A Novel Method For Detecting Faulty Nodes In Tolerant Network

Recently proposed arrangements experience the ill effects of long delays in distinguishing and isolating hubs making defective data. This is inadmissible to DTNs where nodes meet only now and then. This proposes a completely gave and fundamentally implementable way to deal with empower each DTN node to quickly perceive whether its sensors are passing on defective information. The dynamical way of the proposed calculation is approximated by some steady time state conditions, whose equality is projected. The closeness of getting away hand hubs, trying to inconvenience the blemished hub affirmation process, is moreover considered

A new analysis of distributed faulty node detection in DTNS

Previously proposed solutions suffer from long delays in identifying and dividing nodes producing faulty data. This is unsuitable to DTNs where nodes meet only rarely. This proposes a completely conveyed and essentially implementable way to deal with enable each DTN node to quickly distinguish whether its sensors are delivering flawed information. The dynamical conduct of the proposed algorithm is approximated by some persistent time state conditions, whose balance is portrayed. The nearness of getting out of hand nodes, attempting to bother the faulty node recognition process, is additionally considered

Parameter estimation in wireless sensor networks with faulty transducers: a distributed EM approach

We address the problem of distributed estimation of a vector-valued parameter performed by a wireless sensor network in the presence of noisy observations which may be unreliable due to faulty transducers. The proposed distributed estimator is based on the Expectation-Maximization (EM) algorithm and combines consensus and diffusion techniques: a term for information diffusion is gradually turned off, while a term for updated information averaging is turned on so that all nodes in the network approach the same value of the estimate. The proposed method requires only local exchanges of information among network nodes and, in contrast with previous approaches, it does not assume knowledge of the a priori probability of transducer failures or the noise variance. A convergence analysis is provided, showing that the convergent points of the centralized EM iteration are locally asymptotically convergent points of the proposed distributed scheme. Numerical examples show that the distributed algorithm asymptotically attains the performance of the centralized EM method.Peer ReviewedPreprin

Defective Sensor Identification for WSNs Involving Generic Local Outlier Detection Tests

The behavior of a wireless sensor network dedicated to distributed estimation tasks may be significantly altered by the presence of nodes whose sensors are defective and produce erroneous measurements. This paper proposes and analyzes the performance of two distributed algorithms to help each node in determining whether it is equipped with a defective sensor. A node first collects data from its neighborhood, processes them to decide, using some generic local outlier detection test, whether these data contain outliers and broadcasts the result. Then, it determines the status of its own sensor using its result and those received from neighboring nodes. A single-decision and an iterative algorithm for defective sensor detection are proposed. Bounds on the performance of the single-decision algorithm are derived. A theoretical analysis of the probability of error and of the equilibrium of the iterative algorithm is provided for a wide class of local outlier detection tests. The tradeoff between false alarm probability and detection probability is characterized theoretically and by simulation. MAC-layer issues, as well as the effect of packet losses are accounted fo

