scholarly journals Selfish node Detection Based on Fuzzy Logic and Harris Hawks Optimization Algorithm in IoT Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Abbas Akhbari ◽  
Ali Ghaffari
Keyword(s):  
Fuzzy Logic ◽  
False Positive Rate ◽  
Hybrid Approach ◽  
The Internet ◽  
Selfish Nodes ◽  
Selfish Node ◽  
Third Stage ◽  
Positive Rate ◽  
Set Up ◽  
The Internet Of Things

The Internet of things describes a network of physical things for example, “things” that are connected with the sensors, software, and other technologies to connect and exchange data with other devices and systems via the Internet. In this type of network, the nodes communicate with each other because of the low radio range by step by step with the help of each other until they reach their destination, but there are nodes in the network that do not cooperate with other nodes in the network, which are called “selfish nodes”. In this paper, we try to detect selfish nodes based on a hybrid approach to increase the performance of our network. The proposed method consists of three stages: in the first stage, with the help of the Harris hawk operation, we try to set up the cluster and select head cluster; in the second stage, the sink investigates the existence or nonexistence of selfish nodes in the network by considering the general parameters of the network; and in the event of a selfish node in the network, it informs the head clusters to check the cluster members and recognize the selfish node. In the third stage, with the help of fuzzy logic, the amount of reputation of each of the nodes has been realized, and finally, with the help of fusion of head clusters and fuzzy logic, each node is decided to be cooperate or selfish nodes, and in case of head clusters and fuzzy logic in some cases, the opportunity node will be reestablished to participate in network activities otherwise the node will be isolated. The results show that the accuracy of selfish node detection has increased by an average of 12% and the false positive rate is 8% in comparison to existing methods.

scholarly journals Evaluation of the Genotypic Prediction of HIV-1 Coreceptor Use versus a Phenotypic Assay and Correlation with the Virological Response to Maraviroc: the ANRS GenoTropism Study

2010 ◽  
Vol 54 (8) ◽  
pp. 3335-3340 ◽  
Author(s):  
Patricia Recordon-Pinson ◽  
Cathia Soulié ◽  
Philippe Flandre ◽  
Diane Descamps ◽  
Mouna Lazrek ◽  
...  
Keyword(s):  
Virological Response ◽  
False Positive Rate ◽  
Baseline Viral Load ◽  
Phenotypic Assay ◽  
Sensitivity Score ◽  
Positive Rate ◽  
Set Up ◽  
Genotypic Sensitivity Score ◽  
The Relationship ◽  
Hiv 1

ABSTRACT Genotypic algorithms for prediction of HIV-1 coreceptor usage need to be evaluated in a clinical setting. We aimed at studying (i) the correlation of genotypic prediction of coreceptor use in comparison with a phenotypic assay and (ii) the relationship between genotypic prediction of coreceptor use at baseline and the virological response (VR) to a therapy including maraviroc (MVC). Antiretroviral-experienced patients were included in the MVC Expanded Access Program if they had an R5 screening result with Trofile (Monogram Biosciences). V3 loop sequences were determined at screening, and coreceptor use was predicted using 13 genotypic algorithms or combinations of algorithms. Genotypic predictions were compared to Trofile; dual or mixed (D/M) variants were considered as X4 variants. Both genotypic and phenotypic results were obtained for 189 patients at screening, with 54 isolates scored as X4 or D/M and 135 scored as R5 with Trofile. The highest sensitivity (59.3%) for detection of X4 was obtained with the Geno2pheno algorithm, with a false-positive rate set up at 10% (Geno2pheno10). In the 112 patients receiving MVC, a plasma viral RNA load of <50 copies/ml was obtained in 68% of cases at month 6. In multivariate analysis, the prediction of the X4 genotype at baseline with the Geno2pheno10 algorithm including baseline viral load and CD4 nadir was independently associated with a worse VR at months 1 and 3. The baseline weighted genotypic sensitivity score was associated with VR at month 6. There were strong arguments in favor of using genotypic coreceptor use assays for determining which patients would respond to CCR5 antagonist.

scholarly journals What Is the Fastest Way to Connect Stations to a Wi-Fi HaLow Network?

