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dc.contributor.authorGómez Hernández, José Antonio 
dc.contributor.authorGarcía Teodoro, Pedro 
dc.date.accessioned2024-04-24T06:57:02Z
dc.date.available2024-04-24T06:57:02Z
dc.date.issued2024-04-23
dc.identifier.citationGómez-Hernández, J.A.; García-Teodoro, P. Lightweight Crypto-Ransomware Detection in Android Based on Reactive Honeyfile Monitoring. Sensors 2024, 24, 2679. https://doi.org/10.3390/s24092679es_ES
dc.identifier.urihttps://hdl.handle.net/10481/91093
dc.descriptionThis publication results from the project NetSEA-GPT (C-ING-300-UGR23), funded by Consejería de Universidad, Investigación e Innovación and the European Union through the ERDF Andalusia Program 2021–2027, and the project C025/24 INCIBE-UGR, funded with European NextGeneration Funds.es_ES
dc.description.abstractGiven 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 FileObserver service is used to early alert events that access the traps following certain suspicious sequences, and (III) the experimental results show high performance of the solution in terms of detection accuracy and efficiency.es_ES
dc.description.sponsorshipConsejería de Universidad, Investigación e Innovación C-ING-300-UGR23es_ES
dc.description.sponsorshipERDF Andalusia Program 2021–2027es_ES
dc.description.sponsorshipEuropean NextGeneration Funds C025/24 INCIBE-UGRes_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.subjectCrypto-ransomwarees_ES
dc.subjectEarly detectiones_ES
dc.subjectDeceptiones_ES
dc.subjectReactive monitoringes_ES
dc.subjectHoneyfilees_ES
dc.subjectAndroides_ES
dc.titleLightweight Crypto-Ransomware Detection in Android Based on Reactive Honeyfile Monitoringes_ES
dc.typejournal articlees_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/NextGenerationEU/C025/24 INCIBE-UGRes_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.3390/s24092679
dc.type.hasVersionVoRes_ES


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