503 research outputs found
Misbehavior aware on-demand intrusion detection system to enhance security in VANETs with efficient rogue nodes detection and prevention techniques
Vehicular ad-hoc networks (VANETs) facilitate vehicles to broadcast beacon messages to ensure road safety. The goal behind sharing the information through beacon messages is to disseminate network state or emergency information. The exchange of information is susceptible to security attacks of different kinds. Amongst various problems to be solved in VANETs is the issue of rogue nodes and their impact on the network. Rogue nodes are malicious vehicles that are vicious to cause severe damage to the network by modifying or altering false data in beacon messages that could lead to catastrophic consequences like trapping a group of vehicles, road accidents, vehicle collisions, etc. This thesis discusses the problems associated with the security VANETs in the presence of rogue nodes.
We proposed three novel intrusion detection frameworks to detect the rogue nodes responsible for false information, Sybil, and platoon control maneuver attacks only by analyzing and comparing the beacon messages broadcast over the network. The novelty of our frameworks lies in containing network damage and securing VANETs from the harmful impact of rogue nodes. The proposed frameworks are simulated using SUMO, OMNET++, and VENTOS, and the results obtained have been presented, discussed, and compared to existing frameworks. Results show that the developed methods improve the systems’ performance compared to existing methods even when the number of rogue nodes increases in the region
Performance Analysis Of Data-Driven Algorithms In Detecting Intrusions On Smart Grid
The traditional power grid is no longer a practical solution for power delivery due to several shortcomings, including chronic blackouts, energy storage issues, high cost of assets, and high carbon emissions. Therefore, there is a serious need for better, cheaper, and cleaner power grid technology that addresses the limitations of traditional power grids. A smart grid is a holistic solution to these issues that consists of a variety of operations and energy measures. This technology can deliver energy to end-users through a two-way flow of communication. It is expected to generate reliable, efficient, and clean power by integrating multiple technologies. It promises reliability, improved functionality, and economical means of power transmission and distribution. This technology also decreases greenhouse emissions by transferring clean, affordable, and efficient energy to users. Smart grid provides several benefits, such as increasing grid resilience, self-healing, and improving system performance. Despite these benefits, this network has been the target of a number of cyber-attacks that violate the availability, integrity, confidentiality, and accountability of the network. For instance, in 2021, a cyber-attack targeted a U.S. power system that shut down the power grid, leaving approximately 100,000 people without power. Another threat on U.S. Smart Grids happened in March 2018 which targeted multiple nuclear power plants and water equipment. These instances represent the obvious reasons why a high level of security approaches is needed in Smart Grids to detect and mitigate sophisticated cyber-attacks. For this purpose, the US National Electric Sector Cybersecurity Organization and the Department of Energy have joined their efforts with other federal agencies, including the Cybersecurity for Energy Delivery Systems and the Federal Energy Regulatory Commission, to investigate the security risks of smart grid networks. Their investigation shows that smart grid requires reliable solutions to defend and prevent cyber-attacks and vulnerability issues. This investigation also shows that with the emerging technologies, including 5G and 6G, smart grid may become more vulnerable to multistage cyber-attacks. A number of studies have been done to identify, detect, and investigate the vulnerabilities of smart grid networks. However, the existing techniques have fundamental limitations, such as low detection rates, high rates of false positives, high rates of misdetection, data poisoning, data quality and processing, lack of scalability, and issues regarding handling huge volumes of data. Therefore, these techniques cannot ensure safe, efficient, and dependable communication for smart grid networks. Therefore, the goal of this dissertation is to investigate the efficiency of machine learning in detecting cyber-attacks on smart grids. The proposed methods are