Lately, the Internet of Things (IoT) has opened up new opportunities to business and enterprises; however, the cost of providing security and privacy best practices is preventing numerous organizations from adopting this innovation. With the proliferation of connecting devices in IoT, significant increases have been recorded in energy use, harmful contamination and e-waste. A new paradigm of green IoT is aimed at designing environmentally friendly protocols by reducing the carbon impact and promote efficient techniques for energy use. There is a consistent effort of designing distinctive security structures to address vulnerabilities and attacks. However, most of the existing schemes are not energy efficient. To bridge the gap, we propose the hybrid logical security framework (HLSF), which offers authentication and data confidentiality in IoT. HLSF uses a lightweight cryptographic mechanism for unique authentication. It enhances the level of security and provides better network functionalities using energy-efficient schemes. With extensive simulation, we compare HLSF with two existing popular security schemes, namely, constrained application protocol (CoAP) and object security architecture for IoT (OSCAR). The result shows that HLSF outperforms CoAP and OSCAR in terms of throughput with low computational, storage and energy overhead, even in the presence of attackers.

Summary In this study, Burr‐XII and Rayleigh distributions are combined to form a new mixture model that is considered to model heterogeneous data. Our objective is to estimate parameters of the proposed mixture model using Bayesian technique under type‐I censoring. Bayesian parameter estimation for the said mixture model is conducted by using informative priors, ie, gamma and squared root inverted gamma (SRIG) as well as noninformative prior, ie, Jeffrey's prior. Squared error loss function (SELF) and quadratic loss function (QLF) are employed to obtain and Bayes estimators. Properties of the proposed Bayes estimators are highlighted through a simulation study. When prior distributions and loss functions utilized in the study are compared in terms of posterior risks, informative prior found to be more suitable and decision turns out to be in favor of QLF. Prediction limits for the single sample case and two sample case are obtained to provide an insight into future sample data. Application of the proposed model is also elaborated using a real‐life example.

The idea of the Internet of Things (IoT) was developed in parallel to wireless sensor networks (WSNs). In a mobile WSN, a sensor node is generally assumed to move around randomly in direction and speed. Thus, a random waypoint is commonly used for node mobility modeling. Unfortunately, it does not consider the overlapping sensing coverage (OSC) at continuous moves or at a given time of sensor nodes. On top of this, there is no security mechanism to authenticate the sensor nodes and their privacy. Thus, results in a higher probability of occurring OSC in the network and the threats to the network through inside and outside attackers. To resolve these issues in 3D WSNs, this paper proposes a secure and privacy-preserving node mobility model that the nodes take part in periodic rounds securely. An ID-based authentication mechanism for joining nodes in the network and detection of the malicious node based on their survival strategies are proposed in the model. Moreover, the decision making of a next destination during a pause time in a round is three-folded. First, a set of member nodes are elected. Then, all nodes predict their prospective destinations randomly and the member nodes broadcast their prospective destinations' information to neighbors. Finally, the neighborhood nodes adjust their prospective destinations considering the broadcasted information, in order to reduce the OSC in the network. The simulation experiments show that the proposed model reduces the OSC in the network and detects the malicious nodes, thus, results in a higher effective sensing coverage rate of the network in a secure way. INDEX TERMS Internet of things, wireless sensor network, security, privacy, random walk, sensing coverage, overlapping sensing coverage, effective sensing coverage rate.

Nowadays, the most of commercial buildings are build-out with complex architecture and decorated with

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