Biblio

Wireless Sensor networks can be composed of smart buildings, smart homes, smart grids, and smart mobility, and they can even interconnect all these fields into a large-scale smart city network. Software-Defined Networking is an ideal technology to realize Internet-of-Things (IoT) Network and WSN network requirements and to efficiently enhance the security of these networks. Software defines Networking (SDN) is used to support IoT and WSN related networking elements, additional security concerns rise, due to the elevated vulnerability of such deployments to specific types of attacks and the necessity of inter-cloud communication any IoT application would require. This work is a study of different security mechanisms available in SDN for IoT and WSN network secure communication. This work also formulates the problems when existing methods are implemented with different networks parameters.

Considering the evidence that conditions accept a considerable place in each of the structures, owing to limited assets available at each sensor center, it is a difficult problem. Vitality safety is the primary concern in many of the implementations in remote sensor hubs. This is critical as the improvement in the lifetime of the device depends primarily on restricting the usage of vitality in sensor hubs. The rationing and modification of the usage of vitality are of the most serious value in this context. In a remote sensor arrangement, the fundamental test is to schedule measurements for the least use of vitality. These classification frameworks are used to frame the classes in the structure and help efficiently use the strength that burdens out the lifespan of the network. Besides, the degree of the center was taken into account in this work considering the measurement of cluster span as an improvement to the existing methods. The crucial piece of leeway of this suggested approach on affair clustering using fuzzy logic is which can increase the lifespan of the system by reducing the problem area problem word.

Ant Colony Optimization is applied to design a suitable and shortest route between the starting node point and the end node point in the Wireless Sensor Network (WSN). In general ant colony algorithm plays a good role in path planning process that can also applied in improving the network security. Therefore to protect the network from the malicious nodes an ACO based Dynamic Key Management (ACO-DKM) scheme is proposed. The routes are diagnosed through ACO method also the actual coverage distance and pheromone updating strategy is updated simultaneously that prevents the node from continuous monitoring. Simulation analysis gives the efficiency of the proposed scheme.

With the development of wireless sensor networks (WSNs), WSNs have been widely used in various fields such as animal habitat detection, military surveillance, etc. This paper focuses on protecting the source location privacy (SLP) in WSNs. Existing algorithms perform poorly in non-uniform networks which are common in reality. In order to address the performance degradation problem of existing algorithms in non-uniform networks, this paper proposes a robust fixed path-based random routing scheme (RFRR), which guarantees the path diversity with certainty in non-uniform networks. In RFRR, the data packets are sent by selecting a routing path that is highly differentiated from each other, which effectively protects SLP and resists the backtracking attack. The experimental results show that RFRR increases the difficulty of the backtracking attack while safekeeping the balance between security and energy consumption.

It is important to ensure source location privacy (SLP) protection in safety-critical monitoring applications. Also, to achieve effective long-term monitoring, it is essential to design SLP protocols with high energy efficiency and energy balancing. Therefore, this study proposes a new phantom with angle (PwA) protocol. The PwA protocol employs dynamic routing paths which are designed to achieve SLP protection with energy efficiency and energy balancing. Analysis results reveal that the PwA protocol exhibits superior performance features to outperform existing protocols by achieving high levels of SLP protection for time petime periods. The results confirm that the PwA protocol is practical in long-term monitoring systems.riods. The results confirm that the PwA protocol is practical in long-term monitoring systems.

Wireless sensor networks (WSNs) have gained increasing popularity in ubiquitous support of sensing system services. Often, WSNs are energy-constrained and they are deployed in harsh and unattended environments. Consequently, WSNs are vulnerable to energy and environmental factors. To ensure secure and reliable operations in safety-critical monitoring WSNs, it is important to guarantee energy-efficient communications, location privacy protection, and reliability. Fake packet-based source location privacy (SLP) protocols are known to be energy-inefficient. Therefore, in this study, we investigate the impact of energy-inefficient communications on the privacy performance of the fake packet-based SLP protocols. Experiment results show that the protocols achieve short-term and less reliable SLP protection.