based on supervised, unsupervised machine and deep learning, reinforcement learning, and online learning models. These models have to be trained, tested, and validated, using a reliable dataset. In this dissertation, CICDDoS 2019 was used to train, test, and validate the efficiency of the proposed models. The results show that, for supervised machine learning models, the ensemble models outperform other traditional models. Among the deep learning models, densely neural network family provides satisfactory results for detecting and classifying intrusions on smart grid. Among unsupervised models, variational auto-encoder, provides the highest performance compared to the other unsupervised models. In reinforcement learning, the proposed Capsule Q-learning provides higher detection and lower misdetection rates, compared to the other model in literature. In online learning, the Online Sequential Euclidean Distance Routing Capsule Network model provides significantly better results in detecting intrusion attacks on smart grid, compared to the other deep online models
Service Provisioning in Edge-Cloud Continuum Emerging Applications for Mobile Devices
Disruptive applications for mobile devices can be enhanced by Edge computing facilities. In this context, Edge Computing (EC) is a proposed architecture to meet the mobility requirements imposed by these applications in a wide range of domains, such as the Internet of Things, Immersive Media, and Connected and Autonomous Vehicles. EC architecture aims to introduce computing capabilities in the path between the user and the Cloud to execute tasks closer to where they are consumed, thus mitigating issues related to latency, context awareness, and mobility support. In this survey, we describe which are the leading technologies to support the deployment of EC infrastructure. Thereafter, we discuss the applications that can take advantage of EC and how they were proposed in the literature. Finally, after examining enabling technologies and related applications, we identify some open challenges to fully achieve the potential of EC, and also research opportunities on upcoming paradigms for service provisioning. This survey is a guide to comprehend the recent advances on the provisioning of mobile applications, as well as foresee the expected next stages of evolution for these applications
Towards Reliable Multi-Path Routing : An Integrated Cooperation Model for Drones
Ad-hoc networks have evolved into a vital wireless communication component by offering an adaptable infrastructure suitable for various scenarios in our increasingly interconnected and mobile world. However, this adaptability also exposes these networks to security challenges, given their dynamic nature, where nodes frequently join and leave. This dynamism is advantageous but presents resource constraints and vulnerability to malicious nodes, impacting data transmission reliability and security.
In this context, this article explores the development of a secure routing protocol for Ad-hoc networks based on a cooperation reinforcement model to reduce the degradation of routing performance. We leverage the reputation of nodes as an additional security layer to monitor their behavior and evaluate their level of reliability. To exemplify our solution, we focus on drone fleets (UAVs) as a pertinent case study. Drones frequently operate in dynamic, challenging environments, relying on Ad-hoc networks for communication. They serve as an apt illustration, highlighting the complexities of the issue and the efficacy of our proposed remedy. The simulation results show the effectiveness of our proposed solution compared to stae-of-the-artsolutions
Applications
Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications
Scalable Schedule-Aware Bundle Routing
This thesis introduces approaches providing scalable delay-/disruption-tolerant routing capabilities in scheduled space topologies. The solution is developed for the requirements derived from use cases built according to predictions for future space topology, like the future Mars communications architecture report from the interagency operations advisory group. A novel routing algorithm is depicted to provide optimized networking performance that discards the scalability issues inherent to state-of-the-art approaches. This thesis also proposes a new recommendation to render volume management concerns generic and easily exchangeable, including a new simple management technique increasing volume awareness accuracy while being adaptable to more particular use cases. Additionally, this thesis introduces a more robust and scalable approach for internetworking between subnetworks to increase the throughput, reduce delays, and ease configuration thanks to its high flexibility.:1 Introduction
