Evidence map›Paper›PMID 40292695›Full record

ReviewSensors (Basel, Switzerland)2025

A Review of the Authentication Techniques for Internet of Things Devices in Smart Cities: Opportunities, Challenges, and Future Directions.

Ashwag Alotaibi, Huda Aldawghan, Ahmed Aljughaiman

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
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

3 authors.

Ashwag AlotaibiDepartment of Computer Networks and Communications, College of Computer Sciences and Information Technology, King Faisal University, Al-Ahsa 31982, Saudi Arabia.
Huda AldawghanDepartment of Computer Networks and Communications, College of Computer Sciences and Information Technology, King Faisal University, Al-Ahsa 31982, Saudi Arabia.
Ahmed AljughaimanDepartment of Computer Networks and Communications, College of Computer Sciences and Information Technology, King Faisal University, Al-Ahsa 31982, Saudi Arabia.ORCID 0000-0001-9176-9453

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Smart cities have witnessed a transformation in urban living through the Internet of Things (IoT), which has improved connectedness, efficiency, and sustainability. However, the adoption of IoT devices presents significant security vulnerabilities, particularly in authentication. The specific limitations of IoT contexts, such as constrained computational resources, are frequently not adequately addressed by traditional authentication techniques. The existing methods of authentication used for IoT devices in smart cities are critically examined in this review study. We evaluate the advantages and disadvantages of each mechanism, emphasizing real-world applicability. Additionally, we examine cutting-edge developments that offer improved security and scalability, such as blockchain technology, biometric authentication, and machine learning-based solutions. This study aims to identify gaps and propose future research directions to develop robust authentication frameworks that protect user privacy and data integrity.

Indexed as

authenticationblockchainedge computingInternet of Thingssmart cities

Identifiers

PMID40292695
PMCPMC11944561

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.