Biblio

In view of the problem that the health status and safety monitoring of the traditional intelligent home are mainly dependent on the manual inspection, this paper introduces the intelligent home-based remote monitoring system by introducing the Internet-based Internet of Things technology into the intelligent home condition monitoring and safety assessment. The system's Android remote operation based on the MVP model to develop applications, the use of neural networks to deal with users daily use of operational data to establish the network data model, combined with S3C2440A microcontrollers in the gateway to the embedded Linux to facilitate different intelligent home drivers development. Finally, the power line communication network is used to connect the intelligent electrical appliances to the gateway. By calculating the success rate of the routing nodes, the success rate of the network nodes of 15 intelligent devices is 98.33%. The system can intelligent home many electrical appliances at the same time monitoring, to solve the system data and network congestion caused by the problem can not he security monitoring.

Wireless mesh networks (WMNs) are known for possessing good attributes such as low up-front cost, easy network maintenance, and reliable service coverage. This has largely made them to be adopted in various environments such as; school campus networks, community networking, pervasive healthcare, office and home automation, emergency rescue operations and ubiquitous wireless networks. The routing nodes are equipped with self-organized and self-configuring capabilities. However, the routing mechanisms of WMNs depend on the collaboration of all participating nodes for reliable network performance. The authors of this paper have noted that most routing algorithms proposed for WMNs in the last few years are designed with the assumption that all the participating nodes will collaboratively be involved in relaying the data packets originated from a source to a multi-hop destination. Such design approach however exposes WMNs to vulnerability such as malicious packet drop attack. This paper presents an evaluation of the effect of the black hole attack with other influential factors in WMNs. In this study, NS-3 simulator was used with AODV as the routing protocol. The results show that the packet delivery ratio and throughput of WMN under attack decreases sharply as compared to WMN free from attack. On an average, 47.41% of the transmitted data packets were dropped in presence of black hole attack.

Establishing trust relationships between routing nodes represents a vital security requirement to establish reliable routing processes that exclude infected or selfish nodes. In this paper, we propose a new security scheme for the Internet of things and mainly for the RPL (Routing Protocol for Low-power and Lossy Networks) called: Metric-based RPL Trustworthiness Scheme (MRTS). The primary aim is to enhance RPL security and deal with the trust inference problem. MRTS addresses trust issue during the construction and maintenance of routing paths from each node to the BR (Border Router). To handle this issue, we extend DIO (DODAG Information Object) message by introducing a new trust-based metric ERNT (Extended RPL Node Trustworthiness) and a new Objective Function TOF (Trust Objective Function). In fact, ERNT represents the trust values for each node within the network, and TOF demonstrates how ERNT is mapped to path cost. In MRTS all nodes collaborate to calculate ERNT by taking into account nodes' behavior including selfishness, energy, and honesty components. We implemented our scheme by extending the distributed Bellman-Ford algorithm. Evaluation results demonstrated that the new scheme improves the security of RPL.