Wireless Sensor Networks (WSNs): Security and Privacy Issues and Solutions

Wireless sensor networks (WSNs) have become one of the current research areas, and it proves to be a very supportive technology for various applications such as environmental-, military-, health-, home-, and office-based applications. WSN can either be mobile wireless sensor network (MWSN) or static wireless sensor network (SWSN). MWSN is a specialized wireless network consisting of considerable number of mobile sensors, however the instability of its topology introduces several performance issues during data routing. SWSNs consisting of static nodes with static topology also share some of the security challenges of MWSNs due to some constraints associated with the sensor nodes. Security, privacy, computation and energy constraints, and reliability issues are the major challenges facing WSNs, especially during routing. To solve these challenges, WSN routing protocols must ensure confidentiality, integrity, privacy preservation, and reliability in the network. Thus, efficient and energy-aware countermeasures have to be designed to prevent intrusion in the network. In this chapter, we describe different forms of WSNs, challenges, solutions, and a point-to-point multi-hop-based secure solution for effective routing in WSNs

Clustering objectives in wireless sensor networks: A survey and research direction analysis

Wireless Sensor Networks (WSNs) typically include thousands of resource-constrained sensors to monitor their surroundings, collect data, and transfer it to remote servers for further processing. Although WSNs are considered highly flexible ad-hoc networks, network management has been a fundamental challenge in these types of net- works given the deployment size and the associated quality concerns such as resource management, scalability, and reliability. Topology management is considered a viable technique to address these concerns. Clustering is the most well-known topology management method in WSNs, grouping nodes to manage them and/or executing various tasks in a distributed manner, such as resource management. Although clustering techniques are mainly known to improve energy consumption, there are various quality-driven objectives that can be realized through clustering. In this paper, we review comprehensively existing WSN clustering techniques, their objectives and the network properties supported by those techniques. After refining more than 500 clustering techniques, we extract about 215 of them as the most important ones, which we further review, catergorize and classify based on clustering objectives and also the network properties such as mobility and heterogeneity. In addition, statistics are provided based on the chosen metrics, providing highly useful insights into the design of clustering techniques in WSNs.publishedVersio

PAWN: a payload-based mutual authentication scheme for wireless sensor networks

Copyright © 2016 John Wiley & Sons, Ltd. Wireless sensor networks (WSNs) consist of resource-starving miniature sensor nodes deployed in a remote and hostile environment. These networks operate on small batteries for days, months, and even years depending on the requirements of monitored applications. The battery-powered operation and inaccessible human terrains make it practically infeasible to recharge the nodes unless some energy-scavenging techniques are used. These networks experience threats at various layers and, as such, are vulnerable to a wide range of attacks. The resource-constrained nature of sensor nodes, inaccessible human terrains, and error-prone communication links make it obligatory to design lightweight but robust and secured schemes for these networks. In view of these limitations, we aim to design an extremely lightweight payload-based mutual authentication scheme for a cluster-based hierarchical WSN. The proposed scheme, also known as payload-based mutual authentication for WSNs, operates in 2 steps. First, an optimal percentage of cluster heads is elected, authenticated, and allowed to communicate with neighboring nodes. Second, each cluster head, in a role of server, authenticates the nearby nodes for cluster formation. We validate our proposed scheme using various simulation metrics that outperform the existing schemes

An energy-efficient clustering protocol using fuzzy logic and network segmentation for heterogeneous WSN

Wireless sensor networks have become an emerging research area due to their importance in the present industrial application. The enlargement of network lifetime is the major limitation in WSN. Several routing protocols study the extension of lifespan in WSN. Routing protocols significantly influence on the global of energy consumption for sensors in WSN. It is essential to correct the energy efficiency performance of routing protocol in order to improve the lifetime. The protocols based on clustering are the most routing protocols in WSN to reduce energy consumption. The protocols dedicate to WSN have demonstrated their limitation in expanding the lifetime of the network. In this paper, we present Hybrid SEP protocol : Multi-zonal Fuzzy logic heterogeneous Clustering based on Stable Election Protocol (FMZ-SEP). The FMZ-SEP characterizes by four parameters: WSN segmentation (splitting the WSN into the triangle zones ), the Subtractive Clustering Method to determine a correct number of clusters, the FCM and the SEP protocol. The FMZ-SEP prolong the stability period and extend the lifetime. The simulation results point out that the stability period of FMZ-SEP. FMZ-SEP protocol outperforms of MZ-SEP, FSEP and SEP protocol by improving the network lifetime and the stability period

Swarm Intelligence-Based Bio-Inspired Framework for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are gaining immense popularity as a result of their wide potential applications in industry, military, and academia such as military surveillance, agricultural monitoring, industrial automation, and smart homes. Currently, WSN has garnered tremendous significance as it is has become the core component of the Internet of Things (IOT) area. Modern-day applications need a high level of security and quick response mechanism to deal with the emerging data trends where the response is measured in terms of latency, throughput, and scalability. Further, critical security issues need to be considered due to various types of threats and attacks WSNs are exposed to as they are deployed in harsh and hostile environments unattended in most of the mission critical applications. The fact that a complex sensor network consisting of simple computing units has similarities with specific animal communities, whose members are often very simple but produce together more sophisticated and capable entities. Thus, from an algorithmic viewpoint, bio-inspired framework such as swarm intelligence technology may provide valuable alternative to solve the large scale optimization problems that occur in wireless sensor networks. Self-organization, on the other hand, can be useful for distributed control and management tasks. In this chapter, swarm intelligence and social insects-based approaches developed to deal with a bio-inspired networking framework are presented. The proposed approaches are designed to tackle the challenges and issues in the WSN field such as large scale networking, dynamic nature, resource constraints, and the need for infrastructure-less and autonomous operation having the capabilities of self-organization and survivability. This chapter covers three phases of the research work carried out toward building a framework. First phase involves development of SIBER-XLP model, Swarm Intelligence Based Efficient Routing protocol for WSN with Improved Pheromone Update Model, and Optimal Forwarder Selection Function which chooses an optimal path from source to the sink to forward the packets with the sole objective to improve the network lifetime by balancing the energy among the nodes in the network and at the same time selecting good quality links along the path to guarantee that node energy is not wasted due to frequent retransmissions. The second phase of the work develops a SIBER-DELTA model, which represents Swarm Intelligence Based Efficient Routing protocol for WSN taking into account Distance, Energy, Link Quality, and Trust Awareness. WSNs are prone to behavior related attacks due to the misbehavior of nodes in forwarding the packets. Hence, trust aware routing is important not only to protect the information but also to protect network performance from degradation and protect network resources from undue consumption. Finally, third phase of the work involves the development of SIBER-DELTAKE hybrid model, an improved ACO-KM-ECC trust aware routing protocol based on ant colony optimization technique using K-Medoids (KM) algorithm for the formation of clusters with Elliptical Curve Cryptography (ECC). KM yields efficiency in setting up a cluster head and ECC mechanism enables secure routing with key generation and management. This model takes into account various critical parameters like distance, energy, link quality, and trust awareness to discover efficient routing

Adaptive Distributed Fair Scheduling for Multiple Channels in Wireless Sensor Networks

A novel adaptive and distributed fair scheduling (ADFS) scheme for wireless sensor networks (WSN) in the presence of multiple channels (MC-ADFS) is developed. The proposed MC-ADFS increases available network capacity and focuses on quality-of-service (QoS) issues. when nodes access a shared channel, the proposed MC-ADFS allocates the channel bandwidth proportionally to the packet\u27s weight which indicates the priority of the packet\u27s flow. The packets are dynamically assigned to channels based on the packet weight and current channel utilization. The dynamic assignment of channels is facilitated by use of receiver-based allocation and alternative routes. Moreover, MC-ADFS allows the dynamic allocation of network resources with little added overhead. Packet weights are initially assigned using user specified QoS criteria, and subsequently updated as a function of delay and queued packets. The back-off interval is also altered using the weight adaptation. The weight update and back-off interval selection ensure global fairness is attained even with variable service rates

Unified Role Assignment Framework For Wireless Sensor Networks

Wireless sensor networks are made possible by the continuing improvements in embedded sensor, VLSI, and wireless radio technologies. Currently, one of the important challenges in sensor networks is the design of a systematic network management framework that allows localized and collaborative resource control uniformly across all application services such as sensing, monitoring, tracking, data aggregation, and routing. The research in wireless sensor networks is currently oriented toward a cross-layer network abstraction that supports appropriate fine or course grained resource controls for energy efficiency. In that regard, we have designed a unified role-based service paradigm for wireless sensor networks. We pursue this by first developing a Role-based Hierarchical Self-Organization (RBSHO) protocol that organizes a connected dominating set (CDS) of nodes called dominators. This is done by hierarchically selecting nodes that possess cumulatively high energy, connectivity, and sensing capabilities in their local neighborhood. The RBHSO protocol then assigns specific tasks such as sensing, coordination, and routing to appropriate dominators that end up playing a certain role in the network. Roles, though abstract and implicit, expose role-specific resource controls by way of role assignment and scheduling. Based on this concept, we have designed a Unified Role-Assignment Framework (URAF) to model application services as roles played by local in-network sensor nodes with sensor capabilities used as rules for role identification. The URAF abstracts domain specific role attributes by three models: the role energy model, the role execution time model, and the role service utility model. The framework then generalizes resource management for services by providing abstractions for controlling the composition of a service in terms of roles, its assignment, reassignment, and scheduling. To the best of our knowledge, a generic role-based framework that provides a simple and unified network management solution for wireless sensor networks has not been proposed previously

Clustering Based Routing Protocol LEACH and Its’ Variants: A Review

In clustering technique LEACH is refer as an important protocol of the hierarchical routing protocols that is applied to decrease the loss of energy in disseminating and collecting. This paper is related with definite hierarchical routing protocols that are generated from the LEACH. This paper presents some main points of few problems and drawbacks in LEACH and explained how to recover via the sections of LEACH. In this paper various properties are compared, also accomplishment and problems of all hierarchical routing protocols are compared. In this it is also discussed regarding the LEACH and its several protocols that are depend on hierarchal routing protocol

3R: a reliable multi-agent reinforcement learning based routing protocol for wireless medical sensor networks.

Interest in the Wireless Medical Sensor Network (WMSN) is rapidly gaining attention thanks to recent advances in semiconductors and wireless communication. However, by virtue of the sensitive medical applications and the stringent resource constraints, there is a need to develop a routing protocol to fulfill WMSN requirements in terms of delivery reliability, attack resiliency, computational overhead and energy efficiency. This paper proposes 3R, a reliable multi-agent reinforcement learning routing protocol for WMSN. 3R uses a novel resource-conservative Reinforcement Learning (RL) model to reduce the computational overhead, along with two updating methods to speed up the algorithm convergence. The reward function is re-defined as a punishment, combining the proposed trust management system to defend against well-known dropping attacks. Furthermore, an energy model is integrated with the reward function to enhance the network lifetime and balance energy consumption across the network. The proposed energy model uses only local information to avoid the resource burdens and the security concerns of exchanging energy information. Experimental results prove the lightweightness, attacks resiliency and energy efficiency of 3R, making it a potential routing candidate for WMSN