The main aim of the Internet of things is to improve the safety of the device through inter-Device communication (IDC). Various applications are emerging in Internet of things. Various aspects of Internet of things differ from Internet of things, especially the nodes have more velocity which causes the topology to change rapidly. The requirement of researches in the concept of Internet of things increases rapidly because Internet of things face many challenges on the security, protocols and technology. Despite the fact that the problem of organizing the interaction of IIoT devices has already attracted a lot of attention from many researchers, current research on routing in IIoT cannot effectively solve the problem of data exchange in a self-adaptive and self-organized way, because the number of connected devices is quite large. In this article, an adaptive neuro-fuzzy clustering algorithm is presented for the uniform distribution of load between interacting nodes. We synthesized fuzzy logic and neural network to balance the choice of the optimal number of cluster heads and uniform load distribution between sensors. Comparison is made with other load balancing methods in such wireless sensor networks.

Wireless Sensor Network (WSN)is a predominant technology that is widely used in many applications such as industrial sectors, defense, environment, habitat monitoring, medical fields etc., These applications are habitually delegated for observing sensitive and confidential raw data such as adversary position, movement in the battle field, location of personnel in a building, changes in environmental condition, regular medical updates from patient side to doctors or hospital control rooms etc., Security becomes inevitable in WSN and providing security is being truly intricate because of in-built nature of WSN which is assailable to attacks easily. Node involved in WSN need to route the data to the neighboring nodes wherein any attack in the node could lead to fiasco. Of late trust mechanisms have been considered to be an ideal solution that can mitigate security problems in WSN. This paper aims to investigate various existing trust-based Secure Routing (SR) protocols and mechanisms available for the wireless sensing connection. The concept of the present trust mechanism is also analyzed with respect to methodology, trust metric, pros, cons, and complexity involved. Finally, the security resiliency of various trust models against the attacks is also analyzed.

Wireless Sensor Network consists of hundreds to thousands of tiny sensor nodes deployed in the large field of the target phenomenon. Sensor nodes have advantages for its size, multifunctional, and inexpensive features; unfortunately, the resources are limited in terms of memory, computational, and in energy, especially. Network transmission between nodes and base station (BS) needs to be carefully designed to prolong the network life cycle. As the data transmission is energy consuming compared to data processing, designing sensor nodes into hierarchical network architecture is preferable because it can limit the network transmission. LEACH is one of the hierarchical network protocols known for simple and energy saving protocols. There are lots of modification made since LEACH was introduced for more energy efficient purposed. In this paper, hybridization of LEACH-C and LEACH-R and the modification have been presented for a more energy saving LEACH called LEACH-CR. Experimental result was compared with previous LEACH variant and showed to has advantages over the existing LEACH protocols in terms of energy consumption, dead/alive nodes, and the packet sent to Base Station. The result reflects that the consideration made for residual energy to select the cluster head and proximity transmission lead to a better energy consumption in the network.

In order to improve the status monitoring and management ability of wireless sensor networks, a dynamic data compression method based on grid deduplication is proposed. Grid-based sensor node spatial positioning and big data fusion method are adopted to realize dynamic feature mining of wireless sensor network data, extract feature sequence points of wireless sensor network data, reconstruct wireless sensor network data feature space by adopting spatial grid node recombination, build a statistical detection model of dynamic feature mining of wireless sensor network data by combining grid area grouping compression method, and realize embedded fuzzy control and joint feature distributed adaptive learning. The association matching degree of wireless sensor network data is analyzed. Combining fuzzy subspace compression and big data fusion clustering, the quantitative regression analysis model of wireless sensor network data is established. The time series reorganization of wireless sensor network database is realized by index table name, index column and other information. Compressed sensing method is used in linear fusion subspace to realize data compression and adaptive detection of wireless sensor network. Constraint feature points of wireless sensor network data compression are constructed, and dynamic compression and clustering processing of wireless sensor network data are realized at constraint points. Simulation results show that the feature clustering of data compression in wireless sensor networks is better and the storage space of data is reduced.