TruMan : trust management for vehicular networks

Orientador: Luiz Carlos Pessoa AlbiniDissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Informática. Defesa : Curitiba, 21/05/2018Inclui referências: p.54-60Área de concentração: Ciência da ComputaçãoResumo: À medida em que computadores tornam-se menores e mais poderosos, a possibilidade de integrá-los a objetos do cotidiano é cada vez mais interessante. Ao integrar processadores e unidades de comunicação sem fio a veículos, é possível criar uma rede veicular ad-hoc (VANET), na qual carros compartilham dados entre si para cooperar e criar ruas mais seguras e eficientes. Uma solução descentralizada ad-hoc, que não depende de infraestrutura pré-existente, conexão com a internet ou disponibilidade de servidores, é preferida para que a latência de entrega de mensagens seja a mais curta possível em situações críticas. No entanto, assim como é o caso de muitas novas tecnologias, VANETs serão um alvo de ataques realizados por usuários maliciosos, que podem obter benefícios ao afetar condições de trânsito. Para evitar tais ataques, uma importante característica para redes veiculares é o gerenciamento de confiança, permitindo que nós filtrem mensagens recebidas de acordo com valores de confiança previamente estabelecidos e designados a outros nós. Para gerar esses valores de confiança, nós usam informações adquiridas de interações passadas; nós que frequentemente compartilham dados falsos ou irrelevantes terão valores de confiança mais baixos do que os que aparentam ser confiáveis. Este trabalho introduz TruMan, um modelo de gerenciamento de confiança para redes veiculares no contexto de trajetos diários, utilizando o Working Day Movement Model como base para a mobilidade de nós. Este modelo de movimentação permite a comparação entre VANETs e redes sociais tradicionais, pois é possível observar que pares de veículos podem se encontrar mais de uma vez em diversos cenários: por exemplo, eles podem pertencer a vizinhos ou colegas de trabalho, ou apenas tomar rotas similares diariamente. Através de repetidos encontros, uma relação de confiança pode ser desenvolvida entre um par de nós. O valor de confiança resultante pode também ser usado para auxiliar outros nós que podem não ter uma relação desenvolvida entre si. O TruMan é baseado em um algoritmo já existente, que é desenvolvido para redes centralizadas e focado em modelos ad-hoc estáticos; seus conceitos são adaptados para servir uma rede descentralizada e dinâmica, que é o caso de VANETs. Usando valores de confiança formados por interações entre nós, um grafo de confiança é modelado; suas arestas representam as relações de confiança entre pares de nós. Então, componentes fortemente conexos do grafo são formados, de forma que cada nó em um componente confie nos outros nós do mesmo componente direta ou indiretamente. Um algoritmo de coloração de grafo é usado no grafo de componentes resultantes e, usando os resultados de coloração, é possível inferir quais nós são considerados maliciosos pelo consenso da rede. TruMan é rápido, colocando pouca carga nos computadores dos veículos, e satisfaz a maioria das propriedades desejáveis para modelos de gerenciamento de confiança veiculares. Palavras-chave: redes veiculares, gerenciamento de confiança, identificação de nós maliciosos.Abstract: As computers become small and powerful, the possibility of integrating them into everyday objects is ever more appealing. By integrating processors and wireless communication units into vehicles, it is possible to create a vehicular ad-hoc network (VANET), in which cars share data amongst themselves in order to cooperate and make roads safer and more efficient. A decentralized ad-hoc solution, which doesn't rely on previously existing infrastructure, Internet connection or server availability, is preferred so the message delivery latency is as short as possible in the case of life-critical situations. However, as is the case with most new technologies, VANETs might be a prime target for attacks performed by malicious users, who may benefit from affecting traffic conditions. In order to avoid such attacks, one important feature for vehicular networks is trust management, which allows nodes to filter incoming messages according to previously established trust values assigned to other nodes. To generate these trust values, nodes use information acquired from past interactions; nodes which frequently share false or irrelevant data will have lower trust values than the ones which appear to be reliable. This work introduces TruMan, a trust management model for vehicular networks in the context of daily commutes, utilizing the Working Day Movement Model as a basis for node mobility. This movement model allows the comparison of VANETs to traditional social networks, as it can be observed that pairs of vehicles are likely to meet more than once in several scenarios: for example, they can belong to neighbors or work colleagues, or simply take similar routes every day. Through these repeated encounters, a trust relationship can be developed between a pair of nodes. The resulting trust value can also be used to aid other nodes which might not have a developed relationship with each other. TruMan is based on a previously existing algorithm, which was developed for centralized networks and focused on static ad-hoc models; its concepts were adapted to serve a decentralized and dynamic network, which is the case of VANETs. Using trust values formed by node interactions, a trust graph is modeled; its edges represent trust relationships between pairs of nodes. Then, strongly connected components are formed so that each node in each component trusts other nodes in the same component directly or indirectly. A graph coloring algorithm is used on the resulting components graph and, using the coloring results, it is possible to infer which nodes are considered malicious by the consensus of the network. TruMan is fast, so it incurs low pressure on on-board computers, and is able to satisfy most desired properties for vehicular trust management models. Keywords: vehicular networks, trust management, malicious node identification