Resiliency of wireless sensor networks: Definitions and analyses

A scheme for WSNs (wireless sensor networks) security is given by dividing sensing tetrahedron into clusters and using the symmetric polynomials in this paper.The sensing tetrahedron is divided into a number of small grids.All those sensor nodes, both ordinary sensor nodes and heterogeneous sensor nodes are distributed in the sensing tetrahedron.In a grid, all ordinary sensor nodes and heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.All the heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.At last, all sensor nodes establish their keys directly or indirectly in the whole sensing tetrahedron.Analysis and comparison demonstrate this scheme enhances the WSN security, has good network connectivity, saves node storage, reduces network computing load, and extends the network lifetime.

A wireless sensor network consists of many important elements like Sensors, Bass station and User. A Sensor can measure many non electrical quantities like pressure, temperature, sound, etc and transmit this information to the base station by using internal transreceiver. A security of this transmitted data is very important as the data may contain important information. As wireless sensor network have many application in the military and civil domains so security of wireless sensor network become a critical concern. A Sybil attack is one of critical attack which can affect the routing protocols, fair recourse allocation, data aggregation and misbehavior detection parameters of network. A number of detection techniques to detect Sybil nodes have already designed to overcome the Sybil attack. Out of all the techniques few techniques which can improve the true detection rate and reduce false detection rate are discussed in this paper.

Wireless sensor networks are being used more and more. Sensor nodes can be distributed in hazardous environments to collect data. As these environments are usually unsecured, provide security in wireless sensor networks is vital. Detecting attacks in sensor networks is inevitable to provide security. Various attacks threaten sensor networks one of which is Sybil attack, which can be a big threat for geographical routing protocols and multi-path routing. In this paper, a distributed method has been presented using mobile agents and local information of each sensor to detect Sybil attack. The results of simulation show the efficacy of this method in comparison with previous methods.

Being one of the main technologies for Internet of Things (IoT), wireless sensor network is absolutely critical and plays an increasingly important role in the development of Internet of Things. Wireless sensor network is mobile network composed of sensor nodes with limited resources, like computation capability, energy, memory storage, and communication capability. Its characteristic results in that the security of wireless sensor network faces a great challenge. Hence, the security of wireless sensor network is an important issue for the development of IoT and shall be focused on. In this paper, a novel authentication scheme is proposed for wireless sensor networks based on theory of quadratic residues. It is making the use of master key to achieve simple symmetric cryptographic primitives and authentication operation and reach the aims of great resistance against the attacks and low energy consumption. Then the proposed scheme is compared with other network-wide key management schemes, obtaining better results in the aspects of security, efficiency, and scalability.

In-network data aggregation plays an important role to reduce the transmitting energy and data redundancy in large scale sensor networks. However, the security of wireless sensor networks is a challenging problem in the process of data aggregation. An efficient secure data aggregation is proposed to enhance the data security of wireless sensor networks. Firstly, the secure in-network aggregation tree is introduced, then a judgment method based on trust schema was used to detect whether a sensor node has potential misbehavior. After the detection, a local recovery schema is proposed to reduce the possibility to become isolated nodes, which will increase the security level in data aggregation in wireless sensor networks. The performance analysis shows the efficiency of the schema.

Wireless sensor network (WSN) works in a complex environment. To interdict the malicious nodes which attacks the safety of network, such as interrupt attacks and selective forwarding attacks, based on TS-BRS reputation model, a model for malicious node identification based on MNRT-OEP&RS algorithm is constructed. Using the linear regression of machine learning and combining the energy of nodes, data volume, number of adjacent nodes, the node sparsity and other deterministic parameters can solve environmental parameters. Then the similarity of between the benchmark reputation sequence and cycle reputation sequence sets the dynamic reputation double threshold are calculated in order to identify the malicious nodes by dynamically considering the information forwarding behavior. The simulated results show that the improved algorithm can guarantee the security of wireless sensor networks in complex environments effectively with above 90% recognition of malicious nodes and below 8% false positive rate.

