Security In Wireless Sensor Networks Research Articles

Costas array based key pre-distribution scheme (CAKPS) for WSN and its performance analysis

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.

Detection of Wormhole Attack and Secure Path Selection in Wireless Sensor Network

In Wireless Sensor Network (WSN), securable data transmission is one of the most challenges. During the transmission between the source and a destination node, routing information of the particular path may be misbehaved by the particular nodes which are known as wormhole nodes/attackers. The paths which include the wormhole nodes are known as wormhole attacked paths. For improving security in WSN, these wormhole attacked paths should be identified. To achieve this, wormhole attack detection method and optimal or secure path selection are presented in this paper. Initially, ‘K’ paths or multiple paths are generated between source and destination using Ad-hoc On demand Multipath Distance Vector (AOMDV) routing protocol. Then, the source node identifies the wormhole attacked path by verifying the Detection Packet (DP) and Feedback Packet (FP) from the destination. After detecting the wormhole attacked paths, the source node selects the optimal path among the attacker free paths using Particle Swarm Optimization (PSO) algorithm. Simulation results show that the performance of the proposed approach improves energy efficiency and network lifetime of the network.

Model for Malicious Node Recognition Based on Environmental Parameter Optimization and Time Reputation Sequence

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.

A Secure and Energy Efficient Sensor Nodes in Wireless Sensor Networks using Improved Ant Lion Optimization

The Wireless Sensor Network (WSN) has three critical issues as like network lifetime, saving energy and security. A sensor node has limited battery power so it does need an effective key distribution and management mechanism for a safe communication. In the research literatures a massive key supply and administration methodology had been proposed. Thus, there exists a literature report of numerous schemes in WSNs for Key management and done with a wide analysis to classify the available techniques of key management and the expectable network security on them is studied. In this method a secure efficient key management scheme is proposed with the help of Ant Lion Optimization (ALO) for WSN. The aim of this method is to obtain improved security strength with cost effective. The nature of the ant lion in hunting its prey is derived for the ALO algorithm which known for its meta-heuristic function. In resolving the optimization complications with the advantage of having a great speed and limited parameters it is proved to have a better performance.

A Multi Objective Particle Swarm Optimization for Wireless Sensor Networks and Routing Security

WSN stands for Wireless Sensor Network it is an prefect models of the IoT or Internet of Things that gives checking administrations to catastrophic events, for example, volcanoes ejection and seismic tremor which can influence the life of person. All things considered, the QoS or Quality-of-Service it is a significant problem of the basic application so that it is adequate as well as heartiness is guaranteed. Other than this without a doubt administrations and commitments in checking frameworks, WSN's restricted assets can seriously corrupt the Quality-of-Service in the application of Internet of Things. There will be a decrease in the Quality-of-Service because of the blockage in the wireless service network in the application. For these situtations proficient utilization for the rare assets might be critical for guaranteeing consistent tramission of the information. Decreasing pace in the retransmission of the parcel that occurs due to the blockage diminishes sensor hubs power utilization. PDNC also known as Packet Discarding based Node Clustering that is a specific bundle disposing of technique is presented in this research paper. Every hubs conveyed will be bunched to a few gatherings that focuses on the zone and at once selection of a group head will be done. Parcel disposing of procedure will at that point be conveyed at every hub to diminish the quantity of bundles adding to blockage. Reenactment examination utilizing NS-2 demonstrates that the proposed method can lessen blockage along these lines improve the general execution.

Fuzzy based Dynamic Security Parameters Determination Method to Improve Energy Efficiency

Fine dust is a harmful substance that floats in the atmosphere. It is not filtered well in the bronchus and causes health problems when it accumulates in the body. Fine dust that is present in the air outside can flow into buildings through windows and other openings, adversely affecting indoor air quality. It has negative health effects on people who live indoors. As attention to problems associated with fine dust gradually rises, the importance of continuously managing the quality of indoor air through air purification rises. Therefore, recently, research and development into systems to periodically purify indoor air are being carried out. This paper introduces an air purification system, a Wireless Sensor Networks (WSNs)-based Internet of Things (IoT) air purification system. In the WSNs-based IoT air purification system, the IoT air purifier is controlled based on event information that the WSNs senses, so it is important to maintain the security of the event information. To this end, a WSNs security protocol, Interleaved Hop by hop Authentication (IHA), is used in this system. IHA is a security protocol in which sensor nodes and a Base Station (BS) detect and drop false reports if the number of compromised sensor nodes does not exceed a security threshold. That is, because the false report injection attack that the number of compromised sensor nodes exceeds security threshold can’t defend by IHA, it is detected and defended through Data Calibration. However, considerable energy of the sensor nodes is unnecessarily consumed in the process of forwarding false reports. Thus, this paper proposes a method of decreasing and increasing security thresholds dynamically according to the network situation using fuzzy logic. This proposed scheme has the advantages of improvements in both the overall energy efficiency and network lifetime in WSNs.

Secure, Resilient and Green Computing in Wireless Sensor Networks

Secure, Resilient and Green Computing in Wireless Sensor Networks

Hybrid Cryptography Algorithm for Securing Wireless Sensor Networks from Node Clone Attack

Background: Security in WSNs is the most significant because sensor nodes deployed are in an unattended environment, and the information is communicated over insecure wireless channels. Therefore, there is a need to put enhanced security measures for securing sensor nodes as well as ensure secured transmission of information. Objective: These resource-constrained networks suffer from various attacks namely, node clone attack, Sybil attack, and DoS attack. In this paper, we proposed a hybrid cryptography algorithm, which secured WSNs from node clone attack. Methods: The proposed algorithm uses a combination of symmetric (AES) and asymmetric (ECC) cryptography techniques along with the hash function. Further, the proposed algorithm checks the integrity of messages during communication in the sensor network. Results: The performance of the proposed hybrid algorithm was examined through the various metrics like communication, computation, and storage overheads. The comparison of the results validates the efficiency of the proposed hybrid algorithm. Conclusion: The proposed hybrid algorithm provides a secure and efficient solution to the energy sensor networks.

Enhancing the Robustness and Security Against Various Attacks in a Scale: Free Network

The development of the wireless sensor networks (WSNs) in the recent years is mainly due to the readily obtainable low-cost and short-range sensors. The objective of the WSN system is to both sense and transmit the real-time sense contents belonging to a particular monitoring environment for the back-end system for performing the necessary processing and analysis tasks. One of the most significant tasks of prime consideration is to ensure the safety and privacy aspects of the WSN in a wireless channel. The ultimate idea of the wireless sensor network is to preserve the limited node energy and thereby process the huge volume of data without affecting the robustness. The main objective of this work is to strengthen the robustness of the wireless sensor network that particularly relies on a scale-free type of network. The ability of the Scale-free WSNs in tolerating the random attacks efficiently have made them appear significant; on the other hand, they may be vulnerable to certain malicious attacks, that specifically targets the significant nodes in the system. This limitation has been addressed in this work by means of introducing a new modelling strategy called sequential probability ratio test (SPRT) that assists in the generation of scale-free network topologies. SPRT, a unique robustness improvising algorithm for the scale free type of WSNs, has been designed in this work and also the proposed SPRT is compared with the existing EROSE technique. The wide range of experimental results thus ensure that the introduced SPRT modelling methodology can achieves robustness and enhances the security of WSN.

Distributed Key Management to Secure IoT Wireless Sensor Networks in Smart-Agro.

With the deepening of the research and development in the field of embedded devices, the paradigm of the Internet of things (IoT) is gaining momentum. Its technology’s widespread applications increasing the number of connected devices constantly. IoT is built on sensor networks, which are enabling a new variety of solutions for applications in several fields (health, industry, defense, agrifood and agro sectors, etc.). Wireless communications are indispensable for taking full advantage of sensor networks but implies new requirements in the security and privacy of communications. Security in wireless sensor networks (WSNs) is a major challenge for extending IoT applications, in particular those related to the smart-agro. Moreover, limitations on processing capabilities of sensor nodes, and power consumption have made the encryption techniques devised for conventional networks not feasible. In such scenario, symmetric-key ciphers are preferred for key management in WSN; key distribution is therefore an issue. In this work, we provide a concrete implementation of a novel scalable group distributed key management method and a protocol for securing communications in IoT systems used in the smart agro sector, based on elliptic curve cryptography, to ensure that information exchange between layers of the IoT framework is not affected by sensor faults or intentional attacks. In this sense, each sensor node executes an initial key agreement, which is done through every member’s public information in just two rounds and uses some authenticating information that avoids external intrusions. Further rekeying operations require just a single message and provide backward and forward security.

An efficient approach for secured communication in wireless sensor networks

Wireless sensor network (WSN) have limited bandwidth, low computational functions, energy constraints. Inspite of these constraints, WSN is useful where communication happens without infrastructure support. The main concern of WSN is the security as the sensor nodes may be attacked and information may be hacked. Security of WSN should have the capability to ensure that the message received was sent by the particular sent node and not modified during transmission. WSN applications require lightweight and strong authentication mechanisms for obtaining data from unprivileged users. In wireless sensor networks, authentication is the effective method to stop unauthorized and undisrupted communication service. In order to strengthen the authenticated communication, several researchers have developed mechanisms. Some of the techniques work with identifying the attacked node or detecting injected bogus message in the network. Encryption and decryption are the popular methods of providing the security. These are based on either public-key or symmetric-key cryptosystems Many of the existing solutions have limitations in communication and computational expertise. Also, the existing mechanisms lack in providing strength and scalability of the network. In order address these issues; a polynomial based method was introduced in recent days. Key distribution is a significant aspect in key management in WSNs. The simplest method of distribution of key is by hand which was used in the days of couriers. Now a days, most distribution of keys is done automatically. The automatic distribution of keys is essential and convenient in networks that require two parties to transmit their security keys in the same communication medium. In this work, a new type of key exchange mechanism is proposed. The proposed method for authentication among sensor nodes proves to be promising as per the simulation results. The nodes which are unknown to each other setup a private however arbitrary key for the symmetric key cryptosystem.