1.1 Motivation
1.2 Problem statement
1.3 Objectives
1.4 Outline
2 Requirements
2.1 Use cases
2.2 Requirements
2.2.1 Requirement analysis
2.2.2 Requirements relative to the routing algorithm
2.2.3 Requirements relative to the volume management
2.2.4 Requirements relative to interregional routing
3 Fundamentals
3.1 Delay-/disruption-tolerant networking
3.1.1 Architecture
3.1.2 Opportunistic and deterministic DTNs
3.1.3 DTN routing
3.1.4 Contact plans
3.1.5 Volume management
3.1.6 Regions
3.2 Contact graph routing
3.2.1 A non-replication routing scheme
3.2.2 Route construction
3.2.3 Route selection
3.2.4 Enhancements and main features
3.3 Graph theory and DTN routing
3.3.1 Mapping with DTN objects
3.3.2 Shortest path algorithm
3.3.3 Edge and vertex contraction
3.4 Algorithmic determinism and predictability
4 Preliminary analysis
4.1 Node and contact graphs
4.2 Scenario
4.3 Route construction in ION-CGR
4.4 Alternative route search
4.4.1 Yen’s algorithm scalability
4.4.2 Blocking issues with Yen
4.4.3 Limiting contact approaches
4.5 CGR-multicast and shortest-path tree search
4.6 Volume management
4.6.1 Volume obstruction
4.6.2 Contact sink
4.6.3 Ghost queue
4.6.4 Data rate variations
4.7 Hierarchical interregional routing
4.8 Other potential issues
5 State-of-the-art and related work
5.1 Taxonomy
5.2 Opportunistic and probabilistic approaches
5.2.1 Flooding approaches
5.2.2 PROPHET
5.2.3 MaxProp
5.2.4 Issues
5.3 Deterministic approaches
5.3.1 Movement-aware routing over interplanetary networks
5.3.2 Delay-tolerant link state routing
5.3.3 DTN routing for quasi-deterministic networks
5.3.4 Issues
5.4 CGR variants and enhancements
5.4.1 CGR alternative routing table computation
5.4.2 CGR-multicast
5.4.3 CGR extensions
5.4.4 RUCoP and CGR-hop
5.4.5 Issues
5.5 Interregional routing
5.5.1 Border gateway protocol
5.5.2 Hierarchical interregional routing
5.5.3 Issues
5.6 Further approaches
5.6.1 Machine learning approaches
5.6.2 Tropical geometry
6 Scalable schedule-aware bundle routing
6.1 Overview
6.2 Shortest-path tree routing for space networks
6.2.1 Structure
6.2.2 Tree construction
6.2.3 Tree management
6.2.4 Tree caching
6.3 Contact segmentation
6.3.1 Volume management interface
6.3.2 Simple volume manager
6.3.3 Enhanced volume manager
6.4 Contact passageways
6.4.1 Regional border definition
6.4.2 Virtual nodes
6.4.3 Pathfinding and administration
7 Evaluation
7.1 Methodology
7.1.1 Simulation tools
7.1.2 Simulator extensions
7.1.3 Algorithms and scenarios
7.2 Offline analysis
7.3 Eliminatory processing pressures
7.4 Networking performance
7.4.1 Intraregional unicast routing tests
7.4.2 Intraregional multicast tests
7.4.3 Interregional routing tests
7.4.4 Behavior with congestion
7.5 Requirement fulfillment
8 Summary and Outlook
8.1 Conclusion
8.2 Future works
8.2.1 Next development steps
8.2.2 Contact graph routin
Codificación adaptativa de red para sistemas inalámbricos IEEE 802.11s en modo infraestructura
Las redes inalámbricas malladas IEEE 802.11s en modo infraestructura, denominadas comúnmente como iWMNs (Infrastructure Wireless Mesh Networks), están constituidas por nodos inalámbricos estáticos capaces de trabajar coordinadamente para encaminar paquetes de datos. De esta manera, los nodos colaboran para poder intercambiar información entre sí. Más aún, las iWMNs pueden ser interconectadas con otras tecnologías de red y, de este modo, coadyuvar a extender inalámbricamente la cobertura de estas redes; por ejemplo, las iWMNs se emplean hoy en día para extender la cobertura de redes celulares o de redes cableadas. Gracias a estas características, y también a su bajo costo de infraestructura, las redes iWMNs son consideradas hoy en día como una excelente opción para ofrecer servicios de conectividad inalámbrica a Internet en zonas geográficas donde el uso de otras tecnologías resulta inviable. A pesar de las prometedoras características de las iWMNs; existen estudios y resultados que plantean dudas sobre su desempeño, ya que se ha documentado que el rendimiento de estas redes puede ser afectado por numerosos factores; tales como el uso de TCP para transportar información en entornos inalámbricos, la tasa de errores en el medio inalámbrico, así como la contienda por el acceso al medio entre usuarios de la red. Todos estos factores pueden degradar las prestaciones de las iWMNs y, consecuentemente, afectar la calidad de la experiencia que reciben los usuarios. En esta tesis doctoral se