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2744 ◽  
Author(s):  
Dmitry Bankov ◽  
Evgeny Khorov ◽  
Andrey Lyakhov ◽  
Ekaterina Stepanova ◽  
Le Tian ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Optimal Algorithm ◽  
Access Point ◽  
The Internet ◽  
Shared Channel ◽  
Set Up ◽  
The Internet Of Things ◽  
Self Adaptive

Wi-Fi HaLow is an adaptation of the widespread Wi-Fi technology for the Internet of Things scenarios. Such scenarios often involve numerous wireless stations connected to a shared channel, and contention for the channel significantly affects the performance in such networks. Wi-Fi HaLow contains numerous solutions aimed at handling the contention between stations, two of which, namely, the Centralized Authentication Control (CAC) and the Distributed Authentication Control (DAC), address the contention reduction during the link set-up process. The link set-up process is special because the access point knows nothing of the connecting stations and its means of control of these stations are very limited. While DAC is self-adaptive, CAC does require an algorithm to dynamically control its parameters. Being just a framework, the Wi-Fi HaLow standard neither specifies such an algorithm nor recommends which protocol, CAC or DAC, is more suitable in a given situation. In this paper, we solve both issues by developing a novel robust close-to-optimal algorithm for CAC and compare CAC and DAC in a vast set of experiments.

scholarly journals Cloud Data Security Protection Technique using Internet on Things

2019 ◽  
Vol 9 (1) ◽  
pp. 2620-2623
Keyword(s):  
Internet Of Things ◽  
Data Security ◽  
Focal Point ◽  
The Internet ◽  
Application Layer ◽  
Cloud Data ◽  
Safety Concerns ◽  
Set Up ◽  
The Internet Of Things ◽  
The Web

The internet of things is turning into an appealing framework worldview to acknowledge inter-connections throughout corporeal, digital as well as communal gaps. Through the connections amid the IoT, safety concerns befall important, along with it is huge to set up improved resolutions for safety protections. The IoT apparition of unlock data sharing is expert through using cloud registering concepts. Since IoT is depends on the web, safety concerns of internet will similarly emerge in IoT as well as IoT enclose three layers for example perception, transportation and application layers. The safety concerns, modernism along with solution recognized by the application layer are conversed about in this Paper. The principle focal point of this examination work is on Data Security Protection procedure for application layer

Latin America seeks improved cybersecurity governance

2019 ◽  
Keyword(s):  
Latin American ◽  
The Internet ◽  
Private Institutions ◽  
Public And Private ◽  
Content Type ◽  
Set Up ◽  
The Military ◽  
Policy Communities ◽  
Latin American Countries ◽  
The Internet Of Things

Subject Cybersecurity outlook. Significance Latin American countries including Brazil, Argentina, Colombia, Chile, Mexico and Uruguay have set up novel policy communities involving various public and private institutions charged with securing cyberspace. Impacts Regional countries are largely unprepared to enforce a militarised deterrence response. Cyber tensions could flare due to old rivalries and the fact that the military is heavily steering cybersecurity. Cybersecurity shortcomings threaten development of the Internet of Things in the region.

scholarly journals Blockchain-based Smart Waste Management System

2019 ◽  
Vol 8 (11S) ◽  
pp. 1030-1034
Keyword(s):  
Waste Management ◽  
Management System ◽  
The Internet ◽  
Smart Contracts ◽  
Waste Management System ◽  
Digital Currency ◽  
Performance And Evaluation ◽  
Set Up ◽  
The Internet Of Things ◽  
Ways Of Life

