the creation of many new application products and advance open science.

Multi-Agent system has the advantages of information sharing, knowledge accumulation and system stability, which is consistent with the concept of collaborative co-governance of public crisis management, and provides support for dealing with sudden public crises. Based on the background of the all-media environment, this study introduces the Internet-driven mass data management (“ crowdsourcing” crisis management) as a part of the crisis response system to improve the quality of information resource sharing. Crowdsourcing crisis management and Multi-Agent collaborative co-governance mechanism are combined with each other, so as to achieve a higher level of joint prevention and control mechanism, and explore how to effectively share information resources and emergency management resources across regions and departments in public crisis events.

While various encryption algorithms ensure data security, it is essential to determine the accuracy and loss values and performance status in the analyzes made to determine encrypted data by deep learning. In this research, the analysis steps made by applying deep learning methods to encrypted cifar10 picture data are presented practically. The data was tried to be estimated by training with VGG16, VGG19, ResNet50 deep learning models. During this period, the network’s performance was tried to be measured, and the accuracy and loss values in these calculations were shown graphically.

This article is devoted to the existing standards for assessing the state of information security, which provides a classification and comparative analysis of standards for assessing the state of information.

The article describes an analytical model of the actions of an information security violator for the secret extraction of confidential information processed on the protected object in terms of the theory of Markov random processes. The characteristics of the existing models are given, as well as the requirements that are imposed on the model for simulating the process. All model states are described in detail, as well as the data flow that is used in the process simulation. The model is represented as a directed state graph. It also describes the option for evaluating the data obtained during modeling. In the modern world, with the developing methods and means of covert extraction of information, the problem of assessing the damage that can be caused by the theft of the organization's data is acute. This model can be used to build a model of information security threats.

Currently, statistical tests for random number generators (RNGs) are widely used in practice, and some of them are even included in information security standards. But despite the popularity of RNGs, consistent tests are known only for stationary ergodic deviations of randomness (a test is consistent if it detects any deviations from a given class when the sample size goes to infinity). However, the model of a stationary ergodic source is too narrow for some RNGs, in particular, for generators based on physical effects. In this article, we propose computable consistent tests for some classes of deviations more general than stationary ergodic and describe some general properties of statistical tests. The proposed approach and the resulting test are based on the ideas and methods of information theory.

The current supply of a highly specialized cyber security professionals cannot meet the demands for societies seeking digitization. To close the skill gap, there is a need for introducing students in higher education to cyber security, and to combine theoretical knowledge with practical skills. This paper presents how the cyber security training platform Haaukins, initially developed to increase interest and knowledge of cyber security among high school students, was further developed to support the need for training in higher education. Based on the differences between the existing and new target audiences, a set of design principles were derived which shaped the technical adjustments required to provide a suitable platform - mainly related to dynamic tooling, centralized access to exercises, and scalability of the platform to support courses running over longer periods of time. The implementation of these adjustments has led to a series of teaching sessions in various institutions of higher education, demonstrating the viability for Haaukins for the new target audience.

The COVID-19 pandemic introduced novel incentives for adversaries to exploit the state of turmoil. As we have witnessed with the increase in for instance phishing attacks and domain name registrations piggybacking the COVID-19 brand name. In this paper, we perform an analysis at Internet-scale of COVID-19 domain name registrations during the early stages of the virus' spread, and investigate the rationales behind them. We leverage the DomainTools COVID-19 Threat List and additional measurements to analyze over 150,000 domains registered between January 1st 2020 and May 1st 2020. We identify two key rationales for covid-related domain registrations. Online marketing, by either redirecting traffic or hosting a commercial service on the domain, and domain parking, by registering domains containing popular COVID-19 keywords, presumably anticipating a profit when reselling the domain later on. We also highlight three public policy take-aways that can counteract this domain registration behavior.

Analyzing safety and security requirements remains a difficult task in the development of real-life network protocols. Although numerous modeling and analyzing methods have been proposed in the past decades, most of them handle safety and security requirements separately without considering their interplay. In this work, we propose a collaborative modeling framework that enables co-analysis of safety and security requirements for network protocols. Our modeling framework is based on a well-defined type system and supports modeling of network topology, message flows, protocol behaviors and attacker behaviors. It also supports the specification of safety requirements as temporal logical formulae and typical security requirements as queries, and leverages on the existing verification tools for formal safety and security analysis via model transformations. We have implemented this framework in a prototype tool CMSS, and illustrated the capability of CMSS by using the 5G AKA initialization protocol as a case study.

In the era of big data and artificial intelligence, computer networks have become an important infrastructure, and the Internet has become ubiquitous. The most basic property of computer networks is reachability. The needs of the modern Internet mainly include cost, performance, reliability, and security. However, even for experienced network engineers, it is very difficult to manually conFigure the network to meet the needs of the modern large-scale Internet. The engineers often make mistakes, which can cause network paralysis, resulting in incalculable losses. Due to the development of automatic reasoning technology, automatic verification of network configuration is used to avoid mistakes. Network verification is at least an NP-C problem, so it is necessary to compress the network to reduce the network scale, thereby reducing the network verification time. This paper proposes a new model of network modeling, which is more suitable for the verification of network configuration on common protocols (such as RIP, BGP). On the basis of the existing compression method, two compression rules are added to compress the modeled network, reducing network verification time and conducting network reachability verification experiments on common networks. The experimental results are slightly better than the current compression methods.

Game theory is a branch of modern mathematics, which is a mathematical method to study how decision-makers should make decisions in order to strive for the maximum interests in the process of competition. In this paper, from the perspective of offensive and defensive confrontation, using game theory for reference, we build a dynamic evaluation model of information system security risk based on static game model. By using heisani transformation, the uncertainty of strategic risk of offensive and defensive sides is transformed into the uncertainty of each other's type. The security risk of pure defense strategy and mixed defense strategy is analyzed quantitatively, On this basis, an information security risk assessment algorithm based on static game model is designed.