atienden algunos de estos problemas de desempeño mediante la técnica denominada como codificación adaptativa de red. Esta técnica ayuda a que los nodos de una iWMN puedan combinar varios paquetes de datos y de este modo construir un paquete codificado; al transmitir este paquete se transporta la información contenida en los paquetes originales requiriendo únicamente una transmisión inalámbrica, reduciendo de esta manera el uso del medio inalámbrico y, con ello, se incrementa la capacidad de la red. La técnica propuesta, además, busca que el proceso de codificación se adapte a las condiciones de tráfico en la red a través del ajuste dinámico del tiempo de espera de los paquetes en un nodo antes de poder ser combinados; es así como se puede disminuir el retardo de codificación. Con esta propuesta se pretende mejorar sustancialmente el desempeño de las iWMNs, resolviendo algunos problemas que las afectan. La evaluación de la propuesta se realiza empleando simulaciones y evaluaciones numéricas. A través de un minucioso análisis de resultados encontramos que las iWMNs pueden mejorar su rendimiento al emplear la técnica de codificación adaptativa de red, ya que se reduce considerablemente el número de transmisiones inalámbricas en la red, y, por consiguiente: i) se disminuye la contienda por el medio, ii) se reducen las probabilidades de error en el medio y iii) se incrementa la capacidad de la red.IEEE 802.11s INFRASTRUCTURE WIRELESS MESH NETWORKS (commonly known as iWMNs) are integrated by static wireless nodes capable of working in coordination to route data packets. In this way, the nodes collaborate to exchange information with each other. In addition, iWMNs can be interconnected with other network technologies and, in this way, help to wirelessly extend the coverage of these networks; for example, iWMNs are used today to extend the coverage of cellular or wired networks. Thanks to this feature, and also to their low infrastructure cost, iWMNs networks are considered today as an excellent option to offer wireless Internet connectivity services in geographical areas where the use of other network technologies is unfeasible. Despite the promising features of iWMNs, there are studies and results that cast doubt on their performance, since it has been documented that the performance of these networks can be affected by numerous factors; such as the use of TCP to transport information in wireless environments, the transmission errors in the wireless medium, as well as the access contention between network users. All these factors can degrade the performance of iWMNs and, consequently, affect the quality of the experience for the users. In this doctoral thesis, some of these performance problems are addressed through the technique called adaptive network coding. With this technique, the nodes of an iWMN are allowed to combine various data packets and thus build an encoded packet; this packet contains the information from the original packets, requiring only one wireless transmission to transport the original information, reducing the use of the wireless medium and, thereby, increasing the capacity of the network. The proposed technique also seeks to adapt the coding process to the traffic conditions in the network through the dynamic adjustment of the waiting time of the packets in a node before they can be combined. This proposal aims to substantially improve the performance of iWMNs, solving some problems that affect them. The evaluation of the proposal is carried out through simulations and numerical evaluations. After a detailed analysis of the results, we find that iWMNs can improve their performance by using the adaptive network coding technique, since the number of wireless transmissions in the network is considerably reduced, and, consequently, i) the medium access contention decreases, ii) the probability of errors in the medium is reduced, and iii) the capacity of the network increase
Trustworthiness Mechanisms for Long-Distance Networks in Internet of Things
Aquesta tesi té com a objectiu aconseguir un intercanvi de dades fiable en un entorn hostil millorant-ne la confiabilitat mitjançant el disseny d'un model complet que tingui en compte les diferents capes de confiabilitat i mitjançant la implementació de les contramesures associades al model. La tesi se centra en el cas d'ús del projecte SHETLAND-NET, amb l'objectiu de desplegar una arquitectura d'Internet de les coses (IoT) híbrida amb comunicacions LoRa i d'ona ionosfèrica d'incidència gairebé vertical (NVIS) per oferir un servei de telemetria per al monitoratge del “permafrost” a l'Antàrtida.