Blockchain generation and the Internet of Things are two of the most famous technology these days. IoT is an interconnection of devices which have the usefulness to detect, degree, a strategy the country of natural markers just as themselves and incite dependent on the enter outfitted. It can help make astute arrangements which could enhance the best of ways of life of individuals. In like manner, blockchain is dispensed database structures that guarantee an extreme dimension of wellbeing and accessibility of actualities with least exchange overhead. In this proposal, we endeavor to convey together that two innovation to grow a Smart Waste Management System (SWMS). The SWMS is weight-based for example Clients need to pay for the utilization of administrations as indicated by the measure of waste they produce. Installments are made the use of a custom digital currency controlled by utilizing Smart Contracts and the total SWMS can be supported with the guide of a DAO through a totally computerized, observably secure strategy. Blockchain can help bring down the infiltration and supplier esteem which might be particularly valuable to developing countries in which governments are not exceptionally inventive. This paper tries to set up an evidence of concept thru size of performance and evaluation of the applicability of this type of device.

scholarly journals Selfish Node detection based on GA and Learning Automata in IoT

2020 ◽  
Author(s):  
Solmaz Nobahary ◽  
Hossein Gharaee Garakani ◽  
Ahmad Khademzadeh ◽  
Amir Masoud Rahmani
Keyword(s):  
Genetic Algorithm ◽  
Clustering Algorithm ◽  
Fitness Function ◽  
False Positive Rate ◽  
Learning Automata ◽  
Data Packet ◽  
Detection Accuracy ◽  
Second Phase ◽  
Selfish Nodes ◽  
Selfish Node

Abstract It is critical to increasing the network throughput on the internet of things with short-range nodes. Nodes prevent to cooperate with other nodes in the network are known as selfish nodes. Previous studies have done on the selfish nodes detection that leads to increase throughput and reduce the end to end delay. The proposed method for discovering the selfish node is based on genetic algorithm and learning automata. It consists of three phases of setup and clustering, the best routing selection based on genetic algorithm, and finally, the learning and update phase. For appropriate network performance, the clustering algorithm implemented in the first phase. Nodes are working together to send the data packet to the destination in the second phase, and the neighbor node selected for forwarding the data packet in which that node has a high value of fitness function, among others. In the third phase, each node monitors the performance of its neighbor nodes in forwarding the data packet and uses the learning automata system to identify the selfish nodes. By preventing to cooperate selfish nodes and decreasing the probability selection of selfish nodes, it increases the throughput in the network. The results of the simulation show that the detection accuracy of selfish nodes in comparison with the existing methods average 12%, and the false positive rate has decreased by 5%.

scholarly journals Blockchains: Improve the Scalability and Efficiency of Conventional Blockchain by Providing a Lightweight Block Mining and Communication Algorithm

2020 ◽  
Vol 25 (6) ◽  
pp. 737-745
Author(s):  
Subba Rao Peram ◽  
Premamayudu Bulla
Keyword(s):  
Internet Of Things ◽  
Smart City ◽  
Smart Cities ◽  
Hybrid Approach ◽  
Security And Privacy ◽  
Public Key ◽  
The Internet ◽  
Byzantine Fault Tolerance ◽  
Complex Issue ◽  
The Internet Of Things

To provide secure and reliable services using the internet of things (IoT) in the smart cities/villages is a challenging and complex issue. A high throughput and resilient services are required to process vast data generated by the smart city/villages that felicitates to run the applications of smart city. To provide security and privacy a scalable blockchain (BC) mechanism is a necessity to integrate the scalable ledger and transactions limit in the BC. In this paper, we investigated the available solutions to improve its scalability and efficiency. However, most of the algorithms are not providing the better solution to achieve scalability for the smart city data. Here, proposed and implemented a hybrid approach to improve the scalability and rate of transactions on BC using practical Byzantine fault tolerance and decentralized public key algorithms. The proposed Normachain is compares our results with the existing model. The results show that the transaction rate got improved by 6.43% and supervision results got improved by 17.78%.

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