Next Article in Journal
Hybrid Ensemble Deep Learning Framework with Snake and EVO Optimization for Multiclass Classification of Alzheimer’s Disease Using MRI Neuroimaging
Next Article in Special Issue
Identifying Illicit Activities in Blockchain Transaction Graph Networks
Previous Article in Journal
WIS: A Technology of Wireless Non-Contact Incremental Training Sensing
Previous Article in Special Issue
Securing the Internet of Things: Systematic Insights into Architectures, Threats, and Defenses
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Electronics
Volume 14
Issue 21
10.3390/electronics14214327
electronics-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

RDBAlert: An AI-Driven Automated Tool for Effective Identification of Victims’ Personal Information in Ransomware Data Breaches

by
Juan Manuel Tejada-Triviño
,
Elvira Castillo-Fernández
,
Pedro García-Teodoro
and
José Antonio Gómez-Hernández
*
Network Engineering & Security Group, CITIC, University of Granada, 18014 Granada, Spain
*
Author to whom correspondence should be addressed.
Electronics 2025, 14(21), 4327; https://doi.org/10.3390/electronics14214327
Submission received: 27 September 2025 / Revised: 14 October 2025 / Accepted: 22 October 2025 / Published: 4 November 2025
(This article belongs to the Special Issue Digital Security and Privacy Protection: Trends and Applications, 2nd Edition)
Browse Figures
Review Reports Versions Notes

Abstract

Ransomware attacks are increasingly resulting in the public leakage of sensitive personal data, affecting both individuals and organizations worldwide. Aimed to inform victims when their personal information is compromised, this paper introduces RDBAlert, a rapid and efficient practical tool that automates the extraction of multimodal personal data from ransomware leak repositories, enabling victims to mitigate damage early and take necessary precautions to protect themselves from further harm. The comprehensive and modular nature of this novel tool contributes several notable features: (i) automation of ransomware data leak detection; (ii) analysis of information in multiple formats and languages by integrating well-known OCR, text/PDF, and image recognition, as well as multimodal currently available AI-related tools; (iii) user-friendly interface for quick and efficient analysis; and (iv) ability to gather forensic evidence for studying security incidents. In addition to the flexible nature of RDBAlert–as each module can be replaced or upgraded with potentially more effective solutions without impacting the overall service–experimental results show that it is highly effective at identifying personal information, which will contribute to the mitigation of ransomware attack consequences.
Keywords: ransomware; data breach; leak; LMM ransomware; data breach; leak; LMM

Share and Cite

MDPI and ACS Style

Tejada-Triviño, J.M.; Castillo-Fernández, E.; García-Teodoro, P.; Gómez-Hernández, J.A. RDBAlert: An AI-Driven Automated Tool for Effective Identification of Victims’ Personal Information in Ransomware Data Breaches. Electronics 2025, 14, 4327. https://doi.org/10.3390/electronics14214327

AMA Style

Tejada-Triviño JM, Castillo-Fernández E, García-Teodoro P, Gómez-Hernández JA. RDBAlert: An AI-Driven Automated Tool for Effective Identification of Victims’ Personal Information in Ransomware Data Breaches. Electronics. 2025; 14(21):4327. https://doi.org/10.3390/electronics14214327

Chicago/Turabian Style

Tejada-Triviño, Juan Manuel, Elvira Castillo-Fernández, Pedro García-Teodoro, and José Antonio Gómez-Hernández. 2025. "RDBAlert: An AI-Driven Automated Tool for Effective Identification of Victims’ Personal Information in Ransomware Data Breaches" Electronics 14, no. 21: 4327. https://doi.org/10.3390/electronics14214327

APA Style

Tejada-Triviño, J. M., Castillo-Fernández, E., García-Teodoro, P., & Gómez-Hernández, J. A. (2025). RDBAlert: An AI-Driven Automated Tool for Effective Identification of Victims’ Personal Information in Ransomware Data Breaches. Electronics, 14(21), 4327. https://doi.org/10.3390/electronics14214327

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop