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Ransomware Detection for Securing Hybrid Learning Environments in Educational Institutions

  • Pavlos Kampouris
  • , Paul Jenkins*
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Ransomware has become a significant cybersecurity threat, particularly within the education sector. The sometimes-outdated infrastructure, limited security investment for robust defence and the high-value data, make institutions such as schools, colleges and universities valuable sources of information and therefore valuable targets. This paper investigates the anatomy of the attack, with the aim of suggesting the development of an ethical and functional anti-ransomware tool. A review of related material regarding existing anti-ransomware tools such as Bitdefender, Malwarebytes and Microsoft Defender which provide strong behavioural detection is examined and results presented, which provides the basis of the development; however, they often find it difficult working in the operating environments in the education sector, as they are developed to operate on up-to-date equipment, thus it can cause issues in detecting malware. Following the research, a pilot piece of software was developed to test and investigate the issues raised. The software was designed to detect and decrypt a ransomware file and folders.

Original languageEnglish
Title of host publicationContributions Presented at the International Conference on Computing, Communication, Cybersecurity and AI - The C3AI 2025
EditorsNitin Naik, Paul Grace, Paul Jenkins, Shaligram Prajapat
PublisherSpringer Science and Business Media Deutschland GmbH
Pages807-830
Number of pages24
ISBN (Electronic)9783032167910
ISBN (Print)9783032167903
DOIs
Publication statusPublished - 17 May 2026
EventInternational Conference on Computing, Communication, Cybersecurity and AI, C3AI 2025 - Birmingham, United Kingdom
Duration: 10 Jul 202511 Jul 2025

Publication series

NameLecture Notes in Networks and Systems
Volume1811 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

ConferenceInternational Conference on Computing, Communication, Cybersecurity and AI, C3AI 2025
Country/TerritoryUnited Kingdom
CityBirmingham
Period10/07/2511/07/25

Keywords

  • Cybersecurity
  • Decryption
  • Education sector
  • Encryption
  • Ransomware

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