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.

From an information-theoretic standpoint, the intrusion detection process can be examined. Given the IDS output(alarm data), we should have less uncertainty regarding the input (event data). We propose the Capability of Intrusion Detection (CID) measure, which is simply the ratio of mutual information between IDS input and output, and the input of entropy. CID has the desirable properties of (1) naturally accounting for all important aspects of detection capability, such as true positive rate, false positive rate, positive predictive value, negative predictive value, and base rate, (2) objectively providing an intrinsic measure of intrusion detection capability, and (3) being sensitive to IDS operation parameters. When finetuning an IDS, we believe that CID is the best performance metric to use. In terms of the IDS’ inherent ability to classify input data, the so obtained operation point is the best that it can achieve.

At present, the research on the network security problem of underwater wireless sensors is still few, and since the underwater environment is exposed, passive security defense technology is not enough to deal with unknown security threats. Aiming at this problem, this paper proposes an offensive and defensive game model from the finite rationality of the network attack and defense sides, combined with evolutionary game theory. The replicated dynamic equation is introduced to analyze the evolution trend of strategies under different circumstances, and the selection algorithm of optimal strategy is designed, which verifies the effectiveness of this model through simulation and provides guidance for active defense technology.

Rational and smart decision making by means of strategic interaction and mathematical modelling is the key aspect of Game theory. Security games based on game theory are used extensively in cyberspace for various levels of security. The contemporary security issues can be modelled and analyzed using game theory as a robust mathematical framework. The attackers, defenders and the adversarial as well as defensive interactions can be captured using game theory. The security games equilibrium evaluation can help understand the attackers' strategies and potential threats at a deeper level for efficient defense. Wireless sensor network (WSN) designs are greatly benefitted by game theory. A deep learning adversarial network algorithm is used in combination with game theory enabling energy efficiency, optimal data delivery and security in a WSN. The trade-off between energy resource utilization and security is balanced using this technique.

The WSN nodes are arranged uniformly or randomly on the area of need for gathering the required data. The admin utilizes wireless broadband networks to connect to the Internet and acquire the required data from the base station (BS). However, these sensor nodes play a significant role in a variety of professional and industrial domains, but some of the concerns stop the growth of WSN, such as memory, transmission, battery power and processing power. The most significant issue with these restrictions is to increase the energy efficiency for WSN with rapid and trustworthy data transfer. In this designed model, the sensor nodes are clustered using the FCM (Fuzzy C-Means) clustering algorithm with the Reptile Search Optimization (RSO) for finding the centre of the cluster. The cluster head is determined by using African vulture optimization (AVO). For selecting the path of data transmission from the cluster head to the base station, the adaptive relay nodes are selected using the Fuzzy rule. These data from the base station are given to the server with a DNA cryptography encryption algorithm for secure data transmission. The performance of the designed model is evaluated with specific parameters such as average residual energy, throughput, end-to-end delay, information loss and execution time for a secure and energy-efficient routing protocol. These evaluated values for the proposed model are 0.91 %, 1.17Mbps, 1.76 ms, 0.14 % and 0.225 s respectively. Thus, the resultant values of the proposed model show that the designed clustering-based routing protocol using FCM-RSOA and DNA cryptography for smart building performs better compared to the existing techniques.

Currently, air pollution is still a problem that requires special attention, especially in big cities. Air pollution can come from motor vehicle fumes, factory smoke or other particles. To overcome these problems, a system is made that can monitor environmental conditions in order to know the good and bad of air quality in an environment and is expected to be a solution to reduce air pollution that occurs. The system created will utilize the Wireless Sensor Network (WSN) combined with Waspmote Smart Environment PRO, so that later data will be obtained in the form of temperature, humidity, CO levels and CO2 levels. From the sensor data that has been processed on Waspmote, it will then be used as input for data processing using a fuzzy algorithm. The classification obtained from sensor data processing using fuzzy to monitor environmental conditions there are 5 classifications, namely Very Good, Good, Average, Bad and Dangerous. Later the data that has been collected will be distributed to Meshlium as a gateway and will be stored in the database. The process of sending information between one party to another needs to pay attention to the confidentiality of data and information. The final result of the implementation of this research is that the system is able to classify values using fuzzy algorithms and is able to secure text data that will be sent to the database via Meshlium, and is able to display data sent to the website in real time.

