Improve Quality of Service for the Internet of Things using Blockchain & Machine Learning Algorithms.

[EN] The quality of service (QoS) parameters in IoT applications plays a prominent role in determining the performance of an application. Considering the significance and popularity of IoT systems, it can be predicted that the number of users and IoT devices are going to increase exponentially shortly. Therefore, it is extremely important to improve the QoS provided by IoT applications to increase their adaptability. Majority of the IoT systems are characterized by their heterogeneous and diverse nature. It is challenging for these systems to provide high-quality access to all the connecting devices with uninterrupted connectivity. Considering their heterogeneity, it is equally difficult to achieve better QoS parameters. Artificial intelligence-based machine learning (ML) tools are considered a potential tool for improving the QoS parameters in IoT applications. This research proposes a novel approach for enhancing QoS parameters in IoT using ML and Blockchain techniques. The IoT network with Blockchain technology is simulated using an NS2 simulator. Different QoS parameters such as delay, throughput, packet delivery ratio, and packet drop are analyzed. The obtained QoS values are classified using different ML models such as Naive Bayes (NB), Decision Tree (DT), and Ensemble, learning techniques. Results show that the Ensemble classifier achieves the highest classification accuracy of 83.74% compared to NB and DT classifiers.SIPublicación en abierto financiada por el Consorcio de Bibliotecas Universitarias de Castilla y León (BUCLE), con cargo al Programa Operativo 2014ES16RFOP009 FEDER 2014-2020 DE CASTILLA Y LEÓN, Actuación:20007-CL - Apoyo Consorcio BUCL

Optimized Load Centroid and Rabin Onion Secured Routing in Wireless Sensor Network for IoT

Advances in wireless communication have geared up extensive insights wherein the sensors can themselves communicate with other sensors that form significant parts of the Internet of Things (IoT). However, the large-scale acceptance of WSN for IoT is still surfacing threats and controversies that apprehend the security aspects. There are a lot of attacks that can manipulate the routein WSN for IoT. In this work, an Optimized Load Centroid and Rabin Onion Routing (OLC-ROR) method are designed to improve the throughput rate with minimum routing overhead and latency. The proposed method is based on a Centroid and Rabin Signature, a Digital Signature technique. First, the optimal route is identified by considering both the load and residual energy using Load Centroid function. Then onion routing is used for selecting secured route amongst the optimality. Besides, the node genuineness is checked by applying the Rabin Signature

Optimized Load Centroid and Rabin Onion Secured Routing in Wireless Sensor Network for IoT

Advances in wireless communication have geared up extensive insights wherein the sensors can themselves communicate with other sensors that form significant parts of the Internet of Things (IoT). However, the large-scale acceptance of WSN for IoT is still surfacing threats and controversies that apprehend the security aspects. There are a lot of attacks that can manipulate the routein WSN for IoT. In this work, an Optimized Load Centroid and Rabin Onion Routing (OLC-ROR) method are designed to improve the throughput rate with minimum routing overhead and latency. The proposed method is based on a Centroid and Rabin Signature, a Digital Signature technique. First, the optimal route is identified by considering both the load and residual energy using Load Centroid function. Then onion routing is used for selecting secured route amongst the optimality. Besides, the node genuineness is checked by applying the Rabin Signature

IoT Security Evolution: Challenges and Countermeasures Review

Internet of Things (IoT) architecture, technologies, applications and security have been recently addressed by a number of researchers. Basically, IoT adds internet connectivity to a system of intelligent devices, machines, objects and/or people. Devices are allowed to automatically collect and transmit data over the Internet, which exposes them to serious attacks and threats. This paper provides an intensive review of IoT evolution with primary focusing on security issues together with the proposed countermeasures. Thus, it outlines the IoT security challenges as a future roadmap of research for new researchers in this domain