Per complir els objectius de la tesi, en primer lloc, es fa una revisió de l'estat de l'art en confiabilitat per proposar una definició i l'abast del terme de confiança. Partint d'aquí, es dissenya un model de confiabilitat de quatre capes, on cada capa es caracteritza pel seu abast, mètrica per a la quantificació de la confiabilitat, contramesures per a la millora de la confiabilitat i les interdependències amb les altres capes. Aquest model permet el mesurament i l'avaluació de la confiabilitat del cas d'ús a l'Antàrtida.
Donades les condicions hostils i les limitacions de la tecnologia utilitzada en aquest cas d’ús, es valida el model i s’avalua el servei de telemetria a través de simulacions en Riverbed Modeler. Per obtenir valors anticipats de la confiabilitat esperada, l'arquitectura proposada es modela per avaluar els resultats amb diferents configuracions previ al seu desplegament en proves de camp. L'arquitectura proposada passa per tres principals iteracions de millora de la confiabilitat. A la primera iteració, s'explora l'ús de mecanismes de consens i gestió de la confiança social per aprofitar la redundància de sensors. En la segona iteració, s’avalua l’ús de protocols de transport moderns per al cas d’ús antàrtic. L’última iteració d’aquesta tesi avalua l’ús d’una arquitectura de xarxa tolerant al retard (DTN) utilitzant el Bundle Protocol (BP) per millorar la confiabilitat del sistema.
Finalment, es presenta una prova de concepte (PoC) amb maquinari real que es va desplegar a la campanya antàrtica 2021-2022, descrivint les proves de camp funcionals realitzades a l'Antàrtida i Catalunya.Esta tesis tiene como objetivo lograr un intercambio de datos confiable en un entorno hostil mejorando su confiabilidad mediante el diseño de un modelo completo que tenga en cuenta las diferentes capas de confiabilidad y mediante la implementación de las contramedidas asociadas al modelo. La tesis se centra en el caso de uso del proyecto SHETLAND-NET, con el objetivo de desplegar una arquitectura de Internet de las cosas (IoT) híbrida con comunicaciones LoRa y de onda ionosférica de incidencia casi vertical (NVIS) para ofrecer un servicio de telemetría para el monitoreo del “permafrost” en la Antártida.
Para cumplir con los objetivos de la tesis, en primer lugar, se realiza una revisión del estado del arte en confiabilidad para proponer una definición y alcance del término confiabilidad. Partiendo de aquí, se diseña un modelo de confiabilidad de cuatro capas, donde cada capa se caracteriza por su alcance, métrica para la cuantificación de la confiabilidad, contramedidas para la mejora de la confiabilidad y las interdependencias con las otras capas. Este modelo permite la medición y evaluación de la confiabilidad del caso de uso en la Antártida.
Dadas las condiciones hostiles y las limitaciones de la tecnología utilizada en este caso de uso, se valida el modelo y se evalúa el servicio de telemetría a través de simulaciones en Riverbed Modeler. Para obtener valores anticipados de la confiabilidad esperada, la arquitectura propuesta es modelada para evaluar los resultados con diferentes configuraciones previo a su despliegue en pruebas de campo. La arquitectura propuesta pasa por tres iteraciones principales de mejora de la confiabilidad. En la primera iteración, se explora el uso de mecanismos de consenso y gestión de la confianza social para aprovechar la redundancia de sensores. En la segunda iteración, se evalúa el uso de protocolos de transporte modernos para el caso de uso antártico. La última iteración de esta tesis evalúa el uso de una arquitectura de red tolerante al retardo (DTN) utilizando el Bundle Protocol (BP) para mejorar la confiabilidad del sistema.
Finalmente, se presenta una prueba de concepto (PoC) con hardware real que se desplegó en la campaña antártica 2021-2022, describiendo las pruebas de campo funcionales realizadas en la Antártida y Cataluña.This thesis aims at achieving reliable data exchange over a harsh environment by improving its trustworthiness through the design of a complete model that takes into account the different layers of trustworthiness and through the implementation of the model’s associated countermeasures. The thesis focuses on the use case of the SHETLAND-NET project, aiming to deploy a hybrid Internet of Things (IoT) architecture with LoRa and Near Vertical Incidence Skywave (NVIS) communications to offer a telemetry service for permafrost monitoring in Antarctica.