Security in wireless sensor networks is critical due to its way of open communication. In this paper we have provided a solution to detect malicious nodes which perform radio transmission power control attack and sinkhole attack in wireless sensor networks. In the proposed approach, data transmission is divided into multiple rounds of equal time duration. Each node chooses the parent node in the beginning of the round for forwarding the packet towards sink. Each node adds its identity in the packet as a routing path marker and encrypts before forwarding to parent. Child node observes the parent, handles acknowledgement from 2-hop distance node and decides the trust on parent based on successful and unsuccessful transactions. Each node sends a trust value report via multiple paths to Sink at the end of the round. Sink identifies the malicious node by comparing trust value report received from each node with number of data packets received. Simulated the algorithm in NS-3 and performance analysis compared with other recently proposed approach. Simulation results show that proposed method detect the malicious nodes efficiently and early.

□ The major challenge faced by wireless sensor networks are security and communication delay. To solve this issue, a trust model is required to identify malevolent, selfish and compromised nodes. The existing trust systems developed for WSNs are incapable of satisfying these requirements because of their high overhead and low dependability. This paper does a brief review of the various trust models. Wide varieties of trust models are currently available to improve security and efficiency of wireless sensor networks. Among them, Lightweight Dependable Trust System for Clustered wireless sensor network (LDTS) is a suitable one. The LDTS proposes a lightweight trust decision making scheme predicated on nodes in the clustered WSNs. To reduce calculation overheads and improve energy efficiency LDTS is enhanced by integrating a unique protocol defined for data exchange and whenever a node transmits a packet, the packet is validated against this protocol.

Wireless sensor networks (WSNs) comprise tiny devices known as sensors. These devices are frequently employed in short-range communications and can perform various operations such as monitoring, collecting, analyzing, and processing data. WSNs do not require any infrastructure, are reliable, and can withstand adverse conditions. Sensor networks are autonomous structures in which the sensor nodes can enter or leave the network at any time instant. If the entering node is attacker node it will monitor the network operation and can cause security issues in the network that can affect communication. Existing literature presents security improvements in such networks in the form of cryptography, asymmetric techniques, key distribution, and various protocols. However, these techniques may not be effective in the case of autonomous structures and can increase computational complexity. In this paper, a convolutional technique (CT) is proposed that generates security bits using convolutional codes to prevent malicious node attacks on WSNs. Different security codes are generated at different hops and the simulation results demonstrate that the proposed technique enhances network security and reduces computational complexity compared to existing approaches.

In this paper, wireless sensor network (WSN) security issue in the presence of an eavesdropper is analysed. The sensor-sink as well as sensor-eavesdropper channels are assumed to be subjected to generalized-K fading. According to the physical layer security framework, we employ round-robin, optimal sensor and cumulative distribution function-based scheduling scheme to enhance secure connection between sensor nodes and to attain low probability of intercept. Novel analytical results are given in a form of easy-to-compute analytical expressions for the intercept probability. Additionally, asymptotic closed-form expressions are derived and diversity orders of scheduling schemes are determined. Numerical results demonstrate important impacts of fading and shadowing parameters of main and wiretap links, network size and selected scheme on WSN security. Presented results are validated by independent Monte Carlo simulations.

Security of wireless sensor networks is a major issue to protect sensor nodes from the attacker. Key management or key pre-distribution (KPS) is the preliminary step in the security of a sensor network, where secret keys are loaded into the sensor node’s memory before placement of the node in target positions. Various schemes for KPS have been proposed for location dependent as well as location independent wireless sensor networks. Costas arrays are $$n \times n$$ matrices grid represented where dots are placed for the l’s and leave blanks for the 0’s of the matrix for a positive integer n with the property that the vectors connecting two dots of the grid are all distinct as vectors. Costas arrays have a wide range of application including the construction of sonar signal pattern, cryptography, etc. Due to the Costas arrays property of uniqueness among their elements, it can be used in key pre-distribution of wireless sensor networks, especially in a location-dependent grid-based network. In this paper, we have proposed a Costas array based key pre-distribution scheme. Simulations are done on different network scenarios and the results were analyzed. Comparative performance analysis of the scheme is shown for different grid sized network considering various order of Costas array.

