Journal of Intelligent Systems and Internet of Things最新文献

Computer Network Design for the teaching area of the Elvira Cape library Elvira Cape图书馆教学区计算机网络设计

Journal of Intelligent Systems and Internet of Things Pub Date : 2021-10-01 DOI: 10.54216/jisiot.050101

Yackelyn Dayanys Domínguez Izquierdo

引用次数: 7

Intelligent system for IoT botnet detection using SVM and PSO optimization 基于支持向量机和粒子群优化的物联网僵尸网络智能检测系统

Journal of Intelligent Systems and Internet of Things Pub Date : 2021-09-17 DOI: 10.54216/jisiot.030203

M. A. Salam

{"title":"Intelligent system for IoT botnet detection using SVM and PSO optimization","authors":"M. A. Salam","doi":"10.54216/jisiot.030203","DOIUrl":"https://doi.org/10.54216/jisiot.030203","url":null,"abstract":"Botnet attacks involving Internet-of-Things (IoT) devices have skyrocketed in recent years due to the proliferation of internet IoT devices that can be readily infiltrated. The botnet is a common threat, exploiting the absence of basic IoT security technologies and can perform several DDoS attacks. Existing IoT botnet detection methods still have issues, such as relying on labeled data, not being validated with newer botnets, and using very complex machine learning algorithms, making the development of new methods to detect compromised IoT devices urgent to reduce the negative implications of these IoT botnets. Due to the vast amount of normal data accessible, anomaly detection algorithms seem to promise for identifying botnet attacks on the Internet of Things (IoT). For anomaly detection, the One-Class Support vector machine is a strong method (ONE-SVM). Many aspects influence the classification outcomes of the ONE-SVM technique, like that of the subset of features utilized for training the ONE-SVM model, hyperparameters of the kernel. An evolutionary IoT botnet detection algorithm is described in this paper. Particle Swarm Optimization technique (PSO) is used to tune the hyperparameters of the ONE-SVM to detect IoT botnet assaults launched from hacked IoT devices. A new version of a real benchmark dataset is used to evaluate the proposed method's performance using traditional anomaly detection evaluation measures. This technique exceeds all existing algorithms in terms of false positive, true positive and rates, and G-mean for all IoT device categories, according to testing results. It also achieves the shortest detection time despite lowering the number of picked features by a significant amount.","PeriodicalId":122556,"journal":{"name":"Journal of Intelligent Systems and Internet of Things","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132219542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

A comparative study on Internet of Things (IoT): Frameworks, Tools, Applications and Future directions 物联网比较研究:框架、工具、应用与未来方向

Journal of Intelligent Systems and Internet of Things Pub Date : 2021-07-15 DOI: 10.5281/ZENODO.3376687

Mona Mohamed

引用次数: 25

ERP Implementation Road Map for Small and Medium Size Enterprises (SMEs) 中小型企业ERP实施路线图

Journal of Intelligent Systems and Internet of Things Pub Date : 2021-06-16 DOI: 10.5281/ZENODO.4554347

A. N. Zaied, S. Mohmed

引用次数: 5

Hybrid Machine Learning Model for Rainfall Forecasting 降雨预报的混合机器学习模型

Journal of Intelligent Systems and Internet of Things Pub Date : 2021-05-19 DOI: 10.5281/ZENODO.3376685

Hatem Abdel-Kader, M. A. Salam, Mona Mohamed

引用次数: 18

Improving the Security and Authentication of the Cloud with IoT using Hybrid Optimization Based Quantum Hash Function 利用基于混合优化的量子哈希函数提高物联网云的安全性和身份验证

Journal of Intelligent Systems and Internet of Things Pub Date : 2020-12-10 DOI: 10.5281/ZENODO.3689761