Efficient Temporal-key Based Encryption Mechanism for WSN-ETEM

Wireless sensor networks (WSNs) are a promising technology for several industrial real-time and quotidian applications. Due to inherent limitations in WSN, security is a crucial issue. Cryptographic primitives are the fundamental components for designing security protocols to achieve security and privacy in WSN. Based on the review, it has been analyzed that the majority of security protocols for WSN are based on encryption and key distribution. The main open issue for these approaches concerns the establishment of security with an involvement of complex procedure, which presents considerable memory overheads, in contrast with the limited resources of sensor nodes. Therefore, the proposed work presents the modeling of an analytical approach for efficient encryption using temporal key management for robust security services to resists potential attacks and enables secure communication. The utilization of temporal-key mechanism in encryption operation offers additional support to routing operation in the network for secure data transmission with negligible computational overhead, thus preserving a higher level of energy savings in packet transmission operation. The validation of the proposed system performance is carried out a simulation study, which shows the effectiveness of the proposed system in terms of node remaining energy and processing time.

Intrusion detection using dynamic feature selection and fuzzy temporal decision tree classification for wireless sensor networks

Intrusion detection systems assume a noteworthy job in the provision of security in wireless Sensor networks. The existing intrusion detection systems focus only on the detection of the known types of attacks. However, it neglects to recognise the new types of attacks, which are introduced by malicious users leading to vulnerability and information loss in the network. In order to address this challenge, a new intrusion detection system, which detects the known and unknown types of attacks using an intelligent decision tree classification algorithm, has been proposed. For this purpose, a novel feature selection algorithm named dynamic recursive feature selection algorithm, which selects an optimal number of features from the data set is proposed. In addition, an intelligent fuzzy temporal decision tree algorithm is also proposed by extending the decision tree algorithm and integrated with convolution neural networks to detect the intruders effectively. The experimental analysis carried out using KDD cup data set and network trace data set demonstrates the effectiveness of this proposed approach. It proved that the false positive rate, energy consumption, and delay are reduced in the proposed work. In addition, the proposed system increases the network performance through increased packet delivery ratio.

Autoregressive integrated moving average model–based secure data aggregation for wireless sensor networks

Nodes in a wireless sensor network are normally constrained by hardware and environmental conditions and face challenges of reduced computing capabilities and system security vulnerabilities. This fact calls for special requirements for network protocol design, security assessment models, and energy-efficient algorithms. Data aggregation is an effective energy conservation technique, which removes redundant information from the data aggregated from neighbor sensor nodes. How to further improve the effectiveness of data aggregation plays an important role in improving data collection accuracy and reducing the overall network energy consumption. Unfortunately, sensor nodes are normally deployed in an open environment and thus are subject to various attacks conducted by adversaries. Consequently, data aggregation brings new challenges to wireless sensor network security. In this article, we propose a novel secure data aggregation solution based on autoregressive integrated moving average model, a time series analysis technique, to prevent private data from being learned by adversaries. We leverage the autoregressive integrated moving average model to predict the data volume in sensor nodes, and update and synchronize the model as needed. The experimental results demonstrate that our model provides accurate predictions and that, compared with competing methods, our solution achieves better security, lower computation and communication costs, and better flexibility.

Charging wireless sensor network security technology based on encryption algorithms and dynamic model

With the popularization of the Internet, the related information technology is developing faster and faster, and the scale and complexity of the network are also increasing. Wireless networks cover all aspects of life, along with it, network security issues have gradually emerged. In recent years, network security vulnerabilities have been exposed continuously, from WiFi to Bluetooth, people gradually realize the security of wireless networks. The purpose of this article is to solve the existing security problems and study the operation process of RC4 and Advanced Encryption Standard algorithms, and the improvement scheme is put forward. This article is based on the inherent media access control address filtering technology of wireless network card; a dynamic security model for wireless networks is proposed and constructed. Devices accessing the network use 802.1x authentication method and distribute and set security status values for each device, the authentication server uses Remote Authentication Dial in User Service. This article uses the method of virtual private network encryption network to provide an encryption layer for communication between devices and wireless networks, thus, the data in network transmission can be encrypted and protected. In this article, the structure and strategy of Remote Authentication Dial in User Service are changed, in order to ensure the high security of wireless network equipment in the connection process. In the testing phase of this article, we have tested the model in detail several times. Tests are divided into middleman and session interception tests. A large number of test results show that this model can improve the security of wireless network and has good performance.

