Secure Machine-Type Communications toward LTE Heterogeneous Networks

Zhao, Caidan; Huang, Lianfen; Zhao, Yifeng; Du, Xiaojiang

doi:10.1109/mwc.2017.1600141wc

Cited by 36 publications

(10 citation statements)

References 11 publications

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“…M2M connectivity refers to machine communication without human interventions [ 104 , 105 ]. It has been predicted that more than 15 billion M2M connectivity would occur via the Internet by 2021 [ 106 ]. These machines or devices would be connected, collect data from surrounding environments, and share collected data with each other and humans in high security.…”

Section: ML For Enhancing Connectivity In Iot Environmentsmentioning

confidence: 99%

Machine Learning for Smart Environments in B5G Networks: Connectivity and QoS

Alsamhi

Almalki

Al-Dois

et al. 2021

Computational Intelligence and Neuroscience

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The number of Internet of Things (IoT) devices to be connected via the Internet is overgrowing. The heterogeneity and complexity of the IoT in terms of dynamism and uncertainty complicate this landscape dramatically and introduce vulnerabilities. Intelligent management of IoT is required to maintain connectivity, improve Quality of Service (QoS), and reduce energy consumption in real time within dynamic environments. Machine Learning (ML) plays a pivotal role in QoS enhancement, connectivity, and provisioning of smart applications. Therefore, this survey focuses on the use of ML for enhancing IoT applications. We also provide an in-depth overview of the variety of IoT applications that can be enhanced using ML, such as smart cities, smart homes, and smart healthcare. For each application, we introduce the advantages of using ML. Finally, we shed light on ML challenges for future IoT research, and we review the current literature based on existing works.

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Section: ML For Enhancing Connectivity In Iot Environmentsmentioning

confidence: 99%

Machine Learning for Smart Environments in B5G Networks: Connectivity and QoS

Alsamhi

Almalki

Al-Dois

et al. 2021

Computational Intelligence and Neuroscience

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“…For example, an opponent who manages to falsify an intellectual ID can force their owner to pay the opponent's costs. Even worse it appears as a server, because it can trigger a launch attack [58]. The attackers make an unauthorized M2M device.…”

Section: The Security Challenges and Attacks In Iotmentioning

confidence: 99%

Device Classification for Machine to Machine Communication in Internet of Things for Tele-Robotic Surgery: A Review

Lokhande¹,

Patil²

2021

INDJCSE

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Internet of Things (IoT) domain gradually growing in information technology and telecommunications systems area considering its size and complexity. It is recognized as potential domain in IoT applications. New technologies need to anticipate this sharp increase in the number of varying smart devices. In current perspective, the IOT environment, which allows a huge network of things to communicate with each other, may face a number of technical and application problems, such as privacy concerns, security, sensor anonymity, decision support, a variety of device applications, and so on. In this review paper, goal is to study various frameworks for IoT device classification possible in Tele robotic surgery and summarizes the classification algorithm. Tele robotic surgery needs robust and beneficiary control techniques for providing efficient and precise alternative for medical surgeries. Time delays over network severely impact the stability in the surgery and eventually affect the performance of expert doctors. Also we analyze the problems encountered with the M2M connectivity of network devices.

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“…Therefore, these solutions are not viable for critical infrastructure communication in 5G. Thus a higher level of security for critical communication is achievable by utilizing new security mechanisms such as physical layer security adopting Radio-Frequency (RF) fingerprinting [58], using asymmetric security schemes [59] and dynamically changing security parameters according to the situation [21]. Similarly, end-to-end user communication can be secured by using cryptographic protocols like HIP as presented in [60].…”

Section: Security Solutions For Communication Channelsmentioning

confidence: 99%

5G security: Analysis of threats and solutions

Ahmad

Kumar

Liyanage

et al. 2017

2017 IEEE Conference on Standards for Communications and Networking (CSCN)

133

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5G will provide broadband access everywhere, entertain higher user mobility, and enable connectivity of massive number of devices (e.g. Internet of Things (IoT)) in an ultrareliable and affordable way. The main technological enablers such as cloud computing, Software Defined Networking (SDN) and Network Function Virtualization (NFV) are maturing towards their use in 5G. However, there are pressing security challenges in these technologies besides the growing concerns for user privacy. In this paper, we provide an overview of the security challenges in these technologies and the issues of privacy in 5G. Furthermore, we present security solutions to these challenges and future directions for secure 5G systems.

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Secure Machine-Type Communications toward LTE Heterogeneous Networks

Cited by 36 publications

References 11 publications

Machine Learning for Smart Environments in B5G Networks: Connectivity and QoS

Machine Learning for Smart Environments in B5G Networks: Connectivity and QoS

Device Classification for Machine to Machine Communication in Internet of Things for Tele-Robotic Surgery: A Review

5G security: Analysis of threats and solutions

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