To accomplish the thesis objectives, first, a review of the state of the art in trustworthiness is carried out to propose a definition and scope of the trustworthiness term. From these, a four-layer trustworthiness model is designed, with each layer characterized by its scope, metric for trustworthiness accountability, countermeasures for trustworthiness improvement, and the interdependencies with the other layers. This model enables trustworthiness accountability and assessment of the Antarctic use case.
Given the harsh conditions and the limitations of the use technology in this use case, the model is validated and the telemetry service is evaluated through simulations in Riverbed Modeler. To obtain anticipated values of the expected trustworthiness, the proposal has been modeled to evaluate the performance with different configurations prior to its deployment in the field. The proposed architecture goes through three major iterations of trustworthiness improvement. In the first iteration, using social trust management and consensus mechanisms is explored to take advantage of sensor redundancy. In the second iteration, the use of modern transport protocols is evaluated for the Antarctic use case. The final iteration of this thesis assesses using a Delay Tolerant Network (DTN) architecture using the Bundle Protocol (BP) to improve the system’s trustworthiness.
Finally, a Proof of Concept (PoC) with real hardware that was deployed in the 2021-2022 Antarctic campaign is presented, describing the functional tests performed in Antarctica and Catalonia
A Survey of Security in UAVs and FANETs: Issues, Threats, Analysis of Attacks, and Solutions
Thanks to the rapidly developing technology, unmanned aerial vehicles (UAVs)
are able to complete a number of tasks in cooperation with each other without
need for human intervention. In recent years, UAVs, which are widely utilized
in military missions, have begun to be deployed in civilian applications and
mostly for commercial purposes. With their growing numbers and range of
applications, UAVs are becoming more and more popular; on the other hand, they
are also the target of various threats which can exploit various
vulnerabilities of UAV systems in order to cause destructive effects. It is
therefore critical that security is ensured for UAVs and the networks that
provide communication between UAVs. In this survey, we aimed to present a
comprehensive detailed approach to security by classifying possible attacks
against UAVs and flying ad hoc networks (FANETs). We classified the security
threats into four major categories that make up the basic structure of UAVs;
hardware attacks, software attacks, sensor attacks, and communication attacks.
In addition, countermeasures against these attacks are presented in separate
groups as prevention and detection. In particular, we focus on the security of
FANETs, which face significant security challenges due to their characteristics
and are also vulnerable to insider attacks. Therefore, this survey presents a
review of the security fundamentals for FANETs, and also four different routing
attacks against FANETs are simulated with realistic parameters and then
analyzed. Finally, limitations and open issues are also discussed to direct
future wor
Navigating the IoT landscape: Unraveling forensics, security issues, applications, research challenges, and future
Given the exponential expansion of the internet, the possibilities of
security attacks and cybercrimes have increased accordingly. However, poorly
implemented security mechanisms in the Internet of Things (IoT) devices make
them susceptible to cyberattacks, which can directly affect users. IoT
forensics is thus needed for investigating and mitigating such attacks. While
many works have examined IoT applications and challenges, only a few have
focused on both the forensic and security issues in IoT. Therefore, this paper
reviews forensic and security issues associated with IoT in different fields.
Future prospects and challenges in IoT research and development are also
highlighted. As demonstrated in the literature, most IoT devices are vulnerable
to attacks due to a lack of standardized security measures. Unauthorized users
could get access, compromise data, and even benefit from control of critical
infrastructure. To fulfil the security-conscious needs of consumers, IoT can be
used to develop a smart home system by designing a FLIP-based system that is
highly scalable and adaptable. Utilizing a blockchain-based authentication
mechanism with a multi-chain structure can provide additional security
protection between different trust domains. Deep learning can be utilized to
develop a network forensics framework with a high-performing system for
detecting and tracking cyberattack incidents. Moreover, researchers should
consider limiting the amount of data created and delivered when using big data
to develop IoT-based smart systems. The findings of this review will stimulate
academics to seek potential solutions for the identified issues, thereby
advancing the IoT field.Comment: 77 pages, 5 figures, 5 table
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