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.

In Wireless Sensor Networks (WSNs), energy and security are two critical concerns that must be addressed. Because of the scarcity of energy, several security measures are restricted. For secure data routing in WSN, it becomes vital to identify insider packet drop attacks. The trust mechanism is an effective strategy for detecting this assault. Each node in this system validates the trustworthiness of its neighbors before transmitting packets, ensuring that only trust-worthy nodes get packets. With such a trust-aware scheme, however, there is a risk of false alarm. This work develops an adaptive trust computation model (TCM)which is implemented in our already proposed Chimp Optimization Algorithm-based Energy-Aware Secure Routing Protocol (COA-EASRP) for WSN. The proposed technique computes the optimal path using the hybrid combination of COA-EASRP and AODV as well as TCM is used to indicate false alarms in detecting selfish nodes. Our Proposed approach provides the series of Simulation outputs carried out based on various parameters

With the ubiquitous advancement in smart medical devices and systems, the potential of Remote Patient Monitoring (RPM) network is evolving in modern healthcare systems. The medical professionals (doctors, nurses, or medical experts) can access vitals and sensitive physiological information about the patients and provide proper treatment to improve the quality of life through the RPM network. However, the wireless nature of communication in the RPM network makes it challenging to design an efficient mechanism for secure communication. Many authentication schemes have been proposed in recent years to ensure the security of the RPM network. Pseudonym, digital signature, and Authenticated Key Exchange (AKE) protocols are used for the Internet of Medical Things (IoMT) to develop secure authorization and privacy-preserving communication. However, traditional authentication protocols face overhead challenges due to maintaining a large set of key-pairs or pseudonyms results on the hospital cloud server. In this research work, we identify this research gap and propose a novel secure and efficient privacy-preserving authentication scheme using cuckoo filters for the RPM network. The use of cuckoo filters in our proposed scheme provides an efficient way for mutual anonymous authentication and a secret shared key establishment process between medical professionals and patients. Moreover, we identify the misbehaving sensor nodes using a correlation-based anomaly detection model to establish secure communication. The security analysis and formal security validation using SPAN and AVISPA tools show the robustness of our proposed scheme against message modification attacks, replay attacks, and man-in-the-middle attacks.

Data streaming over a wireless network such as Wireless Sensor Networks, where wireless terminals (like PDAs, mobile phones, palmtops) access in data conferencing system, new challenges will be brought about. goal for this paper is to propose a high-speed lightweight encryption (HSLE) for low computational capability controller of WSN, HSLE scheme which reduces latency overhead by modifying existing approaches in order to encrypting data using a probabilistic encryption of data blocks. Proposed work is also useful when we communicate our confidential data on WSN or IoT it should be secure, we just have to save an encrypted data on cloud servers. proposed work is a new key-based algorithm and uses HSLE encryption instead for high end AES. Proposed methods cause significant speed enhancement for data encryption with similar security, in addition, it is best suited in order to communication between hand-held devices such as mobile phones, palmtops etc. algorithm may be used between sites where processing capacity and battery power are limited and efficient encryption is main necessity. This work is implemented on MATLAB and a wireless sensor network of maximum 100 nodes developed for testing the proposed network node encryption system, the time delay observed for the communication in 100 nodes WSN is less in compare with the other available works.

Wireless sensor networks are used in many areas such as war field surveillance, monitoring of patient, controlling traffic, environmental and building surveillance. Wireless technology, on the other hand, brings a load of new threats with it. Because WSNs communicate across radio frequencies, they are more susceptible to interference than wired networks. The authors of this research look at the goals of WSNs in terms of security as well as DDOS attacks. The majority of techniques are available for detecting DDOS attacks in WSNs. These alternatives, on the other hand, stop the assault after it has begun, resulting in data loss and wasting limited sensor node resources. The study finishes with a new method for detecting the UDP Reflection Amplification Attack in WSN, as well as instructions on how to use it and how to deal with the case.

Considering the evolution of technology, the need to secure data is growing fast. When we turn our attention to the healthcare field, securing data and assuring privacy are critical conditions that must be accomplished. The information is sensitive and confidential, and the exchange rate is very fast. Over the years, the healthcare domain has gradually seen a growth of interest regarding the interconnectivity of different processes to optimize and improve the services that are provided. Therefore, we need intelligent complex systems that can collect and transport sensitive data in a secure way. These systems are called cyber-physical systems. In healthcare domain, these complex systems are named medical cyber physical systems. The paper presents a brief description of the above-mentioned intelligent systems. Then, we focus on wireless sensor networks and the issues and challenges that occur in securing sensitive data and what improvements we propose on this subject. In this paper we tried to provide a detailed overview about cyber-physical systems, medical cyber-physical systems, wireless sensor networks and the security issues that can appear.

The amount of information that is shared regularly has increased as a direct result of the rapid development of network administrators, Web of Things-related devices, and online users. Cybercriminals constantly work to gain access to the data that is stored and transferred online in order to accomplish their objectives, whether those objectives are to sell the data on the dark web or to commit another type of crime. After conducting a thorough writing analysis of the causes and problems that arise with wireless networks’ security and privacy, it was discovered that there are a number of factors that can make the networks unpredictable, particularly those that revolve around cybercriminals’ evolving skills and the lack of significant bodies’ efforts to combat them. It was observed. Wireless networks have a built-in security flaw that renders them more defenceless against attack than their wired counterparts. Additionally, problems arise in networks with hub mobility and dynamic network geography. Additionally, inconsistent availability poses unanticipated problems, whether it is accomplished through mobility or by sporadic hub slumber. In addition, it is difficult, if not impossible, to implement recently developed security measures due to the limited resources of individual hubs. Large-scale problems that arise in relation to wireless networks and flexible processing are examined by the Wireless Correspondence Network Security and Privacy research project. A few aspects of security that are taken into consideration include confirmation, access control and approval, non-disavowal, privacy and secrecy, respectability, and inspection. Any good or service should be able to protect a client’s personal information. an approach that emphasises quality, implements strategy, and uses a poll as a research tool for IT and public sector employees. This strategy reflects a higher level of precision in IT faculties.

There has been a significant rise in the use of wireless sensor networks (WSNs) in the past few years. It is evident that WSNs operate in unlicensed spectrum bands [1]. But due to the increasing usage in unlicensed spectrum band this band is getting overcrowded. The recent development of cognitive radio technology [2, 3] has made possible the utilization of licensed spectrum band in an opportunistic manner. This paper studies an introduction to Cognitive Radio Technology, Cognitive Radio Wireless Sensor Networks, its Advantages & Challenges, Cognitive Radio Technology Applications and a comparative analysis of node clustering techniques in CWSN.

Recent years have witnessed impressive advances in technology which led to the rapid growth of the Internet of Things (IoT) and Wireless Sensor Networks (WSNs) using numerous low-powered devices with a huge number of actuators and sensors. These devices gather and exchange data over the internet and generate enormous amounts of data needed to be secured. Although traditional cryptography provides an efficient means of addressing device and communication confidentiality, integrity, and authenticity issues, it may not be appropriate for very resource-constrained systems, particularly for end-nodes such as a simply connected sensor. Thus, there is an ascent need to use lightweight cryptography (LWC) providing the needed level of security with less complexity, area and energy overhead. In this paper, four lightweight cryptographic algorithms called PRESENT, LED, Piccolo, and SPARX were implemented over a Contiki-based IoT operating system, dedicated for IoT platforms, and assessed regarding RAM and ROM usage, power and energy consumption, and CPU cycles number. The Cooja network simulator is used in this study to determine the best lightweight algorithms to use in IoT applications utilizing wireless sensor networks technology.

The design of efficient and secure cryptographic algorithms is a fundamental problem of cryptography. Due to the tight cost and constrained resources devices such as Radio-Frequency IDentification (RFID), wireless sensors, smart cards, health-care devices, lightweight cryptography has received a great deal of attention. Recent research mainly focused on designing optimized cryptographic algorithms which trade offs between security performance, time consuming, energy consumption and cost. In this paper, we present two chaotic stream ciphers based on chaos and we report the results of a comparative performance evaluation study. Compared to other crypto-systems of the literature, we demonstrate that our designed stream ciphers are suitable for practical secure applications of the Internet of Things (IoT) in a constrained resource environment.

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.

Based on the campus wireless IPv6 network system, using WiFi contactless sensing and positioning technology and action recognition technology, this paper designs a new campus security early warning system. The characteristic is that there is no need to add new monitoring equipment. As long as it is the location covered by the wireless IPv6 network, personnel quantity statistics and personnel body action status display can be realized. It plays an effective monitoring supplement to the places that cannot be covered by video surveillance in the past, and can effectively prevent campus violence or other emergencies.

Wireless Sensor Networks (WSN) have assisted applications of multi-agent system. Abundant sensor nodes, densely distributed around a base station (BS), collect data and transmit to BS node for data analysis. The concept of cluster has been emerged as the efficient communication structure in resource-constrained environment. However, the security still remains a major concern due to the vulnerability of sensor nodes. In this paper, we propose a percolation-based secure routing protocol. We leverage the trust score composed of three indexes to select cluster heads (CH) for unevenly distributed clusters. By considering the reliability, centrality and stability, legitimate nodes with social trust and adequate energy are chosen to provide relay service. Moreover, we design a multi-path inter-cluster routing protocol to construct CH chains for directed inter-cluster data transmission based on the percolation. And the measurement of transit score for on-path CH nodes contributes to load balancing and security. Our simulation results show that our protocol is able to guarantee the security to improve the delivery ratio and packets delay.

Satisfying the growing demand for electricity is a huge challenge for electricity providers without a robust and good infrastructure. For effective electricity management, the infrastructure has to be strengthened from the generation stage to the transmission and distribution stages. In the current electrical infrastructure, the evolution of smart grids provides a significant solution to the problems that exist in the conventional system. Enhanced management visibility and better monitoring and control are achieved by the integration of wireless sensor network technology in communication systems. However, to implement these solutions in the existing grids, the infrastructural constraints impose a major challenge. Along with the choice of technology, it is also crucial to avoid exorbitant implementation costs. This paper presents a self-stabilizing hierarchical algorithm for the existing electrical network. Neighborhood Area Networks (NAN) and Home Area Networks (HAN) layers are used in the proposed architecture. The Home Node (HN), Simple Node (SN) and Cluster Head (CH) are the three types of nodes used in the model. Fraudulent users in the system are identified efficiently using the proposed model based on the observations made through simulation on OMNeT++ simulator.

For some countries around the world, meeting demand is a serious concern. Power supply market is increasingly increasing, posing a big challenge for various countries throughout the world. The increasing expansion in the market for power needs upgrading system dependability to increase the smart grid's resilience. This smart electric grid has a sensor that analyses grid power availability and sends regular updates to the organisation. The internet is currently being utilized to monitor processes and place orders for running variables from faraway places. A large number of scanners have been used to activate electrical equipment for domestic robotics for a long period in the last several days. Conversely, if it is not correctly implemented, it will have a negative impact on cost-effectiveness as well as productivity. For something like a long time, home automation has relied on a large number of sensor nodes to control electrical equipment. Since there are so many detectors, this isn't cost-effective. In this article, develop and accept a wireless communication component and a management system suitable for managing independent efficient network units from voltage rises and voltage control technologies in simultaneous analyzing system reliability in this study. This research paper has considered secondary method to collect relevant and in-depth data related to the wireless sensor network and its usage in smart grid monitoring.

Traditional power consumption management systems are not showing enough reliability and thus, smart grid technology has been introduced to reduce the excess power wastages. In the context of smart grid systems, network communication is another term that is used for developing the network between the users and the load profiles. Cloud computing and clustering are also executed for efficient power management. Based on the facts, this research is going to identify wireless network communication systems to monitor and control smart grid power consumption. Primary survey-based research has been carried out with 62 individuals who worked in the smart grid system, tracked, monitored and controlled the power consumptions using WSN technology. The survey was conducted online where the respondents provided their opinions via a google survey form. The responses were collected and analyzed on Microsoft Excel. Results show that hybrid commuting of cloud and edge computing technology is more advantageous than individual computing. Respondents agreed that deep learning techniques will be more beneficial to analyze load profiles than machine learning techniques. Lastly, the study has explained the advantages and challenges of using smart grid network communication systems. Apart from the findings from primary research, secondary journal articles were also observed to emphasize the research findings.

In order to solve the problem of high data collision probability, high access delay and high-power consumption in random access process of power Internet of Things, an access scheme for large-scale micro-power wireless sensors based on slot-scheduling and hybrid mode is presented. This scheme divides time into different slots and designs a slot-scheduling algorithm according to network workload and power consumption. Sensors with different service priorities are arranged in different time slots for competitive access, using appropriate random-access mechanism. And rationally arrange the number of time slots and competing end-devices in different time slots. This scheme is able to meet the timeliness requirements of different services and reduce the overall network power consumption when dealing with random access scenarios of large-scale micro-power wireless sensor network. Based on the simulation results of actual scenarios, this access scheme can effectively reduce the overall power consumption of the network, and the high priority services can meet the timeliness requirements on the premise of lower power consumption, while the low priority services can further reduce power consumption.

Simulations have gained paramount importance in terms of software development for wireless sensor networks and have been a vital focus of the scientific community in this decade to provide efficient, secure, and safe communication in smart cities. Network Simulators are widely used for the development of safe and secure communication architectures in smart city. Therefore, in this technical survey report, we have conducted experimental comparisons among ten different simulation environments that can be used to simulate smart-city operations. We comprehensively analyze and compare simulators COOJA, NS-2 with framework Mannasim, NS-3, OMNeT++ with framework Castalia, WSNet, TOSSIM, J-Sim, GloMoSim, SENSE, and Avrora. These simulators have been run eight times each and comparison among them is critically scrutinized. The main objective behind this research paper is to assist developers and researchers in selecting the appropriate simulator against the scenario to provide safe and secure wired and wireless networks. In addition, we have discussed the supportive simulation environments, functions, and operating modes, wireless channel models, energy consumption models, physical, MAC, and network-layer protocols in detail. The selection of these simulation frameworks is based on features, literature, and important characteristics. Lastly, we conclude our work by providing a detailed comparison and describing the pros and cons of each simulator.

This paper focuses on the system on wireless sensor networks. The system is linear and the time of the system is discrete as well as variable, which named discrete-time linear time-varying systems (DLTVS). DLTVS are vulnerable to network attacks when exchanging information between sensors in the network, as well as putting their security at risk. A DLTVS with privacy-preserving is designed for this purpose. A set-membership estimator is designed by adding privacy noise obeying the Laplace distribution to state at the initial moment. Simultaneously, the differential privacy of the system is analyzed. On this basis, the real state of the system and the existence form of the estimator for the desired distribution are analyzed. Finally, simulation examples are given, which prove that the model after adding differential privacy can obtain accurate estimates and ensure the security of the system state.