This paper presents a distributed adaptive algorithm for node-specific sound zoning in a wireless acoustic sensor and actuator network (WASAN), based on a network-wide acoustic contrast control (ACC) method. The goal of the ACC method is to simultaneously create node-specific zones with high signal power (bright zones) while minimizing power leakage in other node-specific zones (dark zones). To obtain this, a network-wide objective involving the acoustic coupling between all the loudspeakers and microphones in the WASAN is proposed where the optimal solution is based on a centralized generalized eigenvalue decomposition (GEVD). To allow for distributed processing, a gradient based GEVD algorithm is first proposed that minimizes the same objective. This algorithm can then be modified to allow for a fully distributed implementation, involving in-network summations and simple local processing. The algorithm is referred to as the distributed adaptive gradient based ACC algorithm (DAGACC). The proposed algorithm outperforms the non-cooperative distributed solution after only a few iterations and converges to the centralized solution, as illustrated by computer simulations.

Wireless Sensor Network (WSN) is considered as the backbone of Internet of Things (IoT) networks. Authentication is the most important phase that guarantees secure access to such networks but it is more critical than that in traditional Internet because the communications are established between constrained devices that could not compute heavy cryptographic primitives. In this paper, we are studying with real experimentation the efficiency of HIP Diet EXchange header (HIP DEX) protocol over IPv6 over Low Power Wireless Personal Area Networks (6LoWPAN) in IoT. The adopted application layer protocol is Constrained Application Protocol (CoAP) and as a routing protocol, the Routing Protocol for Low power and lossy networks (RPL). The evaluation concerns the total End-to-End transmission delays during the authentication process between the communicating peers regarding the processing, propagation, and queuing times' overheads results. Most importantly, we propose an efficient handshake packets' compression header, and we detailed a comparison of the above evaluation's criteria before and after the proposed compression. Obtained results are very encouraging and reinforce the efficiency of HIP DEX in IoT networks during the handshake process of constrained nodes.

A continually growing number of sensors is required for monitoring industrial processes and for continuous data acquisition from industrial plants and devices. The cabling of sensors represent a considerable effort and potential source of error, which can be avoided by using wireless sensor nodes. These wireless sensor nodes form a wireless sensor network (WSN) to efficiently transmit data to the destination. For the acceptance of WSNs in industry, it is important to build up networks with high trustworthiness. The trustworthiness of the WSN depends not only on a secure wireless communication but also on the ability to detect modifications at the wireless sensor nodes itself. This paper presents the enhancement of the WSN's trustworthiness using an optical localization system. It can be used for the preparation phase of the WSN and also during operation to track the positions of the wireless sensor nodes and detect spatial modification. The location information of the sensor nodes can also be used to rate their trustworthiness.

Secure wireless communication is essential for most industrial applications. The secure and reliable control of processes as well as the data integrity of measured values are key targets in these applications. The industrial Internet-of-Things (IIoT) tries to connect an increasing number of sensors wirelessly. The wireless sensors form wireless sensor networks (WSNs). However, wireless sensor nodes are exposed to various security threats ranging from physical modification on the device itself to remote attacks via the communication channel. It is important to secure the complete lifetime of the wireless sensor nodes and other system components. This includes the production phase, shipping, preparation phase and operational phase. This paper presents a lifetime security concept for a wireless sensor network applied in automotive test beds. In this application scenario, the wireless sensor nodes are used to capture various temperatures in an automotive unit under test. In order to indicate the current state of trustworthiness of the system, a trustworthiness indicator is implemented which is shown to the user. An evaluation of the impact of encrypted communication on power consumption shows that the increase is negligible, and can be expected to be provided by the wireless sensor node's power supply without reducing the node lifetime.

A distributed denial of service attack is a major security challenge in modern communications networks. In this article, we propose models that capture all the key performance indicators of synchronized denial of service protection mechanisms. As a result of the conducted researches, it is found out that thanks to the method of delay detection it is possible to recognize semi-open connections that are caused by synchronous flood and other attacks at an early stage. The study provides a mechanism for assessing the feasibility of introducing and changing the security system of a wireless sensor network. The proposed methodology will allow you to compare the mechanisms of combating denial of service for synchronized failures and choose the optimal protection settings in real-time.

