Evidence map›Paper›PMID 39598986›Full record

ArticleSensors (Basel, Switzerland)2024

A Cross-Layer Secure and Energy-Efficient Framework for the Internet of Things: A Comprehensive Survey.

Rashid Mustafa, Nurul I Sarkar, Mahsa Mohaghegh, Shahbaz Pervez

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Rashid MustafaDepartment of Computer Science and Software Engineering, Auckland University of Technology, Auckland 1010, New Zealand.
Nurul I SarkarDepartment of Computer Science and Software Engineering, Auckland University of Technology, Auckland 1010, New Zealand.ORCID 0000-0003-2770-8319
Mahsa MohagheghDepartment of Computer Science and Software Engineering, Auckland University of Technology, Auckland 1010, New Zealand.
Shahbaz PervezDepartment of Computer Science and Software Engineering, Auckland University of Technology, Auckland 1010, New Zealand.ORCID 0000-0003-0232-2356

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This survey delves into cross-layer energy-efficient solutions and cutting-edge security measures for Internet of Things (IoT) networks. The conventional security techniques are considered inadequate, leading to the suggestion of AI-powered intrusion detection systems and novel strategies such as blockchain integration. This research aims to promote the development of smart cities by enhancing sustainability, security, and efficiency in the industrial and agricultural sectors through the use of IoT, blockchain, AI, and new communication technologies like 5G. In this paper, we provide a comprehensive review and analysis of secure and energy-efficient cross-layer IoT frameworks based on survey of more than 100 published research articles. We highlight the significance of developing IoT security for robust and sustainable connected systems. We discuss multi-layered security approaches and ways to enhance the energy efficiency of resource-constrained devices in IoT networks. Finally, we identify open research issues and future research directions in the emerging field of cross-layer design for secure and energy-efficient IoT networks. In order to improve cybersecurity and efficiency in smart cities, the research also focuses on developing a secure, energy-efficient IoT framework integrating blockchain, artificial intelligence, and quantum-safe cryptography.

Indexed as

cross-layer frameworkenergy efficientgeneral data protection regulationInternet of Thingssecure IoT

Identifiers

PMID39598986
PMCPMC11598742

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.