Wireless sensor networks (WSNs) have demonstrated research and developmental interests in numerous fields, like communication, agriculture, industry, smart health, monitoring, and surveillance. In the area of agriculture production, IoT-based WSN has been used to observe the yields condition and automate agriculture precision using various sensors. These sensors are deployed in the agricultural environment to improve production yields through intelligent farming decisions and obtain information regarding crops, plants, temperature measurement, humidity, and irrigation systems. However, sensors have limited resources concerning processing, energy, transmitting, and memory capabilities that can negatively impact agriculture production. Besides efficiency, the protection and security of these IoT-based agricultural sensors are also important from malicious adversaries. In this article, we proposed an IoT-based WSN framework as an application to smart agriculture comprising different design levels. Firstly, agricultural sensors capture relevant data and determine a set of cluster heads based on multi-criteria decision function. Additionally, the strength of the signals on the transmission links is measured while using signal to noise ratio (SNR) to achieve consistent and efficient data transmissions. Secondly, security is provided for data transmission from agricultural sensors towards base stations (BS) while using the recurrence of the linear congruential generator. The simulated results proved that the proposed framework significantly enhanced the communication performance as an average of 13.5% in the network throughput, 38.5% in the packets drop ratio, 13.5% in the network latency, 16% in the energy consumption, and 26% in the routing overheads for smart agriculture, as compared to other solutions.

The infrastructure of wireless sensor networks (WSN) is structured in an ad-hoc manner and organized nodes reporting the events to the Base Station (BS). A WSN is integrated with smart technologies to develop fast Internet of Things (IoT) communications among different applications. Recently, many researchers proposed their solutions to optimize IoT data transmissions in an energy efficient manner with cost effective support. However, most of the solutions have focused on the design and development of static topologies and overlooked the dynamic structure of mobile sensor nodes. Furthermore, due to limited constraints of sensor nodes with open accessibility of wireless communications medium, data protection against malicious activities need to be redesign with the least network overheads. Therefore, the contribution of this article is to propose an intrusion prevention framework for mobile IoT devices with its integration to WSN so that to provide data security with improved network delivery ratio. The proposed framework is composed of two sub-components. Firstly, non-overlapping and autonomously organized clusters are generated and maintained the clusters’ stability based on the uncertainty principle. Secondly, end-to-end secure and multi-hop routing paths are developed based on the blockchain architecture. The simulation results demonstrate a significant improvement when compared to existing solutions in terms of different network metrics.

Due to the advancement of information and communication technologies, the use of Internet of Things (IoT) devices has increased exponentially. In the development of IoT, wireless sensor networks (WSNs) perform a vital part and comprises of low-cost smart devices for information gathering. However, such smart devices have constraints in terms of computation, processing, memory and energy resources. Along with such constraints, one of the fundamental challenges for WSN is to achieve reliability with the security of transmitted data in a vulnerable environment against malicious nodes. This paper aims to develop an energy-efficient and secure routing protocol (ESR) for intrusion avoidance in IoT based on WSN to increase the network period and data trustworthiness. Firstly, the proposed protocol creates different energy-efficient clusters based on the intrinsic qualities of nodes. Secondly, based on the (k,n) threshold-based Shamir secret sharing scheme, the reliability and security of the sensory information among the base station (BS) and cluster head are achieved. The proposed security scheme presents a light-weight solution to cope with intrusions generated by malicious nodes. The experimental results using the network simulator (NS-2) demonstrate that the proposed routing protocol achieved improvement in terms of network lifetime as 37%, average end-to-end delay as 24%, packet delivery ratio as 30%, average communication cost as 29%, network overhead as 28% and the frequency of route re-discoveries as 38% when compared with the existing work under dynamic network topologies.

The advent of online social networks (OSN) has transformed a common passive reader into a content contributor. It has allowed users to share information and exchange opinions, and also express themselves in online virtual communities to interact with other users of similar interests. However, OSN have turned the social sphere of users into the commercial sphere. This should create a privacy and security issue for OSN users. OSN service providers collect the private and sensitive data of their customers that can be misused by data collectors, third parties, or by unauthorized users. In this paper, common security and privacy issues are explained along with recommendations to OSN users to protect themselves from these issues whenever they use social media.

Nowadays, the integration of Wireless Sensor Networks (WSN) and the Internet of Things (IoT) provides a great concern for the research community for enabling advanced services. An IoT network may comprise a large number of heterogeneous smart devices for gathering and forwarding huge data. Such diverse networks raise several research questions, such as processing, storage, and management of massive data. Furthermore, IoT devices have restricted constraints and expose to a variety of malicious network attacks. This paper presents a Secure Sensor Cloud Architecture (SASC) for IoT applications to improve network scalability with efficient data processing and security. The proposed architecture comprises two main phases. Firstly, network nodes are grouped using unsupervised machine learning and exploit weighted-based centroid vectors for the development of intelligent systems. Secondly, the proposed architecture makes the use of sensor-cloud infrastructure for boundless storage and consistent service delivery. Furthermore, the sensor-cloud infrastructure is protected against malicious nodes by using a mathematically unbreakable one-time pad (OTP) encryption scheme to provide data security. To evaluate the performance of the proposed architecture, different simulation experiments are conducted using Network Simulator (NS3). It has been observed through experimental results that the proposed architecture outperforms other state-of-the-art approaches in terms of network lifetime, packet drop ratio, energy consumption, and transmission overhead.

Wireless mesh networks consist of various mesh clients that are organized in an unfixed infrastructure and packets are forwarded using a multi-hop model. Routing protocols have a significant impact on mesh networks because their performance has a crucial effect on nodes connectivity and throughput. Recently, the integration of mesh clients with the Internet of Things (IoT) has gained significant importance to connect billions of machines and achieve fast coverage with minimum network cost. However, if mesh clients are mobile, then data routing via intermediate nodes gives a noteworthy effect on the network performance and latency. Furthermore, over the Internet, a malicious node may be a part of the mesh network and as a result, the sending information can be manipulated and compromised. Therefore, this research article aims to propose a robust and trusted scheme (RTS) for IoT-based mobile mesh networks to provide reliable routing, data confidentiality, and integrity. Firstly, the proposed scheme presents a robust data routing among mobile mesh clients, routers and gateway devices based on the network parameters and measurement of wireless channels. Moreover, the wireless channels between mesh devices are formulated based on the efficacy of link costs for data dissemination. Besides, the location of mobile mesh clients is determined by computing the distance vector at a regular time interval. Secondly, a secure and authentic data protection technique is proposed using public-private key cryptography, which aims to increase the protection of mesh clients with minimal overhead. The competence of the proposed scheme is significantly improved with respect to network throughput by an average of 14%, packet loss rate by an average of 37%, latency rate by an average of 12%, computational overhead by an average of 34%, and energy efficiency by an average of 20% as compared to other works.