Evidence map›Paper›PMID 38732785›Full record

ArticleSensors (Basel, Switzerland)2024

Lightweight Crypto-Ransomware Detection in Android Based on Reactive Honeyfile Monitoring.

José A Gómez-Hernández, Pedro García-Teodoro

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. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

José A Gómez-HernándezNetwork Engineering & Security Group (NESG), School of Computer Science and Telecommunications Engineering (ETSIIT), C/Periodista Daniel Saucedo Aranda s/n, 18071 Granada, Spain.ORCID 0000-0003-4532-1142
Pedro García-TeodoroNetwork Engineering & Security Group (NESG), School of Computer Science and Telecommunications Engineering (ETSIIT), C/Periodista Daniel Saucedo Aranda s/n, 18071 Granada, Spain.ORCID 0000-0001-6766-1936

Funding

Consejería de Universidad, Investigación e Innovación and the European Union through the ERDF Andalusia 2021-2027the project C025/24 INCIBE-UGR,European NextGeneration Funds
6 · The paper itself

Abstract

Given the high relevance and impact of ransomware in companies, organizations, and individuals around the world, coupled with the widespread adoption of mobile and IoT-related devices for both personal and professional use, the development of effective and efficient ransomware mitigation schemes is a necessity nowadays. Although a number of proposals are available in the literature in this line, most of them rely on machine-learning schemes that usually involve high computational cost and resource consumption. Since current personal devices are small and limited in capacities and resources, the mentioned schemes are generally not feasible and usable in practical environments. Based on a honeyfile detection solution previously introduced by the authors for Linux and Window OSs, this paper presents a ransomware detection tool for Android platforms where the use of trap files is combined with a reactive monitoring scheme, with three main characteristics: (i) the trap files are properly deployed around the target file system, (ii) the

Indexed as

Androidcrypto-ransomwaredeceptionearly detectionhoneyfilereactive monitoring

Identifiers

PMID38732785
PMCPMC11085278

What OpenQuestion holds

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LicenceCC BY
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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.