A Smart Contract-based Blockchain Solution in IoT Networks (Published)
The emergence and growing use of advanced technologies has opened up new possibilities for addressing the security challenges of resource-constrained IoT net- works. As IoT devices exchange sensitive data, secure key management is essential for IoT network security, particularly during the key revocation phase. However, current IoT key management solutions require improvements due to the resource limitations of IoT devices. Despite these limitations, existing key revocation solutions still have several areas for improvement, including high communication overheads. Therefore, a decentralized and efficient solution is necessary to address these issues in IoT networks, with a focus on security. This paper proposes a new solution for key revocation based on Blockchain technology using smart contracts to minimize communication overhead and energy consumption in IoT networks. The paper presents a security and performance analysis to assess its correctness. The results indicate that our proposal outperforms other solutions by having a reduced communication overhead of 93.55%, 91.87%, and 99.75% compared to other solutions during the compromising, leaving, and draining cases, respectively. This demonstrates that our solution is efficient and suitable for IoT networks.
Keywords: Blockchain, Internet of Things (IoT), Security, Wireless Sensor Networks (WSNs)., key revocation
Detection of Faulty Sensors in Wireless Sensor Networks and Avoiding the Path Failure Nodes (Review Completed - Accepted)
For variety of applications, Wireless Sensor Networks (WSNs) have become a new information collection and a monitoring solution. Faults occurring due to sensor nodes are common due low-cost sensors used in WSNs, deployed in large quantities and prone to failure. The goal of this paper is to detect faulty sensors in WSNs and avoiding the path failure nodes. Fault detection is based on the local pair-wise verification between the sensors monitoring the same physical system. Specifically, a linear relationship is shown between the output of any pair of sensors, when the input of a system comes from a common source. Using this relationship, faulty sensors may be detected by using forecasting model based on the parameter (i.e., temperature) and it also identifies which sensor is normal or abnormal. After the fault nodes are detected, first of all disable all the faulty nodes so that network is not affected by erroneous reading and send the information to the base station. Due to the nature of proposed algorithm, it can be scaled to large sensor networks and also saves energy from reduced wireless communication compared to the centralized approaches
Keywords: Fault detection, Forecasting, Wireless Sensor Networks (WSNs).