Performance Evaluation of ASCO-OFDM Based LiFi

Munni, Shahfida Amjad; Islam, Rashed; Mondal, M. Rubaiyat Hossain

doi:10.18178/ijfcc.2020.9.2.562

Cited by 2 publications

(2 citation statements)

References 11 publications

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“…Different entities, such as IoT devices, servers and users, communicate through the Internet. Wi-Fi [11,12], WiMax [13,14], LTE [15,16] are the popular forms of using Internet effectively. Light fidelity (LiFi) [11][12][13][14][15][16] is also an emerging technology for the Internet.…”

Section: Fig 1: An Overview Of Cloud Integrated Iot Systemmentioning

confidence: 99%

“…Wi-Fi [11,12], WiMax [13,14], LTE [15,16] are the popular forms of using Internet effectively. Light fidelity (LiFi) [11][12][13][14][15][16] is also an emerging technology for the Internet. OFDM, MIMO systems are playing a vital role in order to establish upgraded wireless communication systems [17][18].…”

Section: Fig 1: An Overview Of Cloud Integrated Iot Systemmentioning

confidence: 99%

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Review on the Security Threats of Internet of Things

Podder¹,

Mondal²,

Bharati³

et al. 2020

IJCA

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Internet of Things (IoT) is being considered as the growth engine for industrial revolution 4.0. The combination of IoT, cloud computing and healthcare can contribute in ensuring well-being of people. One important challenge of IoT network is maintaining privacy and to overcome security threats. This paper provides a systematic review of the security aspects of IoT. Firstly, the application of IoT in industrial and medical service scenarios are described, and the security threats are discussed for the different layers of IoT healthcare architecture. Secondly, different types of existing malware including spyware, viruses, worms, keyloggers, and trojan horses are described in the context of IoT. Thirdly, some of the recent malware attacks such as Mirai, echobot and reaper are discussed. Next, a comparative discussion is presented on the effectiveness of different machine learning algorithms in mitigating the security threats. It is found that the k-nearest neighbor (kNN) machine learning algorithm exhibits excellent accuracy in detecting malware. This paper also reviews different tools for ransomware detection, classification and analysis. Finally, a discussion is presented on the existing security issues, open challenges and possible future scopes in ensuring IoT security.

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