Secure Mobile Agents Based Clustering Protocol using Modified PSO Algorithm

As per the studies on Wireless Sensor Network (WSN), the major concern of WSN is network lifespan and Quality of Service (QoS) improvement as the sensor nodes are having limited processing and battery capabilities. The clustering based methods delivered improved performance compared to non-clustering methods, but cluster heads (CHs) suffered from the excessive load which leads more energy consumption of sensor nodes that becomes the CH in each interval. The mobile agent’s technology solves such problems. But using mobile agent’s leads problems of data security and unreliable communications in WSN. In this paper, we proposed novel mobile specialists based clustering protocol utilizing the adjusted particle swarm optimization (PSO) algorithm called Secure Mobile Agent based Clustering using modified PSO (SMACP). To optimize the clustering performance we design modified PSO based in CH selection and cluster formation performed efficiently. To secure data communications using the mobile agents, we applied the trust evaluation scheme to evaluate each mobile agents and sensors using parameters such as residual energy, distance, and packet forwarding probability. The simulation results computed for different WSNs in terms of energy efficiency, average throughput, packet delivery ratio (PDR), also, start to finish delay. The exhibition demonstrates that SMACP outperformed the previous methods effectively.

EeTMFO/GA: a secure and energy efficient cluster head selection in wireless sensor networks

Proliferation of technologies in wireless sensor networks is grabbing huge attention across scientific community due to its vast coverage in real life applications. It has emerged as an important technology with lots of potential as it provides useful information to the end users about a target region through real time sensing. Wireless sensor networks due to their characteristics like infrastructure-less deployment, resource restricted nature introduce several issues which may affect the performance of the system. Among these issues, most challenging issues such as energy efficiency, appropriate cluster head selection, secure data delivery and network lifetime enhancement require important concern for enhancement of WSNs which is still herculean task. This paper introduces a secure and energy aware clustering algorithm named energy efficient trusted moth flame optimization and genetic algorithm based clustering algorithm (eeTMFO/GA). Selection of most deserving trustworthy head node (also known as cluster head) is done by using moth flame optimization in clustered WSN framework. In eeTMFO/GA, the fitness function is evaluated on the basis of five important parameters including direct trust metrics such as packet forwarding progress, residual energy of elected node, connected node density, average cluster distance and average delay of transmission. Simulation outcomes have shown significant improvement in energy conservation and network stability period enhancement for eeTMFO/GA in comparison to the existing clustering schemes by 60% in comparison to LEACH protocol, 56.09% when compared to HEED protocol and has shown 42.22% and 16.36% improvement in comparison to ABC and QABC protocols respectively.

Interference and Intrusion in Wireless Sensor Networks

Wireless sensor network (WSN) systems for safety-critical, space and Internet of Things applications have recently begun to adopt open standards and commercial-off-the-shelf equipment, and persistently face challenges of malicious intrusion and spectrum coexistence. These threats are explored through Monte-Carlo simulation and benchtop testing, including matched protocol interference and sophisticated, interactive intrusion attacks. The need for expanding intrusion detection via a more holistic approach, whilst simultaneously improving WSN security, is illustrated. Discussions on WSN security, vulnerabilities, and attacks are also provided.

English

English

Anomaly detection in wireless sensor network using machine learning algorithm

Security in the Wireless Sensor Network(WSNs) is an essential and a challenging task. Anomaly detection is a key challenge to ensure the security in WSN. WSNs are vulnerable to various threats which may cause the node to get damaged and produce faulty measurements. The detection of such anomalous data is required to reduce false alarms. Machine learning algorithm based detection of anomalous data becomes popular now. Most of the current machine anomaly detection algorithms run in a stationary environment and require the entire training data to be kept in the node. In this paper, we formulate an Online Locally Weighted Projection Regression (OLWPR) for anomaly detection in Wireless Sensor Network. Linear Weighted Projection Regression methods are non parametric and the current predictions are performed by local functions that use only the subset of data. So, the computation complexity is low which is one of the requirements in Wireless Sensor Network. The dimensionality reduction in LWPR is done online by Principal Component Analysis (PCA) to handle the irrelevant and redundant data in the input data. After the prediction process, the dynamic threshold value is determined by a dynamic thresholding method to find the deviations of predicted value from the actual sensed value. OLWPR attains the detection rate of 86 percentage and very low error rate of only 16%.