K. Shankar

{"title":"Improving the Security and Authentication of the Cloud with IoT using Hybrid Optimization Based Quantum Hash Function","authors":"K. Shankar","doi":"10.5281/ZENODO.3689761","DOIUrl":"https://doi.org/10.5281/ZENODO.3689761","url":null,"abstract":"The security with the protection of IoT is to stay a consequential test, for the most part, because of the huge scale and dispersed nature of IoT systems. A cloud server brings wide pertinence of IoT in numerous businesses just as Government parts. Be that as it may, the security concerns, for example, verification and information protection of these gadgets assume a key job in fruitful coordination of two innovations. To build the security here, a quantum hash work system and hybrid cuckoo search-Artificial Bee Colony algorithm is displayed. A quantum hash work has been presented as an amazing system for secure correspondence of IoT and cloud because of its irregular disordered robust execution, greater affectability for introductory authority dimension, steadiness, and the exceptionally huge crucial area is hypothetically sufficiently able to oppose different known assaults. Cloud servers utilizing CS-ABC to upgrading the safe calculations through a quantum channel inside the cloud framework. Execution examinations and recreation outcomes demonstrate our presented methods are portrayed and also have greater safety, proficiency with strength opposed to a few surely understood assaults which choose them as a great contender for verifying cloud and IoT applications.","PeriodicalId":122556,"journal":{"name":"Journal of Intelligent Systems and Internet of Things","volume":"317 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124288911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

A Trustworthy Learning Technique for Securing Industrial Internet of Things Systems 工业物联网系统安全的可信学习技术

Journal of Intelligent Systems and Internet of Things Pub Date : 1900-01-01 DOI: 10.54216/jisiot.050104

Osama Maher, E. Sitnikova

{"title":"A Trustworthy Learning Technique for Securing Industrial Internet of Things Systems","authors":"Osama Maher, E. Sitnikova","doi":"10.54216/jisiot.050104","DOIUrl":"https://doi.org/10.54216/jisiot.050104","url":null,"abstract":"Since the Industrial Internet of Things (IIoT) networks comprise heterogeneous manufacturing and technological devices and services, discovering advanced cyber threats is an arduous and risk-prone process. Cyber-attack detection techniques have been recently emerged to understand the process of obtaining knowledge about cyber threats to collect evidence. These techniques have broadly employed for identifying malicious events of cyber threats to protect organizations’ assets. The main limitation of these systems is that they are not able to discover and interpret new attack activities. This paper proposes a new adversarial deep learning for discovering adversarial attacks in IIoT networks. Evaluation of correlation reduction has been used as a means of feature selection for reducing the impact of data poisoning attacks on the subsequent deep learning techniques. Feed Forward Deep Neural Networks have been developed using across various parameter permutations, at differing rates of data poisoning, to develop a robust deep learning architecture. The results of the proposed technique have been compared with previously developed deep learning models, proving the increased robustness of the new deep learning architectures across the ToN_IoT datasets.","PeriodicalId":122556,"journal":{"name":"Journal of Intelligent Systems and Internet of Things","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129043864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Solving the Problem of Target k-Coverage in WSNs Using Fuzzy Clustering Algorithm 用模糊聚类算法解决wsn中目标k-覆盖问题

Journal of Intelligent Systems and Internet of Things Pub Date : 1900-01-01 DOI: 10.54216/jisiot.020203

M. .., Zohre .., Mohammad Reza Esfandyari

引用次数: 6

An effective model for Selection of the best IoT platform: A critical review of challenges and solutions 选择最佳物联网平台的有效模型:对挑战和解决方案的批判性回顾

Journal of Intelligent Systems and Internet of Things Pub Date : 1900-01-01 DOI: 10.54216/jisiot.070204

Mahmoud A. Zaher, N. M. Eldakhly

引用次数: 0

Intelligent Waste Management System for Recycling and Resource Optimization 智能废物回收和资源优化管理系统

Journal of Intelligent Systems and Internet of Things Pub Date : 1900-01-01 DOI: 10.54216/jisiot.010205

A. Sleem, Ibrahim Elhenawy

引用次数: 0