Wireless Sensor Networks (WSNs) are used in many applications in military, environmental, and health-related areas. These applications often include the monitoring of sensitive information such as enemy movement on the battlefield or the location of personnel in a building. Security is important in WSNs. However, WSNs suffer from many constraints, including low computation capability, small memory, limited energy resources, susceptibility to physical capture, and the use of insecure wireless communication channels. These constraints make security in WSNs a challenge. In this paper, we try to explore security issue in WSN. First, the constraints, security requirements and attacks with their corresponding countermeasures in WSNs are explained. Individual sensor nodes are subject to compromised security. An adversary can inject false reports into the networks via compromised nodes. Furthermore, an adversary can create a Gray hole by compromised nodes. If these two kinds of attacks occur simultaneously in a network, some of the existing methods fail to defend against those attacks. The Ad-hoc On Demand Distance (AODV) Vector scheme for detecting Gray-Hole attack and Statistical En-Route Filtering is used for detecting false report. For increasing security level, the Elliptic Curve Cryptography (ECC) algorithm is used. Simulations results obtain so far reduces energy consumption and also provide greater network security to some extent.

Wireless sensor networks (WSNs) are becoming more prevalent in a wide range of uses, including tracking the environment, medical care, and military monitoring. Yet, security, energy efficiency, and overall efficiency are important concerns for these networks. Ensuring the security of data transmission while maintaining energy efficiency is critical for the longevity and reliability of WSNs. This paper proposes a novel method to enhance both security and efficiency in WSNs done the integration of metaheuristic optimization algorithms. The proposed method leverages advanced optimization techniques such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Ant Colony Optimization (ACO) to dynamically optimize key parameters, including node deployment, routing protocols, and encryption schemes. By optimizing the network topology, routing paths, and energy consumption strategies, the algorithm significantly improves data security, minimizes energy usage, and enhances network lifespan. The simulation results show that the suggested methodology beats standard methods in terms of throughput, security resilience and energy efficiency. The findings highlight the potential of metaheuristic optimization algorithms as a robust tool for improving WSN security and operational efficiency in real-world applications

Wireless sensor network is of prime importance because of its applicability in various domains ranging from healthcare applications to military applications. Security of such networks is important as these carry confidential information. Security of Wireless Sensor Network is divided in three phases, prevention, detection and mitigation. In Prevention phase, care is taken so that attack should not occur. But most of the times it is not possible to prevent attacks, so it is very important to detect them as early as possible so that these will not harm a lot to wireless sensor network and that phase is called as intrusion detection. Once Intrusion has been detected we have to take actions to cure from it and it is called as mitigation. So, Intrusion detection is most important phase as far as security of wireless sensor network is concerned. This paper discusses about various detection methodologies such as Anomaly based, Misuse based and Specification based IDS, various decision making schemes for intrusion. Major focus of this paper is to understand various Intrusion Detection Systems that are proposed for wireless sensor network. These are discussed with different issues with advantages and disadvantages. Finally paper gives future directions for selection of Intrusion Detection System.

This paper presents an analysis of Wireless Sensor Network (WSN) security issues that take place due to eavesdropping. The sensor-eavesdropper channels and the sensor sinks are exposed to generalized K-fading. Based on the physical layer security framework we use cumulative distribution, optimal sensors and round robin scheduling scheme to decrease the probability of interception and to equip secure connection between the nodes. For identifying the interception probability, a novel analytical methodology is present with simple analytical expressions. Moreover, diversity orders of scheduling schemes and asymptotic closed-form expressions are evaluated. Numerical results show the crucial result of shadowing and fading parameters of wiretap and main links, selected schemes on WSN security and network size. We have analyzed the output using Monte Carlo simulation and conclusions show the validation of the proposed work.