With the improvement of scientific and technological level in China, wireless sensor network technology has been widely promoted and applied, which has now been popularized to various fields of society from military defense. Wireless sensor network combines sensor technology, communication technology and computer technology together, and has the ability of information collection, transmission and processing. In this paper, the structure of wireless sensor network and node localization technology are briefly introduced, and the key technologies of wireless sensor network development are summarized from the four aspects of energy efficiency, node localization, data fusion and network security. As a detection system of perceiving the physical world, WSN is also facing challenges while developing rapidly.

The paper addresses the issue of providing information security to wireless sensor networks using Security Information and Event Management (SIEM) methodology along with multi-agent approach. The concept of wireless sensor networks and providing their information security, including construction of SIEM system architecture, SIEM analysis methodologies and its main features, are considered. The proposed approach is to integrate SIEM system methodology with a multi-agent architecture which includes data collecting agents, coordinating agent (supervisor) and local Intrusion Detection Systems (IDSs) based on artificial immune system mechanisms. Each IDS is used as an agent that performs a primary analysis and sends information about suspicious activity to the server. The server performs correlation analysis, identifies the most significant incidents, and helps to prioritize the incident response. The presented results of computational experiments confirm the effectiveness of the proposed approach.

Source location privacy (SLP) protection ensures security of assets in monitoring wireless sensor networks (WSNs). Also, low end-to-end delay (EED) and high packet delivery ratio (PDR) guarantee high packet delivery reliability. Therefore, it is important to ensure high levels of SLP protection, low EED, and high PDR in mission-critical monitoring applications. Thus, this study proposes a new angle-based agent node routing protocol (APr) which is capable of achieving high levels of SLP protection, low EED, and high PDR. The proposed APr protocol employs multiple routing strategies to enable a dynamic agent node selection process and creation of obfuscating routing paths. Analysis results reveal that the APr protocol achieves high packet delivery reliability to outperform existing intermediate node-based protocols such as the AdrR and tree-based protocols such as the TbR. Furthermore, the APr protocol achieves significantly high levels of SLP protection to outperform the AdrR protocol.

Fake source packet routing protocols can ensure Source Location Privacy (SLP) protection. However, the protocols have demonstrated some performance limitations including high energy consumption, low packet delivery ratio (PDR), and long end-to-end delay (EED). In this study, a 2-level phantom routing protocol is proposed to address some limitations of an existing fake source packet routing protocol. The proposed protocol supplants the fake source packets with a random second level phantom node to alleviate the limitations. Analysis results confirm that the proposed protocol is capable of achieving strong SLP protection with minimized communication overhead. By removing the fake packet traffic in the network, the protocol incurs minimized energy consumption, maximized PDR, and minimized EED.

Wireless Sensor Networks promises the wireless network tools that does not require any stable infrastructure. Routing is the most important effect of network operation for the extended data rates within the network. Route discovery and route search sent the required packets from the target node source. However, good data transmission is also a threatening task in networks that provide efficient and energy-efficient routing. Various research activities focus on the topology control, source location privacy optimization and effective routing improvement in WSN. Wherein the existing security solutions both routing protocols and source location solutions disrupt the self-organizing nature of wireless sensor networks. Therefore, large overhead signatures are displayed and digitally verified by the requesting node. The cloud-based and routing based schemes have provided efficient security but there are a lot of obstacles for source data and travel path information security in the WSN network. This study is dedicated to calculate the desired number of deployments for sensor nodes in a given area once the selected metric achieves a certain level of coverage, while maintaining wireless connectivity in the network. A trusted node authentication scheme in wireless sensor network reduces the communication between nodes in a secure data transmission network, where shared cryptography is established all adjacent to the sensor node. Route discovery and retransmission increases the network overhead and increases the average end-to-end delay of the network in the conventional systems. This results in higher time complexity, communication overhead and less security of constrained sensor network resources.

