A Framework for Malicious Traffic Detection in IoT Healthcare Environment

Hussain, Faisal; Abbas, Syed Ghazanfar; Shah, Ghalib A.; Pires, Ivan Miguel; Fayyaz, Ubaid U.; Shahzad, Farrukh; García, Nuno M.; Zdravevski, Eftim

doi:10.3390/s21093025

Cited by 122 publications

(75 citation statements)

References 30 publications

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“…To assure network traffic validation, the DPLPLN provides security by recognizing the flooding operation or garbage of packets of Denial of Service (DoS) attacks. Denial of Service (DoS) & Distributed Denial of Service (DDoS) Attacks In Hussain et al. (2021) ; Kamble and Gawade (2020) ; Khatkar et al.…”

Section: Secure Network Architecture and Authentication Approachesmentioning

confidence: 99%

Emerging IoT Applications in Sustainable Smart Cities for COVID-19: Network Security and Data Preservation Challenges with Future Directions

Adil

Khan

2021

Sustainable Cities and Society

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COVID-19 is a global infectious disease that can be easily spread by the contiguity of infected people. To prevent from COVID-19 and reduce its impact in sustainable smart cities, the global research communities are working relentlessly by harnessing the emerging technologies to develop the safest diagnosis, evaluation, and treatment procedures, and Internet of Things (IoT) is one of the pioneers among them. IoT can perform a pivotal role to diminish its immense contagious rate by suitable utilization in emerging healthcare IoT applications in sustainable smart cities. Therefore, the focus of this paper is to outline a survey of the emerging healthcare IoT applications practiced in the perspective of COVID-19 pandemic in terms of network architecture security, trustworthiness, authentication, and data preservation followed by identifying existing challenges to set the future research directions. The salient contributions of this work deal with the accomplishment of a detailed and comprehensive literature review of COVID-19 starting from 2019 through 2021 in the context of emerging healthcare IoT technology. In addition, we extend the correlated contributions of this work by highlighting the weak aspects of the existing emerging healthcare IoT applications, security of different network layers and secure communication environment followed by some associated requirements to address these challenges. Moreover, we also identify future research directions in sustainable smart cities for emerging healthcare IoT utilization in the context of COVID-19 with the most productive results and least network implementation costs.

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Section: Secure Network Architecture and Authentication Approachesmentioning

confidence: 99%

Emerging IoT Applications in Sustainable Smart Cities for COVID-19: Network Security and Data Preservation Challenges with Future Directions

Adil

Khan

2021

Sustainable Cities and Society

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“…Many P2P Botnets show high detection ability in this technique being used. The references [28,29,30] show significant research on usage of detection of anomaly in the system using community based and centrality-based approaches. These approaches show how the enormous number of Botnets can be detected using simple Unsupervised learning approaches.…”

Section: Fig4 Behaviour Based Clusteringmentioning

confidence: 99%

A Report on Botnet Detection Techniques for Intrusion Detection Systems

Sathya¹

2022

IJRASET

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Abstract— A botnet is a malware that degrades the functionality as well as access to a healthy computer system through malware programs. Botnet programs perform DDoS attack, Spam, phishing attacks. Botnet attack takes place in two ways which are peer to peer attacks and command and control attack. The peer-to-peer attack takes place to by passing botnet attacks from one system to another in a peer-to-peer network while the command-and-control attack takes place by a botmaster attack on a server which uses various transactions in exchange with systems on the network and those nodes in the networks function as slaves. The report presents a survey of various techniques of botnet detection models built using several types of machine learning techniques. The report gives the review on various methodologies involved in Botnet Detection and to identify the best methods involved to understand various dataset. We also surveyed on how classification, clustering is used in detection of Botnet to improve the accuracy of the model.

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“…These data can be sensed at a home level or individual devices within a home level. For distribution, the electric loss is also an important parameter [83][84][85][86][87].…”

Section: Internet Of Smart Gridsmentioning

confidence: 99%

Reliable Internet of Things: Challenges and Future Trends

et al. 2021

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The Internet of Things (IoT) is a vital component of many future industries. By intelligent integration of sensors, wireless communications, computing techniques, and data analytics, IoT can increase productivity and efficiency of industries. Reliability of data transmission is key to realize several applications offered by IoT. In this paper, we present an overview of future IoT applications, and their major communication requirements. We provide a brief survey of recent work in four major areas of reliable IoT including resource allocation, latency management, security, and reliability metrics. Finally, we highlight some of the important challenges for reliable IoT related to machine learning techniques, 6G communications and blockchain based security that need further investigation and discuss related future directions.

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A Framework for Malicious Traffic Detection in IoT Healthcare Environment

Cited by 122 publications

References 30 publications

Emerging IoT Applications in Sustainable Smart Cities for COVID-19: Network Security and Data Preservation Challenges with Future Directions

Emerging IoT Applications in Sustainable Smart Cities for COVID-19: Network Security and Data Preservation Challenges with Future Directions

A Report on Botnet Detection Techniques for Intrusion Detection Systems

Reliable Internet of Things: Challenges and Future Trends

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