Evidence map›Paper›PMID 33583978›Full record

ArticleScientometrics2021

Towards a systematic description of the field using bibliometric analysis: malware evolution.

Sharfah Ratibah Tuan Mat, Mohd Faizal Ab Razak, Mohd Nizam Mohmad Kahar, Juliza Mohamad Arif, Salwana Mohamad, Ahmad Firdaus

Abstract read
In one paragraph

Article in Scientometrics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. AI in phishing detection: a bibliometric review.Frontiers in artificial intelligence · 2025
    Pooled it
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

6 authors.

Sharfah Ratibah Tuan MatFaculty of Computing, University Malaysia Pahang, 26300 Gambang, Kuantan, Pahang Malaysia.
Mohd Faizal Ab RazakFaculty of Computing, University Malaysia Pahang, 26300 Gambang, Kuantan, Pahang Malaysia.ORCID 0000-0002-7388-4340
Mohd Nizam Mohmad KaharFaculty of Computing, University Malaysia Pahang, 26300 Gambang, Kuantan, Pahang Malaysia.
Juliza Mohamad ArifFaculty of Computing, University Malaysia Pahang, 26300 Gambang, Kuantan, Pahang Malaysia.
Salwana MohamadFaculty of Computing, University Malaysia Pahang, 26300 Gambang, Kuantan, Pahang Malaysia.
Ahmad FirdausFaculty of Computing, University Malaysia Pahang, 26300 Gambang, Kuantan, Pahang Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Malware is a blanket term for Trojan, viruses, spyware, worms, and other files that are purposely created to harm computers, mobile devices, or computer networks. Malware commonly steals, encrypts, damages, and causes a mess in these devices. The growth of malware attacks has a consequence on the growth and attractiveness of mobile features in mobile devices. Most malware research aims to probe the different methods of preventing, analysing, and detecting malware attacks. This paper aims to demonstrate an exhaustive knowledge map of the Android malware by collecting a ten (10) year dataset from the Web of Science database. A bibliometric analysis was employed for analysing articles published between 2010 and 2019. Using the keyword "malware", 5622 articles were retrieved. After scrutinising with the keywords of "Android malware", 1278 articles were then collected. This study provides an overview of the articles, productivity, research area, the Web of Science categories, authors, high-cited articles, institutions, and impact journals examining malware. Research activities are continued by placing terms in the classification of malware detection systems that outline important areas in malware research. From the analysis, it can be concluded that the highest number of publications focusing on malware studies came from the continent of Asia. Additionally, this study discusses the challenges of malware studies in the recent research studies as well as the future direction.

Indexed as

Android malwareBibliometricIntrusion detection systemWeb of science

Identifiers

PMID33583978
PMCPMC7871169

What OpenQuestion holds

Textmetadata
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.