The usage of K-anonymity to preserve location privacy for wireless sensor network (WSN) monitoring systems, where sensor nodes operate together to notify a server with anonymous shared positions. That k-anonymous position is a coated region with at least k people. However, we identify an attack model to show that overlapping aggregate locations remain privacy-risk because the enemy can infer certain overlapping areas with persons under k who violate the privacy requirement for anonymity. Within this paper we suggest a mutual WSN privacy protocol (REAL). Actual needs sensor nodes to arrange their sensing areas separately into a variety of non-overlapping, extremely precise anonymous aggregate positions. We also developed a state transfer framework, a locking mechanism and a time delay mechanism to address the three main REAL challenges, namely self-organisation, shared assets and high precision. We equate REAL's output with current protocols through virtual experiments. The findings demonstrate that REAL preserves the privacy of sites, offers more precise question answers and decreases connectivity and device expense.

With a storage space limit on the sensors, WSN has some drawbacks related to bandwidth and computational skills. This limited resources would reduce the amount of data transmitted across the network. For this reason, data aggregation is considered as a new process. Iterative filtration (IF) algorithms, which provide trust assessment to the various sources from which the data aggregation has been performed, are efficient in the present data aggregation algorithms. Trust assessment is done with weights from the simple average method to aggregation, which treats attack susceptibility. Iteration filter algorithms are stronger than the ordinary average, but they do not handle the current advanced attack that takes advantage of false information with many compromise nodes. Iterative filters are strengthened by an initial confidence estimate to track new and complex attacks, improving the solidity and accuracy of the IF algorithm. The new method is mainly concerned with attacks against the clusters and not against the aggregator. In this process, if an aggregator is attacked, the current system fails, and the information is eventually transmitted to the aggregator by the cluster members. This problem can be detected when both cluster members and aggregators are being targeted. It is proposed to choose an aggregator which chooses a new aggregator according to the remaining maximum energy and distance to the base station when an aggregator attack is detected. It also save time and energy compared to the current program against the corrupted aggregator node.

Data sampling is critical process for energy constrained Wireless Sensor Networks. In this article, we proposed a Predictive Data Recovery Compressive Sensing (PDR-CS) procedure for data sampling. PDR-CS samples data measurements from the monitoring field on the basis of spatial and temporal correlation and sparse measurements recovered at the Sink. Our proposed algorithm, PDR-CS extends the iterative re-weighted -ℓ1(IRW - ℓ1) minimization and regularization on the top of Spatio-temporal compressibility for enhancing accuracy of signal recovery and reducing the energy consumption. The simulation study shows that from the less number of samples are enough to recover the signal. And also compared with the other compressive sensing procedures, PDR-CS works with less time.

Wireless Sensor Network (WSN) is a heterogeneous type of network consisting of scattered sensor nodes and working together for data collection, processing, and transmission functions[1], [2]. Because WSN is widely used in vital matters, aspects of its security must also be considered. There are many types of attacks that might be carried out to disrupt WSN networks. The methods of attack that exist in WSN include jamming attack, tampering, Sybil attack, wormhole attack, hello flood attack, and, blackhole attack[3]. Blackhole attacks are one of the most dangerous attacks on WSN networks. Enhanced Check Agent method is designed to detect black hole attacks by sending a checking agent to record nodes that are considered black okay. The implementation will be tested right on a wireless sensor network using ZigBee technology. Network topology uses a mesh where each node can have more than one routing table[4]. The Enhanced Check Agent method can increase throughput to 100 percent.

This paper proposes an infrared sensor human target locating system for the Internet of Things. In this design, the wireless sensor network is designed and developed to detect human targets by using 6LoWPAN protocol and pyroelectric infrared (PIR) sensors. Based on the detection data acquired by multiple sensor nodes, K-means++ clustering algorithm combined with cost function is applied to complete human target location in a 10m×10m detection area. The experimental results indicate the human locating system works well and the user can view the location information on the terminal devices.